Feeling overwhelmed by the complexity of control systems in your manufacturing setups? In an era defined by advancements in automation, understanding and leveraging complex systems such as Advanced Process Control (APC) systems has become a non-negotiable necessity for any manufacturing operation, regardless of the industry.
APC, in a nutshell: Advanced Process Control encompasses a range of model-based software technologies, including Multivariable Predictive Control (MPC) or model predictive control, primarily aimed at directing and enhancing the efficiency of process operations. The key is in the precise representation of process dynamics through the models created.
The importance of APC systems in the manufacturing industry cannot be overstated. They are the backbone that provides supervisory control, bridging the gap between basic controls and overall process enhancement. They are the game-changers that aid in realizing sustainable profitability, quality, and operational safety, especially in a progressively Industry 4.0-aligned landscape.
Venturing ahead, this comprehensive guide will shed light on the basics, types, and the undeniably vital role of Artificial Intelligence and Machine Learning in APC systems. You will also learn about cost-effectiveness, optimization techniques, and the promising future of APC systems, all helping you steer through 'Smart Manufacturing', gaining the Smart Factory advantage.
At Scout Systems, we help manufacturers connect people, machines, and production information through digital work instructions, machine monitoring, production tracking, and reporting. While Scout is not an advanced process control system, our technology complements industrial control solutions by providing operational data, production visibility, and integration capabilities that help connect equipment activity with the people managing production.
Understanding the Basics of Advanced Process Control Systems
In the realm of industrial operations, Advanced Process Control (APC) systems are indispensable tools that augment basic process controls, optimizing performance, and operational efficiency.
The Role of Advanced Process Control Systems in Industrial Processes
APC systems are implemented in industries that involve continuous processes, such as chemical, petrochemical, oil and mineral refining, food processing, pharmaceuticals, and power generation. These systems help manage complex industrial processes by monitoring and adjusting numerous variables to improve the overall process performance.
Unlike basic process controls that manage simple operations, APC systems provide a higher level of computational capability. They use sophisticated algorithms to predict future process behaviors and make necessary adjustments for optimal performance. This predictive capability can result in significant improvements in process efficiency, product quality, and economic performance.
The Interaction of Advanced Process Control Systems with Basic Process Controls
Advanced process control systems are not standalone entities but work in conjunction with basic process controls. The basic controls are designed with the process and facilitate basic operation, control, and automation requirements. APCs are added subsequently, often over the course of many years, to address particular performance or economic improvement opportunities in the process.
The integration of APCs with basic controls resides within the process control system, which may include a distributed control system (DCS), programmable logic controller (PLC), and/or a supervisory control computer. Basic controls reside in the DCS and its subsystems, including PLCs, while advanced controls may reside in either the DCS or the supervisory computer, depending on the application.
The Cost-Effectiveness of Advanced Process Control Systems
Implementing an advanced process control system can require significant upfront investment in engineering, instrumentation, software, and ongoing maintenance. However, potential benefits include reduced process variability, improved product quality, lower energy consumption, and increased production efficiency. The financial return depends on the manufacturing process, the control strategy, and the opportunities available for improvement. Manufacturers should evaluate these factors when considering an investment in APC technology.
Types of Advanced Process Control Systems
Advanced Process Control Systems come in various forms, each designed to address specific challenges in industrial processes. Let's explore five main types that are commonly used in industries today.
Advanced Regulatory Control (ARC)
Advanced Regulatory Control (ARC) refers to a set of sophisticated control strategies such as override or adaptive gain. These strategies go beyond the basic functions of a process control system, offering more complex solutions to process control challenges. ARC is often implemented using function blocks or custom programming capabilities at the DCS level. These advanced control techniques can also operate at the supervisory control computer level, depending on the application requirements.
Multivariable Model Predictive Control (MPC)
Multivariable Model Predictive Control (MPC) uses a model of the process to predict future outcomes and adjust control variables accordingly. This technology, often deployed on a supervisory control computer, identifies significant independent and dependent process variables and the dynamic relationships between them. It then uses matrix-math based control and optimization algorithms to control multiple variables simultaneously. The key requirement of MPC is that the models must be linear across the operating range of the controller.
