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
Use IoT to Improve Healthcare Business Outcomes
Before developing an IoT solution, ICURO hit a major roadblock with its healthcare platform. Limited data sharing between healthcare providers and insurance companies impeded effective communication, resulting in frequent duplication of efforts and making it difficult for each entity to deliver better care while maintaining reasonable costs. ICURO wanted to resolve these data sharing issues, they started developing tools and systems that connect products in meaningful ways, enabling both entities to collaborate more effectively.
Case Study
Amazon helped an American energy company
Based on a program need to build a collaborative data repository for the Marine Hydrokinetic Program, NREL wanted to build a secure, yet collaborative, platform to collect, curate, store, and share moderately sensitive data, which focuses on water power research. As part of this effort, NREL built an environment with a Moderate Authority to Operate (ATO) accreditation from the Federal Information Security Management Act (FISMA). With a FISMA Moderate ATO, NREL maintains all mandated cyber security requirements, while gaining the ability to manage and share moderately sensitive data with other government agencies and research entities.As it prepared to design the new infrastructure, NREL knew it needed agility and flexibility. “Our goal was to make it easy for analysts and scientists to access and publish data, but we didn’t want to spend our time managing infrastructure to facilitate that. We want to focus on the product—the data itself,” says Webber. For example, NREL uses a dev-ops team approach focused on the needs of the client and ensures that the research metadata is optimized for accessibility. “We need to make sure the right descriptors and keywords are there so we can easily connect our users to all the other research sites,” says Jon Weers, senior web strategist at NREL. “If the data isn’t discoverable, it’s not useful to researchers.”
