What is process optimization?

Process optimization in manufacturing, or manufacturing process optimization, refers to increasing organizational efficiency through process improvement. It has a lot in common with continuous improvement, which aims to continuously improve processes, products, or services.

Process optimization generally involves making improvements over a number of areas, including machinery, control loops, quality monitoring, maintenance scheduling, etc., in order to result in more processes that are more efficient overall.

With process optimization, the aim is to produce the greatest amount of output, at the highest possible quality, for the lowest possible amount of input resources, including time and labor. Process optimization usually includes eliminating unnecessary steps and automating as much as possible.

Why is process optimization important for process manufacturing plants?

With the help of process optimization, manufacturing plants can:

  • Lower the incidence of errors in e.g. configuring processes, adding ingredients to a mix.
  • Increase product quality.
  • Reduce equipment and plant downtime.
  • Save time that employees spend on tedious or repetitive tasks.
  • Decrease production costs.
  • Improve compliance with industrial and governmental regulations.
  • Boost overall plant productivity.
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How can process plants achieve process optimization?


Identify areas that need improvement

The first step is always to identify what needs improvement. Process optimization typically covers three main areas:

  • Equipment optimization, i.e. ensuring that all tools are working as efficiently as possible.
  • Operating procedure optimization, i.e. standardizing operating procedures according to that which is most efficient.
  • Control optimization i.e. ensuring the control loops which manage the processes do not overlap and are as efficient as possible.

Access real-time data

Today’s technology offers many ways to improve process optimization, but they mostly rely on accurate, up-to-date data about plant conditions. Industrial Internet of Things (IIoT) devices can monitor every aspect of the plant and share the data instantly for full visibility into the plant.

Automate as much as possible

Automating repetitive, time-consuming tasks is one of the best ways to improve quality and consistency, ensure compliance, and lower costs, while at the same time freeing up employees to focus on more complex activities that further advance process optimization.

Apply artificial intelligence (AI) and machine learning (ML)

Process-based AI and ML tools analyze real-time data to spot inefficiencies, speed up root cause analysis for faster resolution of plant issues, and, in the form of predictive analytics, even spot the first signs of developing issues so they can be corrected while still manageable.

Use digital twins

Digital twins use real-time data together with ML to create a virtual model of the plant. Process engineers can use digital twins to spot inefficiencies and investigate bottlenecks without needing to pause production. Frequently, issues can also be resolved through the digital twin, resulting in less downtime and improved productivity.

Monitor progress

Process optimization is rarely a once-and-done activity. Plant managers need to set KPIs so they can measure process optimization success and ensure that improvements remain on track.

How do process plants benefit from process optimization in manufacturing?

With the help of process optimization in manufacturing, process plants can enjoy more efficient processes and increased product quality, thereby boosting the bottom line and helping them maintain their competitive edge.