9. Procedure Automation Strategy - Planning and Definition

This activity takes the available resources and converts them into a Procedure Automation Lifecycle template for each specific automation project within the defined work scope. The template approach gives implementers flexibility to handle different project scales - whether automating large, complex systems with multiple interconnected processes, or implementing automation for a single standalone procedure.

Definition: A Procedure Automation Lifecycle template serves as a standardized framework that guides the automation implementation from initial planning through deployment and maintenance.

In both scenarios, the core requirements from the Company’s procedure automation philosophy remain consistent. However, the specific tool kits (software packages, configuration utilities, and diagnostic tools) and workflows (step-by-step processes for design, testing, and commissioning) included in each template can be customized based on project complexity and scope.

Industrial Example: A large chemical plant might use a template with advanced process modeling tools and multi-stage validation workflows, while a simple pump control automation might use a streamlined template with basic configuration tools and simplified testing procedures.

9.1 Setting the Scope

9.1.1 Introduction

The scope is defined by participants identified in Section 8.1.7 of this standard (refer to that section for the complete list of system components, stakeholders, and operational boundaries that determine what falls within the control system’s area of responsibility).

Note: Understanding scope definition is critical for control engineers as it establishes clear boundaries for system design, safety responsibilities, and operational limits during implementation and maintenance phases.

The process of setting the scope starts with gathering information that will feed into your planning and definition activities (this forms the foundation for your entire control system design). You’ll typically need to collect the following documents and information:

Note: Think of this as building your project requirements database - without complete input information, your control system design will likely have gaps that lead to costly changes later in the project.

Definition: Scope setting in control engineering refers to clearly defining what your control system needs to accomplish, what equipment it will interface with, and what performance requirements it must meet.

• Procedure Automation Strategy, including the procedure automation philosophy and toolkits.
• Standards and guidelines are referenced by the procedure automation philosophy.
• List of candidate procedures to be automated.
• Process Flow Diagrams (PFDs), Piping & Instrument Diagrams (P&IDs), system architecture diagrams, process descriptions, control narratives, standard operating procedures (including alarm response procedures and troubleshooting guides), procedure templates, and process simulations.
• Goals and objectives for the scope of the procedural automation.
• Hazardous operations results and findings.
• Availability and skill level of the workforce.
• Site Management of Change procedures.
• Root cause analysis of incidents in the plant or similar plants that could have been avoided with procedure automation.
• Regulatory constraints on the lifecycle instance.

The key outcomes of this activity are:

Note: These deliverables represent the essential documentation and analyses that must be completed to ensure proper system design and regulatory compliance. Each outcome serves a specific purpose in the overall control system development process.

Definition: Activity outcomes in control engineering refer to the measurable deliverables, documentation, or system improvements that result from completing a specific engineering task or project phase.

Industrial Example: Common outcomes might include updated P&IDs (piping and instrumentation diagrams), tuned PID controller parameters, validated safety interlocks, or commissioned HMI screens that operators will use for process monitoring and control.

• The Physical Model, as described in Chapter 4 of this standard, including a gap assessment.
• Prioritized list of procedures to be automated with their goals and objectives.
• Business justification with cost and Return on Investment estimates.

9.1.2 Physical Model

The creation of the Physical Model (a digital representation of your plant’s equipment and their relationships) as described in Chapter 4 of this standard is an iterative process. Before the creation of the automated procedure lifecycle instance, work on the Physical Model may have been started. The key aspects in this activity are to determine the boundaries and structure of the Physical Model and make sure it is aligned with the process design, I/O plans (input/output wiring and signal documentation), and construction plans.

Definition: The Physical Model is defined to the device level - meaning it includes individual instruments, valves, motors, and other field devices - to support the identification of procedures that are candidates to be automated.

Note: This device-level detail is crucial because automation procedures need to know exactly which physical equipment they will control, from sensors providing feedback to final control elements like control valves.

This activity involves matching up the input/output (I/O) points that are currently available or planned for installation with what’s actually needed to automate specific procedures. When automating procedures, you’ll typically find that additional control signals and measurement signals from field devices are required to achieve the target automation level.

Definition: I/O points include analog inputs (like temperature transmitters), digital inputs (like valve position feedback), analog outputs (like control valve signals), and digital outputs (like pump start/stop commands).

As you identify which procedures need automation, you may discover gaps between your current I/O configuration and what’s required. This often means updating the Physical Model (the documented representation of all system components and their connections) to include these additional I/O requirements.

Industrial Example: If you’re automating a batch mixing procedure, you might realize you need additional flow measurement signals or level transmitters that weren’t originally specified, requiring updates to both your I/O list and system documentation.

9.1.3 Identifying Procedures to be Automated

In this activity, you’ll compile a list of candidate procedures that could be automated (procedures that can be converted from manual operator tasks to automated control system functions). The selection criteria you use will depend on your organization’s current automation experience level. A company just beginning their automation journey will typically use different criteria than one with extensive automation experience.

Note: Organizations new to procedure automation should focus on low-risk, frequently executed procedures first. This approach allows you to gain practical experience and develop company-wide standards for critical automation elements.

Key automation elements to standardize include: - Automation styles: Sequential control, state-based logic, or hybrid approaches

- Exception handling: How the system responds to unexpected conditions or equipment failures
- Operator interface: HMI design, alarm management, and manual override capabilities

This iterative approach helps build confidence and expertise before tackling more complex or safety-critical automated procedures.

All automated procedures should be linked to specific components in the Physical Model (the digital representation of your actual plant equipment and instruments) and documented in the Procedure Specification Model (the structured database that defines how each automated sequence should execute).

Note: This linkage ensures that every automated procedure has clear ties to the physical hardware it controls and maintains proper documentation for maintenance, troubleshooting, and regulatory compliance.

Attributes of candidate operating procedures may include:

Definition: Candidate operating procedures are potential control strategies or operational methods that are being evaluated for implementation in a process control system.

When evaluating these procedures, control engineers typically consider several key characteristics. Each procedure should demonstrate measurable performance metrics, such as response time to setpoint changes and steady-state accuracy. The procedures must also show compatibility with existing control hardware and software infrastructure, including DCS (Distributed Control System) or PLC (Programmable Logic Controller) platforms.

Safety considerations are paramount, requiring each candidate procedure to maintain process variables within safe operating limits and include appropriate emergency shutdown sequences. Economic factors play a crucial role as well, encompassing both implementation costs and ongoing operational expenses like energy consumption and maintenance requirements.

Note: The robustness of a procedure refers to its ability to maintain stable control performance despite process disturbances, measurement noise, or minor equipment variations.

Operational complexity should be balanced with control effectiveness - procedures that are too complex may be difficult for operators to understand and troubleshoot, while overly simple approaches might not adequately handle process dynamics. Additionally, each candidate should include provisions for tuning and optimization, allowing for future adjustments as process conditions change or equipment ages.

Industrial Example: In a temperature control loop, one candidate procedure might use a basic PID controller, while another might employ cascade control with feedforward compensation for better disturbance rejection.

• Complex operation
• Time critical operation
• Repetitive operation
• Hazardous operation
• Safety basis operation
• Offload operator from frequent, low-value activities
• Infrequently performed operations
• Communication between, and coordination of procedures between, control room and field operators
• Communication between operators in upstream and downstream unit control rooms
• Degree of operator interaction
• Support of regulatory requirements

When implementing automation in industrial control systems, automated procedures typically fall into several key categories (this list covers the most common types but isn’t exhaustive):

Start-up Sequences: These procedures systematically bring equipment or entire process units online in the correct order. They handle tasks like pre-checks, equipment initialization, and ramping process variables to setpoints.

Shutdown Procedures: Both planned and emergency shutdown sequences that safely take equipment offline while protecting against damage and ensuring personnel safety.

Batch Operations: Step-by-step automated sequences for batch manufacturing processes, including ingredient additions, mixing cycles, heating/cooling phases, and product discharge.

Maintenance Routines: Automated procedures for routine maintenance tasks such as equipment cleaning cycles (Clean-in-Place systems), calibration sequences, and diagnostic tests.

Safety Interlocks: Automated responses triggered by safety systems when dangerous conditions are detected, such as high pressure trips or gas detection alarms.

Process Optimization: Procedures that automatically adjust process parameters to maintain optimal performance, efficiency, or product quality based on current operating conditions.

Alarm Response: Automated corrective actions taken when specific alarms occur, helping to stabilize the process before operator intervention is required.

Note: The specific categories you’ll encounter depend heavily on your industry sector and the complexity of your control systems. Most modern DCS (Distributed Control System) and PLC platforms provide built-in tools for creating and managing these automated procedures.

9.1.3.1 Normal Operation

Procedure automation for normal operation primarily involves continuously monitoring the process for deviations, such as changes in flow rates, temperature variations, or typical external disturbances (like ambient temperature shifts or supply pressure fluctuations), and then initiating the appropriate corrective response through the control system.

Industrial Example: In a heat exchanger system, the automation monitors inlet temperature and flow rate. When it detects a disturbance like increased cooling water temperature, it automatically adjusts the valve position or pump speed to maintain the desired outlet temperature setpoint.

Note: The key here is distinguishing between “normal” disturbances that the automated system can handle versus abnormal conditions that may require operator intervention or safety system activation.

9.1.3.2 Start-up

A petrochemical plant with multiple cracking furnaces (high-temperature units that break down hydrocarbons into smaller molecules) that require periodic offline maintenance shutdowns. After maintenance work is completed, automated startup sequences can be implemented to safely bring each furnace back to normal operating conditions.

Note: These automated procedures typically include temperature ramping, pressure stabilization, and flow rate adjustments that follow predetermined setpoints to ensure safe and efficient furnace restart without operator intervention.

9.1.3.3 Shutdown

Industrial Example: A petrochemical plant containing multiple cracking furnaces (high-temperature reactors that break down hydrocarbons into smaller molecules) which are taken offline periodically for maintenance. Automated control sequences can be used to safely shut down and isolate the furnace in preparation for maintenance activities.

Note: These automated procedures typically include coordinated steps like reducing feed rates, purging lines with inert gas, and bringing temperatures down in a controlled manner to ensure safe maintenance conditions.

9.1.3.4 Transition

A manufacturing facility produces multiple products using the same process line, switching from one product to another without stopping production (this is called “on-the-fly” changeover). Automating this transition procedure through the control system ensures that each product changeover happens consistently and repeatably every time. This automation significantly reduces the amount of off-specification material produced during the transition period, which improves overall yield and reduces waste.

Note: Off-spec products are materials that don’t meet quality specifications and typically must be reworked or discarded, making them costly to the operation.

9.1.3.5 Enabling or disabling BPCS-resident engineering safeguards

Procedure automation systems can dynamically enable or disable specific safety systems based on the current operating state of the process. This is necessary because certain overrides, interlocks, or alarms are only relevant during particular phases of operation.

Definition: Interlocks are safety mechanisms that prevent equipment operation under unsafe conditions, while overrides allow operators to bypass normal control logic when necessary.

Industrial Example: A high-temperature alarm might be disabled during a planned heating sequence but automatically re-enabled once the process returns to normal operation.

The procedure automation manages these state-dependent safeguards as part of its overall control of operational states and transitions between them. This ensures that safety systems remain active when needed while preventing nuisance alarms or inappropriate lockouts during valid operational phases.

9.1.3.6 Common and repeatable operator activities

During steady state operation (when the process is running at constant, stable conditions), procedure automation systems can monitor the inventory levels of critical feedstocks and calculate projected consumption rates based on current usage patterns. When inventory reaches predetermined thresholds, the system automatically notifies the operator to initiate delivery of new feedstock materials.

Industrial Example: In a chemical plant, the automation system tracks raw material tanks and calculates depletion rates. If Tank A containing reactant X is projected to run empty in 48 hours based on current flow rates, the system alerts operators to schedule the next delivery truck before a supply shortage occurs.

Note: This predictive inventory management helps prevent costly production shutdowns due to material shortages while avoiding excessive inventory holding costs.

9.1.3.7 Alarm response

When working with process alarms, you’ll encounter situations where the standard alarm banner (the notification that appears on your HMI screen) or basic help popup doesn’t provide enough detail for operators to properly respond. This is especially common with complex process upsets or cascading alarm scenarios.

Industrial Example: Consider a distillation column temperature alarm - the basic banner might just show “T-101 HIGH,” but operators need to know the potential causes (fouled reboiler, composition changes, control valve issues) and the proper response sequence.

Procedure automation (automated step-by-step guidance systems) can bridge this gap by delivering detailed troubleshooting instructions, safety considerations, and response procedures directly to the operator interface when these complex alarms occur. This helps ensure consistent and appropriate responses, particularly valuable during shift changes or when less experienced operators are on duty.

Note: This approach is particularly useful for infrequent but critical alarms where operators might not immediately recall the proper response procedure.

9.1.3.8 Abnormal situation response

The procedure automation system can automatically initiate degradation scenarios (predetermined safety responses) when it detects specific abnormal process conditions. These degradation scenarios serve as protective measures and can include several strategies: executing a controlled process shutdown before the Safety Instrumented System (SIS) forces an emergency shutdown, transitioning the process to a less efficient but stable operating state, or engaging constraint control strategies that maintain operation within safe boundaries.

Note: Degradation scenarios act as intermediate safety layers between normal operation and emergency shutdown, helping prevent process upsets from escalating to SIS activation.

Industrial Example: In a reactor temperature control scenario, the automation might reduce feed rate and increase cooling when temperature approaches limits, rather than waiting for the SIS to trigger an emergency shutdown at the safety limit.

9.1.3.9 Emergency situation response

When an abnormal process condition (such as high pressure, temperature excursion, or equipment malfunction) occurs in a plant system, operators have a limited time window to identify and correct the issue through normal control actions. If this abnormal situation cannot be resolved within the available timeframe, it escalates into an emergency situation that triggers an automatic or manual emergency shutdown sequence (ESD). At this point, the primary focus shifts from process control to personnel safety protection and requires immediate notification of emergency response teams, management, and potentially external authorities beyond the standard operations crew.

Industrial Example: A reactor temperature rising above normal setpoint is abnormal - operators can adjust cooling or reduce feed rate. If temperature continues climbing toward safety limits despite these actions, an emergency shutdown activates to isolate the reactor and alert the emergency response team.

9.1.3.10 Equipment outage mitigation

A process contains two centrifuges used for product refining. The centrifuges are not identical and hence operate differently. When the primary centrifuge has an outage (unplanned shutdown or maintenance), the automation system can control the changeover to the backup unit. This includes transitioning feeds and adjusting other operating conditions as needed to maintain process continuity.

Note: The control logic must account for the different operating characteristics between the two centrifuges, such as speed setpoints, flow rates, and timing sequences, to ensure smooth transitions without product quality issues or safety concerns.

9.1.3.11 Data entry and calculations

Operators sometimes are required to make calculations and enter the results in a log or into the system.

Common Examples: Calculating efficiency percentages from flow and temperature readings, determining material balance corrections, or computing setpoint adjustments based on measured process variables (PVs). These calculations might involve simple arithmetic like averaging multiple sensor readings or more complex formulas for heat transfer coefficients.

Note: Many modern control systems can automate these calculations through function blocks or custom logic, but manual calculation is still necessary when sensors fail, during commissioning, or when troubleshooting unexpected process behavior.

Creating the list of candidate procedures for a brownfield project (upgrading or modifying an existing plant) or existing plant involves an analysis of current operations. For a greenfield project (building a new plant from scratch), an analysis of similar plants may be performed. The impact on the operations staffing plan may be used as a criterion for refining the list of candidates to ensure operations staffing plans are aligned with the automated procedure plans.

Note: When identifying which processes to automate, consider how automation will change operator workload and responsibilities. Reducing manual tasks in one area might allow operators to focus on higher-priority activities elsewhere, but this requires careful coordination between automation design and workforce planning.

Industrial Example: In a chemical plant brownfield project, you might analyze current batch procedures that operators perform manually every 2-4 hours. These repetitive, time-consuming tasks often become prime candidates for automation, freeing operators to handle exception management and quality oversight instead.

Each candidate automated procedure must be mapped to the Physical Model (the mathematical representation of your process equipment and dynamics). Define the scope, objectives, and goals of each candidate procedure at a sufficiently high level to enable clear implementation of a compliant control design. This means specifying what the procedure will accomplish, which process units it will control, and the desired operational outcomes.

Important: Document major impact items that will affect your control strategy, particularly any requirements for advanced control techniques such as model predictive control (MPC), cascade control loops, or feedforward compensation. These requirements will significantly influence your control system architecture and implementation approach.

Note: The mapping between your automated procedure and Physical Model ensures that your control logic aligns with the actual process behavior and constraints.

In large projects that include multiple candidate procedures, the candidate list will typically undergo several refinement cycles throughout the pre-FEED (pre-Front End Engineering Design) and FEED phases. This iterative refinement occurs as business constraints evolve and Process Automation Objectives are updated to reflect changing project requirements.

Note: Pre-FEED and FEED are early project phases where engineers define the scope, technology selection, and basic design parameters before detailed engineering begins.

Industrial Example: A refinery expansion project might start with 15 candidate control strategies during pre-FEED, then narrow down to 8 after economic constraints are clarified, and finally select 3-4 strategies during FEED based on finalized automation objectives and safety requirements.

9.1.4 Selection of Procedures to Automate

Since automating procedures requires significant engineering time and resources, implementing a ranking system proves very useful for prioritizing which processes to automate first. This ranking should evaluate several key factors: the consequences of manual operation (safety risks, quality impacts, downtime costs), the technical complexity of the automation implementation, financial considerations (both implementation costs and expected savings), and how frequently the procedure will be executed.

Note: A procedure used daily with high safety consequences should typically rank higher for automation than a monthly procedure with minimal risk, even if the monthly procedure is technically simpler to automate.

Practical Approach: Consider creating a scoring matrix that weighs each factor according to your facility’s priorities - safety-critical operations might receive higher weighting than cost savings in some industries.

