Data and Clean-in-Place

How food manufacturers can ensure a quality clean every time.

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Just as cleaning processes vary by product and industry, so do their effectiveness.

When a process or cleaning instance becomes ineffective, we may assume contaminants have grown resistant to the chemical. To address inconsistent sanitation results, many food processors have moved to new chemistries or automated equipment. However, even automated processes leave much room for error, as numerous other factors can cause the effectiveness of a clean to fluctuate.

Often, the issue causing an ineffective clean comes down to an element within the cleaning process itself, not the chemical or equipment. When evaluating clean-in-place systems (CIP), chemical concentration, contact time, temperature, and conductivity are all critical factors to achieving an effective clean. If one of these elements varies too much, a clean could, at best, result in wasted water and chemical and, at worst, fail to meet compliance or cause food safety risks.

For example, a clean not heated to the proper temperature for the appropriate time may have to be rerun, and if not, it could pose a food safety risk. Overly concentrated chemicals can damage equipment, while under-concentrated chemicals become less effective. The success of a clean depends on the repeatability and consistency of every step and element in the sanitation process, beyond just the sanitizer. 

Throughout the history of food processing, monitoring these elements was difficult, if not impossible. Fortunately, as capabilities in data gathering and analytics grow, food processors can harness that power and improve the effectiveness of their cleaning processes—and food hygiene, sustainability, and efficiency, as well. 

Accessing the Full Story of Your Clean

Until recently, the story of a sanitation process was buried. In the case of clean-in-place procedures, employees could document some data points, such as when a CIP process ran. They could check that water and chemicals were present and run the process for the time the recipe called for. However, visibility into the above factors—chemical concentration, water temperature, delivery and return flow, and conductivity—was (and in many cases, still is) lacking. Plants could be breaking compliance without knowing it due to the lack of visibility into these critical facets of food hygiene and efficiency.

While many industries have capitalized on the insights data can provide, data analytics is relatively new to the food processing industry, at least in sanitation and clean-in-place processes. However, the stories that data can tell are invaluable to food processors. With new software and data analysts emerging in the industry, food processors can gain a clearer view into their cleaning processes and monitor critical data points that affect compliance, efficiency, sustainability, and costs.

For example, plant managers can now visualize factors like water temperature, flow, conductivity, the amount of caustic or alkaline chemicals used, and other parameters using a site’s installed sensors that send that data from the plant’s automation system to the cloud. This allows a plant manager (or anyone with access to the program) visibility into every run, from start to finish. These programs empower users to measure the effectiveness of a run down to the phase and time stamp. 

With visualizations like these, plant managers can uncover patterns and variances over several runs, notifying you of more significant issues or isolated events.

This software enables plant managers to review data from individual sensors during cleaning phases, uncovering details that can help pinpoint water, energy, or chemical loss.

In other words, data analysis unveils the full story of a plant’s clean, down to the granular details.

Using Insights to Ensure a Consistent, Effective Clean

Once plant managers can see the story of their full cleaning process—including the concentration and effectiveness of chemistries—they can use that data to help achieve food safety, resource sustainability and business goals. That means they can work towards a more consistent, repeatable clean, and address issues like overheating, chemical losses, and challenges in compliance. In short, plants can more responsively manage key performance indicators for food safety, efficiency, and quality improvements.

The Future of Sanitation in Food Processing

Big data has enabled countless brands to improve processes, make better business decisions, and increase profitability. Now, food and beverage processors can do the same, and at a crucial time for food hygiene and water and energy stewardship. Success in food and beverage processing now takes more than a quality product; it takes uncompromising standards for hygiene, compliance, stewardship, and costs. It’s data that can help you set and meet those standards—every run, every time.

Barry Sperling is a project manager at Diversey Food and Beverage.

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