Super smart: In-line product quality measurements
“Super smart: in-line measurement of product quality”
Super smart: in-line measurement of product quality. Instead of off-line product quality tests. Why? Because you can immediately notice if the production process is not performing optimally: it allows you to timely adjust your production process, in order to prevent rejected batches and ensure product quality consistency. So, is the introduction of in-line measurement always a no-brainer? I’d say yes: if you take the right approach.
It starts with defining the business case: a sound calculation of potential savings that come with an in-line measurement system. Demonstrate the benefits and prove the return on investment. Include the current losses related to rework- and rejects, and the value of product quality consistency. And – of course – the time efficiency benefits related to taking samples and performing off-line product quality tests. And what about time efficiency related to an early warning of process deviations: your chance to prevent off-spec production! A manual product quality test will always be late and leaves you lagging behind.
If the result of this calculation is convincing, you make a fair chance that your project will be approved.
How to use in-line measurement data
Depending on the nature of your product and production process, you select the most suitable in-line measurement device and arrange for installation and validation. But this is only the beginning: because how can you ensure that the in-line measurement results will actually be used optimally for a better product quality?
Predictive capacity and inter-relations with other process conditions
For example: we measure in-line moisture-content, pH, brix or viscosity. What’s important at this point is to analyze the measurement data to find answers to questions like:
– What is the predictive capacity of your in-line measurement for the product quality of your end-product?
– Which parameters in my production process are interrelated to my in-line measurements?
– Which of these parameters can be influenced by the plant operator?
– Which adjustments to the process are best in case of deviations in in-line measurements? Operators need guidelines for this.
Provide context to your in-line measurements
To find an answer to this type of questions, you need more data from your process. This can be machine data, or data relating to end-product quality or even raw material product quality. And – of couse – the data coming from your in-line measurements.
Fact-based models to optimize process control
Anyway…….in order to end up with a good data analysis, you need to bring together the necessary data. This will allow you to see trends, discover correlations between processing conditions that influence product quality, etc. Now you can define fact-based models to optimize process control from raw materials receipt, during the various stages of your production processes, until end-product quality
Clear instructions for your operators
This will enable you to end up with clear instructions for operators and quality control engineers how to operate the process. If you can incorporate these instructions in your factory’s real-time monitoring system, then you have a real good support system for the daily factory operations.
HAI has succesfully created real-time monitoring software systems for many factories.
Do you want to know how we can do this for your factory too? Please contact us for a free consultation.
Interested in more best practices of smart use of factory data, especially in the Food Industry?
Get inspired by successes of others when it comes to OEE, quality, positive release, golden batch, CIP-cleaning, operator support, factory data anaytics, in-line measurements, factory dashboards… and much more.
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