Process control in the food industry
Why Statistical Process Control (SPC)?
Extensive logging of data and monitoring of production processes does not automatically lead to good process control. Good process control requires that the most important parameters are monitored in a way that provides early insight into process performance and abnormal situations. The right information must be provided at the right time so that operators can intervene in time and prevent production disruptions as quickly as possible without downtime, without loss of quality and with minimal costs. The power of Statistical Process Control (SPC) is to recognize and repair abnormal situations and disruptions in production as quickly as possible. It is therefore the foundation for good process control.
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Step-by-step plan for implementing Statistical Process Control (SPC)
To implement Statistical Process Control (SPC), follow these steps:
- Process analysis: Teams of operators and process technologists identify process characteristics and the risks of process disruptions. Other functions, such as maintenance or quality, are involved where necessary.
- Defining measurement types: For the most significant risks, determine which process parameters are suitable for detecting process disruptions.
- Analysis of measurements: Based on collected data, determine the appropriate frequency and sample size to ensure accurate and timely detection.
- Determining SPC limits and OCAPs: Operationalize the process control system for use by operators by designing control charts (indicating when to intervene) and Out-of-Control Action Plans (OCAPs, indicating how to intervene).
Practical observations on Statistical Process Control (SPC)
The following practical observations can assist you in successfully implementing Statistical Process Control (SPC) and generating additional value during the process.
- Collaborative development of the control methodology by the employees directly involved fosters a shared understanding and ensures that the expertise of both operators and process technologists is effectively utilized.
- Selecting appropriate statistical analysis methods is crucial for gaining insight into the primary sources of variation and the relationships between process parameters and the final outcome. Incorrect choices lead to an insufficiently understood process and, consequently, poor process control.
- OCAPs (Out-of-Control Action Plans) prove remarkably useful in harmonizing operator workflows and facilitating discussions on how operators handle process disturbances.
- