Process Control & Optimization
Overview
Process control and optimization (PCO) is the discipline of adjusting a process to maintain or optimize a specified set of parameters without violating process constraints. The PCO market is being driven by rising demand for energy-efficient production processes, safety and security concerns, and the development of IoT systems that can reliably predict process deviations. Fundamentally, there are three parameters that can be adjusted to affect optimal performance.
- Equipment optimization: The first step is to verify that the existing equipment is being used to its fullest advantage by examining operating data to identify equipment bottlenecks.
- Operating procedures: Operating procedures may vary widely from person-to-person or from shift-to-shift. Automation of the plant can help significantly. But automation will be of no help if the operators take control and run the plant in manual.
- Control optimization: In a typical processing plant, such as a chemical plant or oil refinery, there are hundreds or even thousands of control loops. Each control loop is responsible for controlling one part of the process, such as maintaining a temperature, level, or flow. If the control loop is not properly designed and tuned, the process runs below its optimum. The process will be more expensive to operate, and equipment will wear out prematurely. For each control loop to run optimally, identification of sensor, valve, and tuning problems is important. It has been well documented that over 35% of control loops typically have problems. The process of continuously monitoring and optimizing the entire plant is sometimes called performance supervision.
Applicable Industries
- Transportation
- Equipment & Machinery
- Chemicals
Applicable Functions
- Discrete Manufacturing
- Quality Assurance
Market Size
The advanced process control market is estimated to reach USD 1.4 billion by 2020; growing at a CAGR of 11.79% from 2014 to 2020.
Source: Markets and Markets
Case Studies.
Case Study
The Kellogg Company
Kellogg keeps a close eye on its trade spend, analyzing large volumes of data and running complex simulations to predict which promotional activities will be the most effective. Kellogg needed to decrease the trade spend but its traditional relational database on premises could not keep up with the pace of demand.
Case Study
Reducing Operating Costs And Improving Safety
To ensure safe operation of the nuclear plant, the Institute of Nuclear Power Operations sets the performance objectives and defines the criteria (PO&C) to meet those objectives. The plant personnel manually compare each line item in the CAP report against the PO&C to evaluate the seriousness of the event. A spilled cup of coffee in the wrong place might not be too serious, while a critical pump leaking that has the potential to shut down the plant is another matter entirely. This manual process of classifying the seriousness of each item in a CAP report lies at the heart of the continuous effort to improve the safety and operation of the nuclear power plant, but requires significant time and resources. Our client needed a way to automate the classification process to increase its efficiency and to extract information from years of reported events to better understand their causes and anticipate possible adverse events.