How CP Kelco reduced process deviations, resulting in yearly potential savings of over $1m

About CP Kelco

‍

CP Kelco, part of J.M Huber Corporation, is a leading producer of speciality hydrocolloids with offices and facilities across the globe. Their speciality hydtocolloids are used as a water-based thickener or stabilizer in a large variety of products. In addition, CP Kelco leverages its capabilities to bring concepts and ideas to real-workd products in a broad range of applications.

‍

‍

CP Kelco Success Story

‍

‍

How industrial analytics transforms them to face the future

‍

Norman Ridgley works as Senior Manager Operational Excellence at CP Kelco globally. In his presentation at PI World 2018, Norman will discuss how TrendMiner’s self-service analytics on top of OSIsoft PI helps their production facility to gain deeper insight in operational performance.

‍

‍

‍

Their Digitalization Journey

‍

Senior Manager Operational Excellence, Norman Ridgley was looking for a way to advance their usage of plant data. Receiving more insights would enable them to improve throughput and quality while lowering operating costs. At that time, CP Kelco sites were working with basic OSIsodt PI systems, which collected raw data.

‍

CP Kelco decided that the following actions had to be taken to get more value from their time-series data. Firstly, they agreed that it is necessary to create data relationship at the process and batch level. And further, identify tools for visualizing, trending, and analysis. In line with these goals, they decided to use TrendMiner.

‍

TrendMiner proved to be a key support tool which helped CP Kelco find deviations within their production process. By implementing TrendMiner on top of OSIsoft PI, it became much easier to analyze and monitor their production process. CP Kelco was able to reduce the use of raw materials and produce more efficiently with better control of quality.

‍

‍

‍

Solution and Implementation

‍

‍

CP Kelco uses TrendMiner to get deeper insights into operational performance

‍

TrendMiner helped CP Kelco to visualize and draw conclusions from their time-series data. It helped them to perfrom root-cause analysis without complex data modeling techniques to assess what causes deviations against best operational performance.

‍

‍

Analyze based on exceptions to drive simplicity

Researching all situations that deviate from standard operational practice with self-service analytics helps CP Kelco to make meaningful improvements that have the largest impact on their operational perfromance.

‍

Promote organic growth across sites sharing success

In order to maximize the utilization of data, the team decided that their process engineers needed to be trained properly. They want to promote the use of advanced industrial analytics in their organization.

‍

‍