The list of candidate automated procedures should be further analyzed, prioritized and selected for automation. Based upon these criteria candidate automated procedures are selected for automation. When evaluating which processes to automate first, control engineers typically consider several key factors that determine both the feasibility and return on investment.

Note: This selection process is critical because automating the wrong procedures first can waste resources and create system complexity without meaningful benefits.

Criteria for prioritization and selection may include:

Definition: Candidate automated procedures are potential control processes that have been identified as suitable for automation but require further evaluation before implementation. This evaluation helps ensure that automation efforts focus on processes that will deliver the greatest operational improvements while remaining technically feasible within current system constraints.

9.1.4.1 Safety impact

A procedure that was developed in response to a previous near miss incident can be implemented using automation to minimize the likelihood of a similar event occurring in the future. By automating critical safety procedures (rather than relying on manual operator actions), we can eliminate human error factors and ensure consistent execution of protective measures.

Industrial Example: If operators previously forgot to engage safety interlocks during equipment maintenance, implementing automated interlock sequences through the control system can prevent this oversight from happening again.

Note: Near miss incidents are events that could have resulted in injury, equipment damage, or process upset but didn’t due to chance or timely intervention - they serve as valuable learning opportunities for improving safety systems.

BPCS procedures that reduce the likelihood of activating a higher-level safety response system.

Definition: BPCS (Basic Process Control System) refers to the primary control system that maintains normal process operations through standard regulatory control loops, alarms, and operator interventions.

Control Engineering Context: These procedures work as the first line of defense by keeping process variables within safe operating ranges. When BPCS functions properly, it prevents conditions that would otherwise require intervention from higher-level safety systems like Safety Instrumented Systems (SIS) or emergency shutdown systems.

Industrial Example: A temperature control loop in a reactor that maintains setpoint prevents overheating conditions that would trigger an emergency cooling system or plant shutdown sequence.

9.1.4.2 Regulatory impact

Environmental controls to maintain emissions within regulatory requirements.

Definition: These are automated control systems that continuously monitor and adjust industrial processes to keep pollutant emissions below legally mandated limits set by environmental agencies like the EPA.

Industrial Example: A coal-fired power plant uses a feedback control loop with stack gas analyzers (sensors that measure pollutant concentrations in exhaust gases) to automatically adjust limestone injection rates in the flue gas desulfurization system, ensuring SO₂ emissions stay below the permitted threshold of 0.6 lbs/MWh.

Note: These systems typically employ cascade control strategies where the primary controller maintains the process variable (like furnace temperature) while secondary controllers manage emission control equipment (scrubbers, baghouses, or selective catalytic reduction systems) based on real-time emission measurements.

9.1.4.3 Economic impact

A procedure that captures the control actions and operating techniques of your most skilled operator during a grade change (transition between different product specifications) can be standardized and implemented across all shifts to reduce changeover time and operating costs.

Industrial Example: If your best operator consistently completes polymer grade transitions 20% faster with less off-spec material, documenting their valve sequencing, setpoint timing, and override strategies allows other operators to achieve similar performance.

Note: This approach works best when the efficient operator’s actions can be reliably reproduced through detailed procedures or automated sequences in your DCS (Distributed Control System).

9.1.4.4 Operational impact

Automation of repetitive procedures currently performed by an operator can free up operators for higher value-added activities.

Definition: Repetitive procedures include tasks like routine data logging, valve adjustments based on setpoints, or periodic equipment status checks that follow the same sequence each time.

Industrial Example: Instead of having an operator manually adjust steam valve positions every 30 minutes based on pressure readings, implementing a PID controller (proportional-integral-derivative controller that automatically adjusts output based on error between setpoint and measured value) allows the operator to focus on process optimization, troubleshooting abnormal conditions, or equipment maintenance planning.

Note: This approach typically improves both process consistency and operator job satisfaction while reducing the potential for human error in routine tasks.

The capture of knowledge from experienced operators can be used in operator assistance procedures to train less experienced operators. This knowledge transfer process involves documenting the decision-making patterns, troubleshooting methods, and operational best practices that seasoned operators have developed through years of hands-on experience.

Industrial Example: An experienced operator might know that when a particular temperature controller starts oscillating, the issue is often caused by a sticky valve rather than tuning problems. This type of practical insight can be captured and incorporated into training procedures or operator decision support systems.

Note: These operator assistance procedures can be implemented through various methods including standard operating procedures (SOPs), computerized operator support systems, or mentorship programs that systematically transfer tacit knowledge from senior to junior staff.

9.1.4.5 Infrastructure requirements

Example: Due to critical operations requirements, the automated procedure must be run in a controller (a dedicated hardware device that executes control logic in real-time).

Note: Controllers are preferred for critical operations because they provide deterministic timing and reliable execution compared to general-purpose computers, ensuring the process responds predictably even under high system loads.

Operator assistance procedures may run in an application server (a dedicated computing platform that hosts and executes software applications separate from the main control system).

Note: This architecture allows the assistance procedures to operate independently from critical control functions, providing operational guidance without interfering with real-time process control. The application server typically communicates with the control system through standard industrial protocols to gather process data and display relevant information to operators.

9.1.4.6 Risk assessment

Procedure automation can help reduce risks that come from industrial and chemical hazards or security threats. By automating critical procedures, we remove the need for human operators to be physically present in dangerous environments or to manually execute complex safety sequences that could be prone to human error.

Industrial Example: In a chemical processing plant, automated emergency shutdown procedures can isolate hazardous materials and safely depressurize systems faster and more reliably than manual operator intervention.

Note: Automation systems typically use programmed logic controllers (PLCs) or distributed control systems (DCS) to execute these safety procedures based on predetermined sensor inputs and safety interlocks.

Procedure automation can increase upfront project expenses and extend implementation timelines, but typically reduces long-term operational costs through improved efficiency and reduced manual labor requirements.

Note: When evaluating automation projects, control engineers should perform a cost-benefit analysis comparing initial capital expenditure (CAPEX) against ongoing operational expenditure (OPEX) savings to determine the project’s return on investment (ROI).

Industrial Example: Automating a manual valve sequencing procedure may require additional I/O modules, programming time, and testing phases (increasing project costs), but eliminates the need for operators to perform routine valve operations, reducing labor costs and human error over the system’s lifecycle.

9.1.4.7 Frequency of use

Decoking a furnace is an infrequently performed maintenance procedure (typically done every few months to remove carbon buildup from furnace tubes). Since operators may not be familiar with the complex sequence of steps due to its infrequent nature, automating this procedure through programmed control sequences can significantly reduce the risk of operational errors and improve safety.

Note: Decoking involves shutting down the furnace, purging with steam, and burning off accumulated coke deposits - a process that requires precise timing and coordination of multiple control loops.

Example: Liquid nitrogen truck loading is frequently performed several times per shift. Automating this procedure may significantly reduce operational effort.

Process Context: Liquid nitrogen loading typically involves multiple manual steps including connecting transfer lines, monitoring flow rates, and ensuring proper fill levels - tasks that consume considerable operator time each shift.

Automation Benefits: Implementing automated control systems (using flow sensors, level transmitters, and pneumatic valves) can reduce the manual workload by handling routine sequencing and monitoring tasks, allowing operators to focus on other critical activities.

Note: The repetitive nature of this process makes it an ideal candidate for automation, as the control logic can be standardized and the return on investment is typically achieved quickly due to labor savings.

The outcome of this activity is a list of procedures that will be automated (converted from manual operations to automatic control system operations).

Note: These procedures typically include repetitive tasks, safety-critical operations, or processes requiring precise timing that are better handled by control systems rather than human operators.

9.1.5 Business Justification

Once you’ve finished developing the Physical Model (a mathematical representation of the system’s behavior) and documented all the procedures that need automation, you should prepare a business justification before moving forward. This justification serves as a key input for management approval, which is required before you can begin the detailed specifications and design phases of your control system project.

Note: The business justification typically includes cost-benefit analysis, ROI calculations, and risk assessments that help stakeholders understand why the automation project is worth pursuing.

When building a business case for a control system project, several key factors should be evaluated to demonstrate return on investment and project value:

Cost Factors: - Initial capital expenditure for hardware, software, and installation - Engineering and commissioning costs (time spent on system configuration, tuning, and startup) - Training expenses for operators and maintenance personnel - Ongoing maintenance and support costs

Operational Benefits: - Improved process efficiency and reduced energy consumption - Enhanced product quality and reduced waste or rework - Increased throughput or production capacity - Better regulatory compliance and reduced risk of violations

Safety and Risk Considerations: - Reduced safety incidents through automated safety systems (SIS - Safety Instrumented Systems) - Lower insurance premiums due to improved risk profile - Minimized environmental impact and associated liability

Competitive Advantages: - Faster response to market demands through flexible automation - Enhanced data collection capabilities for process optimization - Reduced labor costs through automation of manual tasks

Note: When presenting to management, quantify benefits wherever possible using metrics like payback period, net present value (NPV), or internal rate of return (IRR). Include both tangible benefits (direct cost savings) and intangible benefits (improved safety culture, enhanced reputation) to build a comprehensive justification.