Nonlinear MPC
Nonlinear MPC is similar to Multivariable MPC, utilizing dynamic models and matrix-math based control. However, it does not require model linearity. This allows Nonlinear MPC to accommodate processes with models that have varying process gains and dynamics, such as dead-times and lag times, offering more flexibility in handling complex process dynamics.
Inferential Measurements
Inferential Measurements, also known as soft sensors, are another type of advanced process control. These systems use mathematical models to estimate difficult-to-measure process variables based on easier-to-measure variables. This approach can significantly improve process efficiency and product quality.
Sequential Control
Sequential Control refers to the process of executing a series of operations in a specific order. This type of control is common in batch processes, where operations need to be carried out step-by-step in a predetermined sequence.
Choosing the right advanced process control technology depends on the process being managed, the available instrumentation, and the level of automation required. Manufacturers should also consider how their control systems will exchange information with production management software and the people responsible for operating their equipment. Connecting these systems can provide additional context for understanding production performance and identifying opportunities for improvement.
The Role of Artificial Intelligence and Machine Learning in Advanced Process Control Systems
The dawn of Artificial Intelligence (AI) and Machine Learning (ML) has ushered in a new era for advanced process control systems. They have become instrumental in optimizing operational parameters and tuning the overall system for maximum efficiency.
How AI and ML Optimize Operational Parameters in Process Control
Traditionally, the operations and logic of process control systems, particularly in oil and gas industries, were governed by physics equations and operator experience. However, this approach has its limitations. AI and ML bring a dynamic perspective to this process, analyzing operational conditions and suggesting optimized parameters.
AI and ML algorithms have the ability to learn from historical data, identify patterns, and predict future outcomes. This allows them to provide suggestions for logic parameters or give tips to operators. This can lead to significant improvements in cost efficiency, production volumes, and safety.
By integrating AI and ML into your process control systems, you're not just making your operations smarter; you're making them more adaptable to change and more responsive to new opportunities.
The Use of Machine-Learning Models and Advanced Analytics in Tuning APCs
Machine learning models and advanced analytics play a crucial role in tuning Advanced Process Control (APC) systems. These models can analyze vast amounts of data and make intelligent decisions to optimize the system's performance.
For instance, machine learning can be used to predict the optimal settings for a system under different operating conditions. This can help prevent system failures, reduce waste, and improve efficiency.
Advanced analytics, on the other hand, can provide valuable insights into the system's performance. By analyzing data from various sources, it can identify patterns, trends, and anomalies that might otherwise go unnoticed. This can help identify potential problems before they become serious, enabling proactive maintenance and reducing downtime.
Successful implementation of AI and machine learning in advanced process control requires reliable data, appropriate models, and coordination between engineering, operations, and technology teams. Manufacturers also benefit from connecting this technology with the production information generated by their equipment and operators.
Not all predictive manufacturing software relies on machine learning. Statistical analysis, production forecasting, and rules-based calculations can also provide valuable insights. For example, manufacturers can use historical build-time data and real-time production events to forecast job completion times and adjust schedules as operating conditions change.
Beyond the control algorithms themselves, manufacturers can benefit from connecting advanced process control with the people, machines, and production information across their operations. This is where complementary shop floor software plays an important role.
How Shop Floor Software Supports Advanced Process Control
Advanced process control systems use sophisticated algorithms and control strategies to optimize industrial processes. While these systems focus on process control and automated optimization, complementary shop floor management software can provide additional production data and operational context.
Scout Systems helps bridge the gap between people, machines, and production workflows through digital work instructions, machine monitoring, production tracking, and reporting.
Machine Monitoring and Data Collection
Through its Tracker product, Scout collects signals from manufacturing equipment using a signal interpreter. These signals are cataloged and associated with production events, including transitions between manufacturing steps or units, machine pauses, and emergency stops (E-Stops).
