Diversey’s new IntelliCIP platform uncovers deep data insights to optimise CIP performance

Diversey – the leading global hygiene and cleaning company – is launching its IntelliCIP (Clean-in-Place) cloud-based data analytics platform. Designed to securely collate and process Food and Beverage (F&B) production CIP data, IntelliCIP delivers real-time insight into hygiene compliance and the operational performance of each cleaning run.

By analysing and monitoring selected data points, a production facility can easily access, review and act on its CIP results. Facilities will now be able to truly understand if their CIP process is in control.

Measuring the True Effectiveness of Each CIP Run

IntelliCIP provides a solution to constant issues in the F&B industry. Specifically, ensuring food safety, quality, and traceability in the context of cost pressures and changing production demands. These, alongside dealing with large amounts of data, are familiar challenges that confront effective CIP management. IntelliCIP unlocks information that is typically buried within the automation system, or within results from current manual tracking.

Until IntelliCIP, understanding if excess resources are being used, or if a risk of contamination is being caused to products because hygiene parameters are not being met, has been largely unexplored. Similarly, being fully aware of where the potential for operator intervention has an impact on the efficacy and efficiency of cleaning.

Converting Data into Actionable Information

IntelliCIP has an easy-to-use interface that enables a site to view where a CIP may be causing a loss of resources; while it also compares run data to visualise the variances within the process. The data is automatically collected and analysed to provide proof of compliance with the cleaning protocols. This is in addition to indicators and opportunities – which are revealed progressively – to identify where production can be optimised.

Cleaning run reports let users act quickly to undertake corrective actions that are focused and swift, to ensure food safety, and improve operational efficiency and sustainability. There is expectation of site automation driving repeatability in each cleaning run for a recipe. IntelliCIP’s statistical analysis reveals the variance between the cleaning runs over time, allowing focused data-driven improvements to be implemented and providing more confidence that there will be no negative effect on the cleaning result.

Ruben Jakobs, Knowledge Based Services Leader, Diversey, states: “IntelliCIP is the next evolution in data gathering in the F&B industry. Diversey is delivering a solution that is a step change, transforming the transparency of our customers’ CIP data, with a primary focus on revealing insight on efficiencies and hygiene regardless of sector. It will now be possible for our customers to determine whether they are under or over-cleaning. Previously, with such a wide range of data available, it has proven difficult for them to gather a clear picture. The data remains almost hidden, crucially along with the potential insights to improve hygiene, efficiency, and many other aspects of their operations. The overwhelming majority of CIP systems are not changed from the point of installation and until the fresh perspectives that IntelliCIP offers, there has been nothing to make sense of this data. With this new clarity, production facilities will finally be able to see if their organisation is working to their expectations and adjust accordingly as a consequence.”

Continuous Process Monitoring

IntelliCIP’s continuous process monitoring gives facilities the control to ensure hygienic target compliance, an overview of chemical and utilities to track water, energy, and chemical consumption, and the ability to manage their KPIs for food safety, efficiency, and quality improvements. This new remote monitoring and analysis platform provides access to a quick view of CIP processes for any date range, specific unit, CIP circuit, or recipe, and enables responsive action when compliance with defined (validated) parameters have not been met.

 

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