• Maximizing equipment availability and safety

Example: Minimum safety incidents

This objective focuses on reducing the frequency of safety-related events in the control system to the lowest achievable level. Safety incidents in control engineering typically include equipment malfunctions, process deviations that could lead to hazardous conditions, emergency shutdowns, and operator safety events.

Industrial Example: In a chemical processing plant, this might involve minimizing unplanned reactor trips, preventing pressure vessel over-pressurization, or reducing instances where safety interlocks activate due to process upsets.

Note: This is often measured through safety metrics like Total Recordable Incident Rate (TRIR) or the frequency of Safety Instrumented System (SIS) activations. The control strategy should incorporate robust fault detection, redundant safety systems, and predictive maintenance to achieve this objective.

Example: Minimum Equipment Replacement

When designing control systems, engineers must consider the economic lifecycle of field equipment and instrumentation. The minimum equipment replacement strategy focuses on determining the optimal point to replace control components before they reach end-of-life, balancing maintenance costs against system reliability.

This approach involves analyzing failure rates, maintenance schedules, and replacement costs for critical control elements like sensors, actuators, and I/O modules. The goal is to minimize total cost of ownership while maintaining acceptable system performance and safety margins.

Key factors to evaluate:

• Mean time between failures (MTBF) for each component
• Preventive maintenance intervals versus reactive repair costs
• Impact of equipment failure on overall process control
• Availability of spare parts and technical support

Industrial Example: In a temperature control loop, replacing aging RTD sensors proactively based on drift patterns and calibration history can prevent process upsets that would cost significantly more than the sensor replacement itself.

Note: This strategy requires maintaining detailed equipment history and performance data to make informed replacement decisions rather than running equipment to complete failure.

Example: Maximum Asset Reliability and Minimum Equipment Redundancy

This scenario focuses on achieving the highest possible reliability from your primary assets while keeping backup equipment to an absolute minimum. In practical terms, this means designing control systems that maximize uptime of critical equipment (pumps, compressors, reactors) without relying heavily on standby units.

Key Control Strategy: Implement advanced predictive maintenance algorithms and real-time monitoring to prevent failures before they occur, rather than depending on redundant equipment to handle breakdowns.

Industrial Example: A single main reactor with sophisticated condition monitoring sensors and predictive controls, rather than installing a backup reactor. The control system continuously monitors vibration, temperature trends, and performance parameters to schedule maintenance during planned outages.

Trade-off Consideration: This approach requires extremely robust control logic and monitoring systems, as equipment failure has immediate process impact. Higher initial investment in advanced sensors and control algorithms is offset by lower capital costs for redundant equipment.

Note: This strategy works best for processes with flexible scheduling or when equipment has proven high reliability records in similar applications.

Example: Transitioning a process from one state to another without negative impact or damage to production equipment

When changing operating conditions in an industrial process (such as moving from startup to normal operation, or switching between different production modes), the transition must be carefully managed to avoid equipment damage or production losses. This involves implementing smooth setpoint changes, proper sequencing of control actions, and monitoring critical process variables throughout the transition.

Industrial Example: When starting up a distillation column, you can’t simply jump from ambient temperature to operating temperature - this requires a gradual ramp-up of heating while monitoring pressure, temperature profiles, and flow rates to prevent thermal shock to the column internals.

Note: Successful transitions often require temporary adjustment of controller tuning parameters (PID gains) or switching to different control strategies during the transition period, then returning to normal control once steady-state is achieved.

• Increasing revenues

Example: Minimum Operation Loss and Increased Availability

This example demonstrates how proper control system design can minimize operational disruptions while maximizing equipment uptime. Operation loss refers to any reduction in production capacity or efficiency due to system failures, unplanned shutdowns, or suboptimal performance. Availability represents the percentage of time a system operates as intended compared to total scheduled operating time.

Key Control Engineering Considerations:

Implementing redundant control loops and fail-safe mechanisms helps maintain continuous operation even when individual components fail. By designing robust feedback control systems with appropriate gain margins and phase margins (safety factors that ensure stable operation), we can prevent small disturbances from escalating into major shutdowns.

Industrial Example: In a chemical reactor control system, having backup temperature sensors and dual PID controllers ensures that if the primary temperature control fails, the secondary system automatically takes over, preventing costly batch losses and maintaining product quality.

Note: Modern distributed control systems (DCS) and programmable logic controllers (PLCs) often include built-in diagnostic capabilities that can predict component failures before they occur, further reducing unexpected operation losses and improving overall system availability.

Example: Improved Quality

Process control systems directly impact product quality by maintaining consistent operating conditions. When control loops are properly tuned and functioning optimally, they minimize process variations that can lead to off-specification products.

Key Quality Improvements:

Process variability reduction occurs when controllers maintain setpoints within tight tolerances. A well-designed control strategy keeps critical parameters (temperature, pressure, flow rate, composition) stable, which translates to more uniform product characteristics.

Industrial Example: In a chemical reactor, maintaining temperature within ±2°C instead of ±5°C can reduce product quality variations by up to 60%, leading to fewer rejected batches and improved yield.

Feedforward control (anticipatory control that responds to disturbances before they affect the process) combined with feedback control creates a more responsive system that prevents quality excursions before they occur.

Note: Statistical Process Control (SPC) data often shows significant improvement in process capability indices (Cp and Cpk values) after implementing advanced control strategies, demonstrating quantifiable quality gains.

Reduced operator intervention is another benefit, as automated control systems respond more consistently than manual adjustments, eliminating human error and ensuring repeatable results across different shifts and operators.

Example: Maximum throughput and yield

This example demonstrates how to optimize both throughput (the rate at which material flows through the system) and yield (the percentage of input material that becomes usable output product) simultaneously. In process control applications, these two objectives often conflict - pushing for higher throughput can reduce product quality and lower yield, while maximizing yield typically requires slower, more controlled processing.

Control Challenge: The control system must balance the trade-off between processing speed and product quality. This requires careful tuning of setpoints for flow rates, temperatures, pressures, and residence times (the amount of time material spends in each process stage).

Typical Approach: Use a multivariable controller (such as Model Predictive Control) that can handle multiple inputs and outputs while respecting process constraints. The controller optimizes an objective function that weighs both throughput and yield according to economic priorities.

Industrial Example: In a chemical reactor, increasing the feed rate boosts throughput but may not allow sufficient reaction time, reducing conversion efficiency and yield. The control system must find the optimal operating point that maximizes overall profitability rather than just one parameter.

Example: Minimum Order Execution and Fast Response to Changes and Transitions

This example demonstrates how to achieve rapid system response while using the lowest possible controller order (the number of poles and zeros in the transfer function). Lower-order controllers are generally preferred because they’re easier to tune, more robust to plant variations, and simpler to implement in industrial hardware.

The key challenge here is balancing two competing requirements: maintaining fast settling time during setpoint changes or load disturbances, while keeping the controller structure as simple as possible. Higher-order controllers can provide faster response but introduce complexity and potential stability issues.

Design Approach: Start with a basic PID controller (third-order) and only add complexity if the performance specifications cannot be met. Monitor the closed-loop step response and disturbance rejection to verify that both transient behavior and steady-state accuracy requirements are satisfied.

Industrial Example: In a temperature control application, a simple PI controller might provide adequate disturbance rejection for slow thermal processes, while a servo positioning system may require additional derivative action or feedforward compensation to achieve the required bandwidth and settling time.

Note: Fast response typically means minimizing rise time and settling time, while minimum order execution refers to using the simplest controller structure that still meets all performance specifications.

• Reducing operating expenses

Example Minimum energy consumption (e.g., fuel, steam, cooling water, electricity, compressed air, etc.)

Note: This represents a common economic objective in process control where the controller seeks to minimize the total energy costs while maintaining desired product quality and throughput. Energy consumption can be directly measured through flow meters, power meters, or calculated from actuator positions and equipment operating points.

Industrial Example: In a distillation column, minimizing energy consumption might involve optimizing the reboiler steam flow and condenser cooling water flow while still achieving the required separation efficiency between product streams.

Example: Minimum utility consumption (chemical, N2, water, etc.)

This optimization objective focuses on reducing the consumption of plant utilities required for process operation. Utilities typically include process chemicals (solvents, catalysts, additives), nitrogen for inerting and purging operations, cooling/heating water, steam, and compressed air. The control system aims to minimize these inputs while maintaining product quality and process constraints.

Industrial Example: In a chemical reactor, minimizing nitrogen purge flow while ensuring adequate oxygen removal, or reducing cooling water flow rate while maintaining required temperature setpoints.

Note: This objective often conflicts with production rate targets, requiring multi-objective optimization techniques to find the optimal balance between utility costs and throughput.

Example: Minimum catalyst consumption and longer catalyst life

In process control applications involving catalytic reactions, maintaining optimal catalyst utilization is critical for both economic efficiency and operational longevity. From a control perspective, this requires implementing feedback control strategies that monitor catalyst activity indicators (such as conversion rates, selectivity, or temperature profiles) and adjust process variables accordingly.