This information helps connect equipment activity with the production processes and operators involved.
Statistical Analysis and Production Reporting
Scout's Reporting suite uses statistical methods to analyze production data. For example, unit build-time reporting can exclude results that fall outside configured standard deviation thresholds, allowing manufacturers to evaluate typical build-time performance without those outliers influencing the reported averages.
Dynamic Production Forecasting
Scout's Live Production application calculates predicted job completion times using average build times, current production conditions, and other scheduling factors.
As jobs are completed or interrupted, the system dynamically recalculates estimated completion times for subsequent jobs at a station. These calculations also account for scheduled breaks and other timing constraints, allowing forecasts to adjust as production conditions change.
This provides manufacturers with continuously updated production forecasts without requiring machine-learning models.
Integration with Advanced Manufacturing Systems
Scout supports information exchange with other manufacturing and industrial systems through push and pull integrations where appropriate.
This allows Scout to serve as an additional source of production data and operational context for compatible advanced process control systems and other industrial software platforms.
Scout does not replace dedicated APC technology or automatically adjust machine parameters. Instead, it complements advanced control systems by connecting machine signals, production information, and human workflows.
Together, these technologies can provide manufacturers with a more complete understanding of their operations and support better-informed process improvement decisions.
Maximizing the Value of Advanced Process Control Systems
Just as owning a high-performance sports car requires regular tuning and maintenance to keep it running at peak performance, so does an advanced process control system. With the right approach and attention to key indicators, you can not only maintain but maximize the value of your APCs. Here's how:
Regular Tuning and Comprehensive Approach for Efficient Operation of APCs
The first step towards maximizing the value of your APCs is to ensure regular tuning and maintenance of key components. This includes sensors, instrumentation, and underlying Basic Loop Controls (BLCs). A comprehensive approach that encompasses people, processes, and technologies is essential in this regard.
People: Engage operators and vendors in performance management. A comprehensive change management approach can help ensure APCs are utilized effectively and maintained in good health.
Processes: Implement digital work instructions with built-in quality assurance to maintain standardization that is proven to deliver on your customer's expectations.
Technologies: Review and improve APC design and logic. Use advanced analytics to identify the right objective function and input-output relationships.
As an example, a North American basic-materials company managed to increase zinc recovery by around 8% using this comprehensive approach.
Indicators for Identifying Opportunities for Optimization
Identifying opportunities for optimization is also crucial in maximizing the value of your APCs. Key performance indicators (KPIs) and dashboards can provide valuable insights into APC performance and health. For instance, high variability in process parameters, such as temperature or pressure, may indicate poor controls and present an opportunity for optimization.
Collaborating with APC Vendors and Prioritizing Optimization Initiatives
Collaboration with APC vendors and process-control specialists is important when identifying opportunities for optimization. Manufacturers should also involve their production teams to ensure that improvements in equipment performance translate into practical improvements on the shop floor.
At Scout Systems, we begin projects with our Project Success Mode Effect and Analysis (PSMEA) tool to identify customer priorities, understand operational challenges, and establish a framework for successful implementation. This collaborative approach helps connect technology improvements with the people and processes involved in production.
At Scout Systems, we believe in working closely with our customers to understand their unique needs and challenges. Our dedicated team collaborates with you to configure digital work instructions, quality assurance, and machine monitoring capabilities to your unique needs, ensuring a seamless Industry 4.0 adaptation.
The key to maximizing the value of your advanced process control system is not just about having the latest technology, but about effectively using and maintaining it. As the saying goes, "A well-tuned old instrument can outperform a poorly maintained new one."
The Future of Advanced Process Control Systems
As advanced process control technology evolves, manufacturers face opportunities to improve performance while addressing the complexity and maintenance requirements of industrial control systems. Alongside developments in control strategies, the integration of APC with connected manufacturing software is becoming increasingly important for bringing equipment data, production workflows, and operational decisions together.
