What is process data?

Process data is simply another term for the massive amounts of data generated by the many processes that take place in a manufacturing plant. Process data is generally made up of time series data, which is gathered by the myriads of sensors on equipment and parts and the Industrial Internet of Things (IIoT) connected devices which make up the plant itself.

Process data is a subset of big data which has been transforming industries and verticals for the past few years. It’s typically stored in a data historian, which automatically collects data from the various devices around the plant and compresses it for long-term storage.

With the advent of artificial intelligence (AI) and machine learning (ML)-powered analytics, manufacturing executives are able to extract more value from the wealth of process data produced by the plant. Process data is the foundation of today’s newest applications like predictive maintenance, predictive monitoring, and predictive analytics.

Why is process data important for process manufacturing plants?

Process data and advanced analytics together can help manufacturing companies gain a better understanding of plant operations in order to optimize them for greater efficiency and productivity.

With the right tools, process data can enable manufacturing plants to:

  • Pick up on the early signs of part failure, implement a quick repair, and thus reduce plant downtime, cut labor costs, and extend equipment lifecycle.
  • Identify process anomalies that indicate issues like fouling or blockage, and respond quickly to maintain high product quality and quantity.
  • Improve root cause analysis, frequently removing the need for employees to enter a hazardous area to investigate and cutting the time it takes to resolve an issue.
  • Spot areas where speed, efficiency, and/or quality could be improved to increase overall profitability.
  • Understand the strengths and weaknesses of the plant, so as to be ready to seize opportunities and mitigate risks as soon as they appear.

How can process plants make the most of their process data?


Improve data collection

It’s important to make sure that you’re getting a full picture of operations in the entire plant, with sensors and monitors for every item of equipment and process, and that all the data you gather can be accessed and analyzed by your analytics tools. Send process data to a central hub so that there are no silos preventing it from being crunched.

Invest in the right tools

It’s clear that there’s far too much process data for manual analysis to make much headway, and even digital analytics struggle to keep up with the flood of industrial big data. You need advanced analytics platforms that use ML and AI to analyze data in real-time and quickly spot emerging patterns.

Invite all stakeholders to benefit from process data

Process data insights and predictions can bring value to all corners of a manufacturing business; as long as you make it possible for employees to access them. Look for self-serve, user-friendly analytics tools that allow all your workers to help themselves to insights, including those who don’t have training in data science.

Establish business goals

Process data insights are a means to an end. You can’t gain their true value if you don’t know what you’re measuring or what you wish to achieve, so at the same time and enhancing your data collection and analytics capabilities, it’s vital to define the KPIs you wish to improve or business strategy questions that you want to explore.

How do process plants benefit from process data?

Process data is the raw material that powers advanced analytics applications. Manufacturing plants can take their insights and predictions, and use them to increase plant efficiency, optimize production quality and quantity, and sharpen their competitive edge in a crowded market.