Key Control Considerations: - Feed rate control: Regulating reactant flow rates to prevent catalyst overloading, which can cause deactivation through coking or sintering - Temperature management: Maintaining optimal reaction temperatures using cascade control loops (inner temperature control with outer conversion rate control) to prevent thermal degradation of the catalyst - Pressure optimization: Controlling system pressure to maximize catalyst effectiveness while minimizing mechanical stress

Note: Catalyst deactivation is often a slow process that traditional feedback control may not detect quickly enough. Consider implementing model predictive control (MPC) or adaptive control strategies that can anticipate catalyst degradation based on process history and adjust setpoints proactively.

Industrial Example: In a continuous stirred tank reactor (CSTR) for hydrogenation, monitoring the hydrogen consumption rate alongside temperature and pressure allows the control system to detect early signs of catalyst deactivation and automatically adjust residence time or temperature to maintain product quality while extending catalyst life.

Example: Improved management of process loopbacks based on product analysis

Process loopbacks (recycle streams that return material from downstream back to upstream process units) can significantly impact overall system performance and stability. By implementing real-time product analysis feedback, control engineers can optimize these recycle streams more effectively.

Key Implementation Approach: Monitor critical product quality parameters using online analyzers and use this data to adjust loopback flow rates and compositions. This creates a more responsive control strategy compared to traditional time-based or fixed-ratio recycle management.

Control Strategy Benefits: - Reduced material waste by recycling only when product specifications require it - Improved process stability through dynamic adjustment of recycle rates - Enhanced product consistency by maintaining tighter control over key quality variables - Better energy efficiency since unnecessary recycle pumping and heating/cooling is minimized

Practical Consideration: When designing this type of control system, ensure adequate analyzer response time and reliability, as delays or failures in product analysis can lead to suboptimal recycle decisions. Consider implementing analyzer redundancy or fallback control modes for critical applications.

Example: Minimize material waste during process transitions

Process transitions (switching between different product grades, setpoints, or operating modes) often generate significant material waste due to off-specification product during the changeover period. As a control engineer, you can implement several strategies to reduce this waste:

Control Strategy: Use advanced control techniques like feedforward control to anticipate disturbances during transitions, or implement model predictive control (MPC) to optimize the transition trajectory. MPC calculates the optimal sequence of control moves to reach the new setpoint while minimizing deviations from quality specifications.

Practical Implementation: Configure your DCS (Distributed Control System) or PLC to execute pre-programmed transition sequences that gradually ramp key process variables rather than making step changes. This controlled approach keeps the process closer to specification limits throughout the changeover.

Industrial Example: In a polymer production facility, transitioning from one grade to another typically wastes 2-3 tons of material. By implementing a coordinated control strategy that simultaneously adjusts temperature, pressure, and feed rates in a calculated sequence, waste can be reduced to less than 1 ton per transition.

Note: Document transition procedures and continuously monitor key performance indicators like transition time and waste generation to identify improvement opportunities. Small optimizations in transition control can result in substantial cost savings over time.

9.1.5.1 Improving workforce productivity

Example: Minimum Staffing Requirements for Control Projects During FEED and Detailed Design Phases

This example addresses the minimum personnel allocation needed for control system implementation during two critical project phases: FEED (Front End Engineering Design - the preliminary engineering phase where basic design concepts and specifications are established) and detailed design (where comprehensive technical drawings, specifications, and documentation are finalized).

Note: Proper staffing during these phases is crucial since control system design decisions made early in FEED will significantly impact the entire project’s automation strategy, while detailed design phase requires sufficient manpower to develop all control narratives, P&IDs (Piping and Instrumentation Diagrams), and system architecture documentation.

Key Consideration: Understaffing during these phases often leads to design gaps, increased engineering hours during later project phases, and potential control system performance issues during commissioning and startup.

Example: Maximum workforce productivity that achieves increased throughput with the same staffing levels or maintains the same throughput with reduced staffing requirements.

Definition: Workforce productivity in control systems context refers to the operational efficiency gained through automation, where control systems enable fewer operators to manage the same or greater production output.

Industrial Example: A manufacturing line that previously required 4 operators can maintain the same production rate with 2 operators after implementing automated process control, or the same 4 operators can now handle 50% higher throughput due to improved system efficiency.

Example: Increased automation reduces the amount of operator attention required for specific production processes, allowing operators to focus more on exception detection and response rather than continuous direct monitoring.

Definition: Exception detection refers to identifying when process variables deviate from their normal operating ranges or when equipment behaves unexpectedly.

Industrial Example: In a typical chemical reactor, instead of an operator constantly watching temperature and pressure readings, automated control loops maintain setpoints while the operator monitors alarm systems and investigates any process upsets or equipment malfunctions that require human intervention.

Example: Reduced time and training needed to bring new operators up to speed due to knowledge retention

When control systems incorporate knowledge retention capabilities (storing operational decisions, alarm responses, and process adjustments), new operators can learn more efficiently from documented best practices. This reduces both initial training duration and the learning curve for understanding complex process interactions.

Practical Benefit: Instead of relying solely on verbal knowledge transfer from experienced operators, new staff can access a database of previous successful control actions and their outcomes. This systematic approach to knowledge preservation helps maintain consistent operational performance even during workforce transitions or shift changes.

Note: Knowledge retention systems typically integrate with HMI (Human-Machine Interface) platforms and historian databases to capture both operator actions and corresponding process responses.

Example: Improved shift-to-shift consistency due to knowledge transfer and retention

When control systems effectively capture and transfer operational knowledge between shifts, plants achieve more consistent performance across all operating periods. This knowledge transfer includes documented best practices, alarm response procedures, and process optimization insights that experienced operators have developed.

Industrial Example: A continuous process unit maintains the same product quality and throughput whether running on day, evening, or night shift because critical process knowledge (like optimal setpoint ranges, common disturbance patterns, and proven control strategies) is systematically shared between operators rather than lost during shift changes.

Key Benefits: - Reduced process variability between shifts - Faster response to common process disturbances - Better utilization of lessons learned from experienced operators - Minimized “learning curve” for newer operators

Note: This consistency is typically measured through statistical process control (SPC) charts that track key performance indicators across different shifts, showing reduced variance in metrics like product quality, energy consumption, or throughput rates.

Example: Improved management of process issues and bottlenecks, allowing for planned action at specific process points.

Advanced control systems enable better identification and handling of process constraints and flow restrictions that limit overall system performance. By implementing real-time monitoring and predictive analytics, control engineers can detect developing bottlenecks before they impact production and schedule corrective actions at predetermined intervention points in the process.

Industrial Example: In a chemical reactor train, temperature excursions or catalyst deactivation can create throughput bottlenecks. Modern control systems can predict these conditions and automatically trigger planned responses like feed rate adjustments or switching to backup equipment at specific process stages.

Note: This proactive approach replaces reactive troubleshooting with systematic bottleneck management, improving overall equipment effectiveness (OEE) and reducing unplanned downtime.

Example: Improved process management of clean-in-place (CIP) systems to reduce time and materials costs.

Definition: CIP systems automatically clean process equipment without disassembly by circulating cleaning solutions through pipelines, tanks, and other components.

By implementing better control strategies for CIP operations, we can optimize cleaning cycle timing, reduce chemical consumption, and minimize water usage. This typically involves coordinating temperature control, flow rate management, and chemical concentration monitoring to ensure effective cleaning while eliminating unnecessary extended cycles.

Industrial Example: In a food processing plant, optimized CIP control can reduce cleaning time from 45 minutes to 30 minutes per cycle while maintaining sanitation standards, resulting in increased production uptime and lower operating costs.

• Improved process stability to minimize costs

Decrease the challenges associated with safety interlocks by implementing improved process control strategies.

Definition: Safety interlocks are protective systems that automatically shut down or prevent equipment operation when unsafe conditions are detected.

Common Challenge: Poor process control often leads to frequent, unnecessary interlock trips due to process variables exceeding safe operating limits, resulting in production downtime and operator frustration.

Control Engineering Approach: By tightening control loops (reducing steady-state error and minimizing overshoot), implementing cascade control where appropriate, and tuning controllers for optimal disturbance rejection, we can maintain process variables well within their safe operating ranges. This reduces nuisance trips while maintaining the critical safety function of the interlock system.

Industrial Example: In a reactor temperature control system, improving PID tuning and adding feedforward control for cooling water temperature variations can prevent temperature spikes that would otherwise trigger high-temperature interlocks.

Example: Decrease the challenges to safety systems with improved process control.

When process variables deviate from their setpoints or operating ranges, safety instrumented systems (SIS) are forced to intervene more frequently to maintain safe operating conditions. By implementing tighter process control strategies, we can reduce these deviations and minimize unnecessary safety system activations.

Industrial Example: In a chemical reactor, poor temperature control might cause frequent high-temperature alarms that trigger safety shutdowns. Improving the temperature control loop (through better PID tuning, cascade control, or feedforward compensation) keeps the process closer to setpoint, reducing safety system demands.

Improved process control reduces challenges to safety systems by: - Minimizing process upsets that could trigger safety interlocks - Reducing wear on safety devices (relief valves, emergency shutdown valves) from frequent cycling - Decreasing the likelihood of spurious trips that cause production losses - Maintaining process variables well within safe operating limits rather than allowing them to approach trip points

Note: This approach follows the hierarchy of risk reduction where inherently safer design and process control (prevention) are preferred over relying solely on safety instrumented functions (protection).

The outcome of this activity is the approval of the procedure automation scope or a decision to loop back to an earlier step in the work process.

Definition: Procedure automation scope refers to the specific boundaries and extent of what will be automated within a given process or system - essentially defining which manual operations will be converted to automatic control.

Note: The loop-back mechanism is a common quality gate in automation projects that ensures each phase is properly validated before proceeding to implementation. If the scope doesn’t meet requirements or feasibility criteria, the project returns to refinement stages rather than moving forward with an inadequate design.

9.2 Creating the Lifecycle Instance

When an Automated Procedure Lifecycle instance is created from a snapshot of the Procedure Automation Strategy (the master template that defines how automated procedures should execute), it may be modified based upon specific constraints and requirements of that particular instance.

Note: Each instance represents a unique execution of the procedure with its own operating conditions, equipment states, and process requirements that may differ from the original strategy template.

Each lifecycle instance (a specific implementation or deployment of the automation system) may have unique requirements that differ from the standard approach. The Procedure Automation Strategy may be modified, or an addendum created, to document which parts of the strategy are used, not used, modified, or created for that particular instance.

Definition: A lifecycle instance refers to a specific project or implementation phase where the automation strategy is applied to real equipment or processes.

Lifecycle instance requirements may include:

• Lifecycle workflow guidelines {Do we need an Example here to explain such guidelines?}
• Automated procedure performance criteria

Performance Criteria for Maximizing Operator Adoption of Automated Procedures

When designing automated control sequences, the success of implementation heavily depends on operator acceptance and consistent usage. Key performance criteria should focus on creating procedures that operators will actually use in real-world conditions.

Critical Design Considerations:

The automated procedures must demonstrate clear operational advantages over manual methods, such as reduced cycle times, improved consistency, or enhanced safety margins. Operators need to see tangible benefits that make their work easier or more effective.

User interface design plays a crucial role in adoption rates. The HMI (Human Machine Interface) should provide intuitive navigation, clear status indicators, and logical alarm prioritization. Complex procedures should be broken down into understandable steps with visual confirmation of each stage.

Reliability Requirements:

Automated sequences must perform consistently under normal operating conditions with minimal false alarms or unexpected stops. When failures do occur, the system should provide clear diagnostic information and allow for smooth transition to manual control.

Note: Operators will abandon automated procedures if they experience frequent nuisance trips or unclear fault messages that slow down production.

Training and Documentation:

Effective operator training should cover both normal operation and common troubleshooting scenarios. Documentation must be readily accessible and written in practical terms that relate to actual plant operations rather than theoretical control concepts.

Regular feedback collection from operators helps identify pain points and areas for improvement in the automated procedures.

Performance Criteria for Optimal Controller Hardware Sizing

When designing automation systems, determining the right number and type of controllers is critical for both performance and cost-effectiveness. The performance criteria should focus on ensuring adequate processing power, I/O capacity, and communication bandwidth to handle all automated procedures without bottlenecks.

Key factors to evaluate include CPU utilization (typically keeping peak loads under 80% to allow for process variations), scan time requirements (the time needed to complete one full execution cycle of the control logic), and I/O point count with appropriate safety margins. Memory requirements for program storage, data logging, and historical trending must also be considered.

Note: Controller sizing often involves balancing redundancy needs against cost - having backup controllers for critical processes versus accepting some risk for non-essential functions.

Network loading is another crucial criterion, as distributed control systems rely heavily on communication between controllers, HMIs (Human Machine Interfaces), and field devices. Excessive network traffic can cause delays that impact control performance.

Industrial Example: In a batch manufacturing process, you might need separate controllers for recipe management, safety interlocks, and equipment control, each sized according to their specific processing demands and response time requirements.

• Generation of documentation for automated procedures to fit a specific project’s requirements

Example: Operating Guideline Documents

Operating guideline documents serve as standardized procedures that define how control systems should be operated under various plant conditions. These documents typically specify setpoint ranges, alarm limits, and response procedures for both normal and abnormal operating scenarios.

Definition: Setpoints are the desired target values that controllers attempt to maintain (such as temperature = 150°C or pressure = 25 psig).

For control engineers, these guidelines provide critical information about: - Permissible control parameter ranges during startup, normal operation, and shutdown sequences - Required responses to process alarms and safety interlocks - Manual override procedures when automatic control fails - Coordination requirements between different control loops (especially important in cascaded or feedforward control strategies)

Industrial Example: In a distillation column, operating guidelines would specify the acceptable range for reflux ratio setpoints, the sequence for transitioning from manual to automatic control during startup, and the required actions if the overhead temperature exceeds alarm limits.

Note: These documents should be regularly updated as process modifications occur and serve as training materials for operators who interact with your control systems daily.

When working on engineering design documents, control engineers must ensure that all control system specifications, loop diagrams, and instrumentation details are clearly documented. These documents serve as the foundation for implementing and maintaining control strategies throughout a project’s lifecycle.

Key Components: Design documents typically include P&ID drawings (Piping and Instrumentation Diagrams showing process flow and control points), control narratives that explain the operational logic, alarm and interlock matrices, and instrument datasheets with calibration ranges and accuracy requirements.

Industrial Example: For a temperature control loop on a reactor vessel, the design document would specify the transmitter range (0-500°C), controller tuning parameters (PID gains), valve sizing calculations, and safety interlocks that shut down heating if temperature exceeds setpoint by more than 50°C.

Note: Always verify that control system architecture matches the documented design before commissioning. Discrepancies between design documents and actual implementation are common sources of startup issues and can lead to unsafe operating conditions or poor control performance.

These documents also serve as the primary reference for troubleshooting, modifications, and regulatory compliance audits, making their accuracy critical for long-term plant operation.

• Necessary Tool kits as required for the design, development, and maintenance of the instance throughout its life cycle

When working with control systems, code libraries and design standards serve as fundamental building blocks for developing reliable and maintainable automation solutions. Code libraries contain pre-written functions and modules that handle common control tasks, such as PID controller implementations, signal filtering routines, and communication protocols. These libraries help avoid reinventing the wheel and reduce development time while ensuring proven functionality.

Definition: Code libraries are collections of reusable software components that provide standard functions for control system operations, from basic mathematical operations to complex control algorithms.

Design standards establish consistent practices for programming structure, variable naming conventions, documentation requirements, and system architecture. Following these standards becomes crucial when multiple engineers work on the same project or when systems require long-term maintenance and troubleshooting.

Industrial Example: A manufacturing plant might use a standardized PID library across all temperature control loops, ensuring consistent tuning methods and documentation formats that any control engineer can understand and modify.

Note: While it might seem restrictive at first, adhering to established code libraries and design standards actually speeds up development and reduces errors, especially when integrating with existing plant systems or working with legacy equipment.

When developing HMI (Human-Machine Interface) systems, establishing comprehensive libraries and design standards is crucial for maintaining consistency and efficiency across control system projects. These libraries contain pre-built graphical elements, symbols, and interface components that can be reused throughout different applications.

Definition: HMI libraries are collections of standardized visual elements like pump symbols, valve indicators, alarm displays, and navigation buttons that follow established design conventions.

Design standards should address several key areas: color coding schemes (such as red for alarms, green for normal operation), typography guidelines for readability at various distances, and consistent symbol representations for common industrial equipment. These standards ensure that operators can quickly interpret information regardless of which system they’re working with.

Industrial Example: A water treatment facility might use the same motor symbol design across all their HMI screens, whether displaying lift pumps, blowers, or mixers. This consistency reduces operator confusion and training time.

The development of these libraries typically involves collaboration between control engineers, operators, and plant management to ensure the visual elements accurately represent equipment behavior and provide intuitive operation. Version control of these libraries is essential, as modifications should be systematically implemented across all related projects to maintain standardization.

Note: Many SCADA platforms like Wonderware, FactoryTalk View, or Ignition provide built-in library management tools that help organize and distribute these standardized components across multiple projects.

When you develop or update automation procedures in your control system, make sure to document any improved practices or lessons learned that emerge during the process. This feedback should be systematically captured and communicated back to the Procedure Automation Strategy work process (the higher-level team or department responsible for defining automation standards and methodologies across your organization).

Note: This creates a continuous improvement loop where field experience from individual projects helps refine the overall automation strategy and standards for future implementations.

9.3 Work Plan

9.3.1 Introduction

The work plan activity creates a detailed work plan that documents all requirements needed to execute the remaining work processes throughout the procedure automation lifecycle (the complete sequence of phases from initial design through implementation, testing, and maintenance). This work plan must be integrated with the broader project or operational work plan, which encompasses critical elements like manpower loading plans (resource allocation showing how many personnel are needed and when) and project schedules.