The Challenges and Limitations of Current APC Systems
Despite the significant benefits of APC systems, they're not without their challenges. The complexity of these systems, for instance, can make them difficult to operate and maintain. Moreover, they tend to cast a wide net, incorporating large matrices of variables and models, which can make the system cumbersome and increase maintenance needs.
The extensive use of feedforward models in traditional APC systems, though powerful in proactively rejecting disturbances, adds an additional layer of complexity and maintenance. This approach may not always be necessary or beneficial in all applications, especially given the reliability of simple feedback control.
Proposed Paradigms for More Affordable and Reliable APC Systems
To overcome these challenges, the industry is moving towards a new paradigm: smaller, more affordable, agile, and reliable APC systems. These systems use durable qualitative models, sans embedded optimizers, with more intuitive and succinct matrix designs.
This shift towards a more streamlined approach to APC systems focuses on automation, leveraging existing, proven, manual multivariable control operating practices. This approach can result in more manageable systems that are easier to implement and maintain.
The Role of Connected Manufacturing Software in the Future of APC Systems
As manufacturing technology becomes more connected, production management and shop floor software can complement advanced process control systems by providing additional information about equipment activity, operator workflows, and production performance.
Scout Systems supports this connection through digital work instructions, quality assurance, machine monitoring, and production data collection. Its Tracker technology interprets equipment signals and associates them with production events, while its Reporting and Live Production applications help manufacturers analyze performance and anticipate job completion times.
Through supported integrations, Scout can exchange information with other manufacturing and industrial systems, providing additional operational context that may be useful to advanced process control applications.
These technologies serve different but complementary purposes. APC systems focus on controlling and optimizing industrial processes, while Scout helps connect equipment information with operators, production workflows, and manufacturing decisions. Together, they can contribute to a more connected and informed manufacturing environment.
As we look towards the future, it's clear that the evolution of advanced process control systems will continue to be instrumental in driving operational efficiency and productivity in the manufacturing industry. In this era of smart manufacturing, embracing these advancements is not just an option, but a necessity.
In the next section, we'll wrap up our comprehensive guide to advanced process control systems, reflecting on the importance of these systems in the current and future landscape of manufacturing.
Conclusion: The Importance of Advanced Process Control Systems in the Era of Smart Manufacturing
As we've explored, advanced process control (APC) systems play an important role in modern manufacturing. By monitoring process conditions and applying sophisticated control strategies, these technologies can help manufacturers improve efficiency, product quality, and operational consistency.
However, successful manufacturing operations involve more than automated process control. Manufacturers also need reliable production data, clear operator instructions, and visibility into equipment performance. Complementary technologies such as Scout Systems help connect people, machines, and production information, supporting better-informed decisions and continuous improvement.
As manufacturing technology evolves, connecting industrial control systems with accurate production data and shop floor operations becomes increasingly valuable. This connection helps manufacturers identify inefficiencies, understand production performance, and make informed improvements. As Charles B. from Gunderson stated, "We now have an accurate accounting of the time it takes to manufacture specific parts. We have identified non value added time issues and made adjustments and improvements to increase production."
Improving production visibility and connecting people with manufacturing technology need not be daunting. At Scout Systems, we are dedicated to making the digital transition easy and efficient. Our unique approach targets a return on investment while helping you navigate systematic changes. Our experts provide continuous guidance, allowing your staff to focus on your factory. And with our Accelerator Program, we make it possible to fast-track your digital transformation, securing your place at the forefront of innovation.
In less than 3 months, you can experience improvements that can be quantified; using the data to validate your investment. As one of our clients, Eli from Technical Cable Applications, noted, "Our experience with Scout Systems has been very much worthwhile. You will get a wealth of good data to make informed and intelligent decisions in whatever your process entails."
Ready to make your manufacturing operations more connected? Scout Systems helps bring people, machines, and production data together through digital work instructions, machine monitoring, reporting, and integration with other manufacturing technologies. Explore our solutions to discover how better production visibility can support your smart manufacturing goals.
For further reading, explore our products and learn more about our digital transition approach.
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