What is Process Control in Manufacturing?

Process control is a set of procedures designed to ensure that processes within a manufacturing plant are carried out correctly and that the desired output will be achieved. It’s been around since the 1980s, but new technologies such as artificial intelligence (AI) and machine learning (ML) in manufacturing have made it more powerful and impactful. 

Today, process control automatically manages production conditions to maintain quality, throughput, and efficiency in the plant. It both relies on AI and ML and makes it possible for plants to implement AI-powered automated processes. Automated systems need process control to ensure that they are operating as expected, while process control uses data from automated sensors and monitoring devices to set and adjust its controls. 

Process control involves feedback loops, which monitor a huge range of applications, activities, and variables, including temperature, vibrations, pressure levels, flow, and more, to spot unwanted variations from the norm and initiate action to adjust and correct each process. Plants also use process control to monitor or manage control connectors and analytical components. A series of linked feedback loops can cover highly complex systems, up to and including an entire plant, as long as the loops are interoperable. SCADA (Supervisory Control and Data Accusation) is one of the most popular and widely-adopted process control systems used in process manufacturing. 

Why does process control matter for process manufacturing plants?

Process control is vital for any company that wants to run automated or semi-automated processes. It almost entirely removes the need for human intervention (apart from monitoring the process controls) to allow plants to operate autonomously despite minor variations in input, conditions, etc. 

Even without widespread automation, process control systems enable plants to:

  • Raise the quality of their products and consistently hit quality requirements
  • Save energy and water by running equipment more efficiently
  • Increase efficiency in the plant, limit rework and scrapped batches, and reduce the risk of human error
  • Improve safety levels by ensuring that all equipment and processes are running correctly
  • Lower manufacturing costs by maintaining a more efficient plant
  • Same time previously spent on manual checks

It’s estimated that process manufacturing businesses could save up to 15% in energy costs through an effective process control system. 


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How can process manufacturing plants implement process control?


Decide where to apply your process control systems 

The first step is to consider which processes within your plant to include under your process control systems. You might begin with simpler processes and then work up to cover more complex ones, or begin with the processes that are most critical for production. 

Identify your data sources 

As mentioned above, process control relies on data from sensors and devices. Decide which metrics to track to spot variations in processes, and how to reliably gather data for those metrics. 

Refine your data collection processes

Your data will be coming in from numerous sources and in many different formats. You need to establish a robust system that brings all your data together in a single repository, and processes it to be accessible to your process control tools. 

Set process control limits

Examine your data to work out the limits within which variations can occur without affecting product quality, safety, or plant efficiency. These will be the control limits that your process control systems will enforce. 

How do process plants benefit from process control in manufacturing?

Implementing process control in manufacturing enables process plants to enjoy improved quality and efficiency while cutting costs and reducing waste. In the long term, it assists manufacturing organizations to step closer to full automation and lights-off manufacturing, saving employee time for more revenue-driving activities and ultimately increasing profits.