Note: This integration ensures that automation development activities align with overall project timelines and resource constraints, preventing scheduling conflicts and ensuring adequate staffing for each phase of the automation project.

Work plan content that is unique to automating procedures may include:

Definition: Automation procedures refer to the systematic conversion of manual control processes into automated sequences that can be executed by control systems (PLCs, DCS, or SCADA systems) with minimal human intervention.

When developing work plans for automation projects, control engineers must consider several specialized elements beyond standard project planning. These unique components typically encompass the technical specifications for control logic development, human-machine interface (HMI) design requirements, and safety interlock configurations that ensure safe automated operation.

Note: Unlike manual procedures, automated sequences require precise definition of all possible system states, failure modes, and recovery procedures since the control system cannot make intuitive decisions like a human operator.

The work plan should also address integration challenges with existing control infrastructure, including communication protocol compatibility (such as Modbus, Ethernet/IP, or Profibus) and the coordination of new automated functions with legacy manual operations during transition periods.

Industrial Example: In a pump automation project, the work plan would need to specify not just the pump start/stop logic, but also pressure monitoring thresholds, backup pump sequencing, and the specific operator override capabilities required for maintenance scenarios.

• Functional specifications format and contents
• Design format and contents
• Approach to testing and validation
• Implementation guidelines and standards
• Training requirements and plans
• Installation and commissioning plans
• Support of operations and maintenance of automated procedures
• Project team identification

The format and contents of procedure specifications and implementation module designs should be established during the work plan development phase.

Definition: Procedure specifications are detailed documents that outline the step-by-step methods for executing control strategies, while implementation module designs define how individual control functions (like PID loops, interlocks, or safety systems) will be structured and coded.

Note: Setting these standards early in the project prevents inconsistencies later and ensures all team members follow the same documentation and coding conventions, which is critical for system maintenance and troubleshooting.

9.3.2 Risks Associated with Automated Procedures

Risk factors that apply to the development and use of automated procedures may include:

Note: When implementing automated control systems, it’s important to identify potential failure modes early in the design phase. These risk factors can lead to system malfunctions, safety incidents, or production losses if not properly addressed during commissioning and operation.

Definition: Automated procedures refer to pre-programmed sequences of control actions that execute without direct operator intervention, commonly implemented through PLCs (Programmable Logic Controllers), DCS (Distributed Control Systems), or SCADA systems.

Industrial Example: In a chemical processing plant, an automated startup sequence might control valve positions, pump operations, and temperature setpoints. Each step in this sequence presents potential risk points that must be evaluated against safety interlocks and process constraints.

• Higher CPU, memory utilization, or network latency than expected may result in adverse performance or constrain future changes.

You may need to install additional hardware components to prevent system performance degradation, which could delay your project timeline and increase costs beyond the original budget.

Note: Performance degradation typically refers to slower response times, reduced accuracy, or decreased stability in your control loops - common issues that arise when system demands exceed the original design specifications.

Industrial Example: If your PLC (Programmable Logic Controller) is running at 90% capacity and you’re adding new control loops, you might need additional I/O modules or a more powerful processor to maintain acceptable scan times.

Legacy system incompatibility refers to the technical challenges that arise when older control systems cannot effectively communicate or integrate with modern automation equipment and software platforms. This incompatibility typically stems from outdated communication protocols (such as older serial interfaces versus modern Ethernet-based networks), different data formats, or hardware that lacks the necessary interfaces for current technology standards.

Common Issues: Older PLCs may use proprietary communication protocols that newer HMIs or SCADA systems cannot interpret directly, requiring protocol converters or gateway devices. Additionally, legacy systems often operate on different voltage levels, signal types (4-20mA analog versus digital fieldbus), or use discontinued software that cannot run on current operating systems.

Industrial Example: A 20-year-old DCS (Distributed Control System) using Foundation Fieldbus may struggle to integrate with a new MES (Manufacturing Execution System) that expects OPC-UA communication, necessitating middleware solutions or system upgrades to bridge the technological gap.

This incompatibility can result in increased maintenance costs, reduced system reliability, and limitations in implementing modern features like advanced analytics or remote monitoring capabilities.

The existing current measurement technologies in the system are incompatible with each other or with the required specifications. This typically occurs when different current sensing methods (such as current transformers, Hall effect sensors, or shunt resistors) operate at different voltage levels, have mismatched signal outputs, or use incompatible communication protocols.

Common Issues: Current sensors with 4-20mA analog outputs cannot directly interface with digital systems expecting Modbus communication, or sensors rated for different current ranges may provide inaccurate readings when used together in the same control loop.

Impact: This incompatibility can lead to measurement errors, signal conditioning problems, or complete inability to integrate current feedback into the control system, potentially compromising both performance and safety.

• Lack of prior experience with automated procedures may lead to
  • Underestimating the resources which are required to meet the process control and business objectives.
  • Lack of prior experience with automated procedures may lead to inadequate specification and implementation of automated procedures resulting in project schedule/cost overruns and faulty operation.
• The complexity of control system design and implementation requirements may be underestimated.
  • Complex process unit interactions may be underestimated.
  • Automated procedures may require higher-performance devices.
• The lack of a toolkit may increase the probability of project cost and schedule overruns.
• The automation of existing procedures without first verifying their accuracy.
• The automation of existing procedures may require extra work to programmatically execute logic that was previously handled by operator judgment. Automated procedures may not be able to detect and respond to unanticipated failure modes as well as a human operator. For example, an undiagnosed sensor fault may provide a false reading resulting in undesirable logic being executed by an automated procedure.
• Automated procedures are not designed with sufficient input from operators.
• The impact of automated procedures on the alarm management system, regulatory control, and safety system.
• Low utilization of automated procedures by operators.
• Over time operators lose the ability or knowledge to manually execute a procedure in cases where the automated procedure is not available.
• Operators are not provided sufficient information and involvement in the procedure to maintain situational awareness during procedure execution.

Control system risks should be first addressed during the early Planning and Definition phases and when developing Procedure Specifications. Note: This early identification helps prevent costly modifications later in the project lifecycle. During ongoing Monitor and Assessment activities (continuous evaluation of system performance and safety), both the originally identified risks and any new risks discovered by operations personnel need regular review to determine if additional mitigation measures are necessary.

Definition: Risk mitigation refers to implementing safeguards, redundancies, or procedural changes to reduce the likelihood or impact of potential system failures or safety hazards.

9.3.3 Testing

Automated control procedures must undergo thorough testing before transferring responsibility to operations teams to reduce the likelihood of process disturbances or safety incidents during normal plant operation. Inadequately tested procedures create uncontrolled risk exposure that can lead to costly downtime, equipment damage, or worse.

Definition: Process disturbances (or “plant upsets”) refer to any deviation from normal operating conditions that can affect product quality, equipment performance, or safety systems.

This operational risk can be effectively minimized through a systematic and comprehensive testing approach that validates both normal operation sequences and exception handling scenarios.

Note: Testing should include both steady-state conditions and dynamic responses during process transitions, as many control issues only surface during startup, shutdown, or mode changes.

A structured testing methodology helps identify potential failure modes before they impact production, ensuring that automated procedures perform reliably across all expected operating conditions and edge cases.

The testing approach is established during the strategy development phase and serves as the foundation for defining requirements when creating the test plan (covered in Section 10.4, “Test Plan”). This approach outlines the overall methodology and scope for how system validation will be conducted.

Note: The testing approach typically includes decisions about test types (functional, performance, safety), test environments (simulation, hardware-in-the-loop, field testing), and acceptance criteria before detailed test procedures are written.

Testing automated procedures (step-by-step control sequences that run without operator intervention) requires much more comprehensive verification than typical regulatory control loops. While regulatory control testing might only involve checking setpoint responses, automated procedures need rigorous testing that often requires either a process simulation or actual plant equipment to properly validate all operational scenarios.

Definition: Regulatory control refers to basic feedback control loops that maintain process variables like temperature, pressure, or flow at desired setpoints.

Using a simulation environment provides significant advantages for testing automated procedures. It allows you to systematically exercise all possible logic paths within the procedure, particularly the exception handling routines (abnormal conditions, equipment failures, or safety interlocks), in a much shorter timeframe and with considerably less risk compared to testing on live plant equipment. A dynamic process simulation can rapidly recreate different operating conditions and scenarios that might take hours or days to encounter during actual plant operations.

Industrial Example: Testing a reactor startup procedure might involve verifying normal operation, but also testing responses to scenarios like valve failures, temperature excursions, or emergency shutdowns - all of which can be safely simulated without risking actual equipment or production.

The ability to quickly set up and run various operating conditions makes simulation an invaluable tool for thorough procedure validation before deployment to the actual process.

When dynamic process simulations are used (mathematical models that predict how a process behaves over time), a parallel development path may be used to prepare the test environment, so it is ready for testing on time.

Note: This parallel approach means you can set up your testing hardware, software, and procedures while the simulation models are still being developed, rather than waiting for the simulation to be complete before starting test preparation. This helps avoid project delays and ensures your control system testing can begin as soon as the dynamic models are validated.

9.3.4 Requirement

Note

The procedure owner shall ensure that all automated procedures are tested and validated.

Note: Testing typically involves running the automated sequence in a controlled environment or simulation mode, while validation requires demonstrating that the procedure achieves the desired process outcomes under actual operating conditions.

Industrial Example: For an automated batch mixing procedure, testing would verify that valves open/close in the correct sequence and timers function properly, while validation would confirm that the final product meets quality specifications and safety interlocks operate as designed.

9.3.5 Documentation

During the execution of the procedure lifecycle (the complete sequence from procedure initiation through completion), the required documents are automatically generated by the control system.

Note: These documents typically include execution logs, alarm histories, batch records, and regulatory compliance reports that are essential for process validation and audit trails.

Documentation requirements should clearly define who will be using each document (operators, maintenance technicians, other engineers), what specific information it contains (control logic, I/O lists, safety interlocks), and how that information is organized within the document.

Note: Well-defined documentation requirements help ensure that critical system information like PLC program logic, HMI screen layouts, and alarm configurations are captured consistently across all project deliverables.

Automating the documentation preparation process (using tools that can extract information directly from your control system programming software) can save significant engineering hours and reduce overall project costs.

Industrial Example: Many modern programming platforms like RSLogix, TIA Portal, or DeltaV can automatically generate I/O reports, tag databases, and loop drawings directly from the configured control logic, eliminating manual transcription errors and reducing documentation time by 50-70%.

9.3.6 Requirement

Note

The procedure owner shall ensure that the documentation requirements are specified before the execution of the procedure lifecycle instance.

Note: Documentation requirements typically include technical specifications, validation records, change logs, and compliance documentation that will be needed throughout the procedure’s execution.

Definition: The procedure owner is the designated person responsible for overseeing the entire procedure from planning through completion, including ensuring proper documentation and regulatory compliance.

9.3.7 Requirement

Note

The procedure owner shall ensure that all documentation is kept up to date throughout the procedure lifecycle instance.

Note: Documentation includes process flow diagrams, control logic descriptions, safety interlocks, operating parameters, and any associated maintenance procedures. Keeping these updated is critical for safe operation and effective troubleshooting when process conditions change or equipment is modified.

9.3.8 Training

Training requirements must address three key components: who needs training, what content to cover, and how to deliver that training effectively. Personnel requiring training on automated procedures typically include operators (who directly interact with the control system during normal operations) and supervisors (who oversee operations and may need to intervene during abnormal conditions).

Note: Table 10 provides specific definitions for different categories of Operating Staff within your facility’s organizational structure.

The training content should cover both the normal automated sequence and potential failure modes, while the delivery method might include hands-on simulator training, classroom instruction, or computer-based modules depending on the complexity of the automated procedure.

Operating Staff has the responsibility to verify that all relevant operating and maintenance personnel receive appropriate training on the automated procedure before implementation. This includes not only the control room operators who monitor the system, but also field maintenance technicians who may need to troubleshoot or manually override the automated sequences during equipment failures.

9.4 Toolkits

When setting up an Automated Procedure Lifecycle (the complete management system for automated control sequences from creation to retirement), it should begin by using the toolkits provided by the Procedure Automation Strategy as its foundation for implementation. These toolkits contain both platform-independent materials (code and configurations that work across different control systems) and platform-dependent materials (hardware-specific implementations for particular PLCs, DCS systems, or SCADA platforms).

Note: Think of toolkits as standardized building blocks that ensure consistency across your automation projects while allowing flexibility for different hardware environments.

When implementing specific automated control sequences, you may find that your current software tools and hardware configurations don’t fully support the required functionality. In these cases, you’ll need to either enhance existing tools (such as upgrading PLC programming software or adding new function blocks) or develop entirely new tools to meet the automation requirements.

Definition: Tool augmentation refers to adding capabilities to existing systems, while new tool generation means creating custom solutions from scratch.

Industrial Example: You might need to create custom HMI screens for a new process, or develop specialized control algorithms that aren’t available in your standard control library.

These enhanced or newly developed tools should be documented and evaluated for addition to the company’s standard engineering resources. This ensures other projects can benefit from the work and maintains consistency across control system implementations.

When implementing a lifecycle instance, the specific system and version referenced in your procedure automation strategy may not match what’s actually available in your current toolkit. This version mismatch means you’ll need to update those components and examples to align with the newer system version you’re working with.

Note: A lifecycle instance refers to a specific implementation or deployment of an automated process within your control system. The procedure automation strategy is your documented plan for how automation should be implemented across different processes.

Common Scenario: If your automation strategy was developed using PLC programming examples for Rockwell Studio 5000 v32, but your plant is now running v34, you’ll need to verify compatibility and update any deprecated function blocks or changed syntax in your implementation.

Platform independent toolkit materials are designed to work with Control Specifications and design processes that can be applied across different control systems, regardless of the specific hardware or software platform being used (meaning the same approach works whether you’re using Allen-Bradley, Siemens, Schneider, or other control platforms). These platform-independent materials may include:

Note: This approach allows control engineers to develop standardized design methodologies and documentation that can be reused across multiple projects, even when different clients or facilities use different control system brands.

• A sample description of automation goals
• A sample User Requirements Specification (URS)
• A sample Functional Requirements Specification (FRS)
• Templates for writing procedures

Example 1 A standardized list of action verbs with their specific technical definitions for use in control system procedures and operating instructions.

Note: Using consistent verb definitions across all procedures helps eliminate ambiguity in operations. For instance, “START” might mean different things to different operators, but with standardized definitions, everyone follows the same interpretation when executing control sequences.

Definition: Action verbs in control documentation are precise command words that tell operators exactly what physical or system action to perform, reducing the risk of miscommunication during critical operations.

Example 2 demonstrates a standardized framework for control system procedures that includes both organizational elements (like a table of contents for easy navigation) and essential content requirements. This structured approach ensures that all critical information is consistently documented across different control systems and can be easily referenced by operators and maintenance personnel.

Note: Having a common procedure structure is particularly important in industrial settings where multiple engineers may need to troubleshoot, modify, or maintain the same control systems over time. The standardized format reduces the learning curve when working with unfamiliar equipment or processes.

• Checklists for use on projects in each work process.

Platform-dependent material refers to control system components and documentation designed specifically for a particular hardware platform or software architecture (such as a specific PLC brand, DCS system, or real-time operating system). While these materials must still follow the general guidelines and standards outlined in the platform-independent toolkit, they provide engineers with concrete starting points for designing and implementing control solutions on their specific system.

Definition: Platform-independent material contains universal control principles and standards that apply regardless of the hardware or software being used, while platform-dependent material translates these principles into actionable guidance for specific equipment.

The key benefit of platform-dependent materials is that they bridge the gap between theoretical control concepts and practical implementation. Instead of having to figure out how to apply general control strategies to your particular system, these materials give you tested approaches tailored to your platform’s capabilities and constraints.

Note: Even though platform-dependent materials are customized for specific systems, they should always maintain compliance with industry standards and the broader control philosophy established in your organization’s platform-independent documentation.

Typical platform-dependent materials include:

• A sample Detailed Design Specification (DDS)
• Implementation standards for configuration/programming for a platform
• HMI designs and implementations specific to a platform
• Libraries of designs and code to foster reuse

Equipment modules or units often include standardized libraries designed to automate similar equipment types or classes, ensuring consistent operational behavior across the system. These libraries contain pre-programmed control logic, function blocks, and parameter sets that can be reused for equipment with comparable functionality.

Industrial Example: A chemical plant might use the same motor control library for all centrifugal pumps, regardless of their specific application, ensuring uniform start-up sequences, fault handling, and monitoring across all pump operations.

Note: Using standardized libraries reduces commissioning time, minimizes programming errors, and simplifies maintenance since operators and technicians work with familiar, consistent interfaces and behaviors throughout the facility.

Libraries can contain a complete vertical slice of a project that spans multiple development phases. This includes both platform-independent components like URS (User Requirements Specification - defines what the system must do from the user’s perspective) and FRS (Functional Requirements Specification - details how the system will meet those user needs), as well as platform-dependent elements such as DDS (Detailed Design Specification - the technical blueprint for implementation) and the actual implementation code that runs on specific hardware or software platforms.

Note: A vertical slice means the library captures all layers of development for a particular feature or function, from high-level requirements down to executable code, rather than just one phase of the project.

Each organization may have its own format for documents such as URS (User Requirements Specification), FRS (Functional Requirements Specification), and DDS (Detailed Design Specification).

Note: The URS defines what the system needs to do from the user’s perspective, the FRS specifies how the system will function to meet those requirements, and the DDS provides the technical implementation details including hardware specifications, software architecture, and control logic design. While the content requirements are often standardized across the industry, the actual document templates, formatting, and review processes can vary significantly between companies.

Toolkits may contain controlled documents (formally managed documents with version control and approval processes) as well as informal documents and computer files.

Note: Controlled documents typically include approved procedures, specifications, and safety protocols that require formal change management, while informal documents might include personal notes, draft calculations, or reference materials that don’t require official approval processes.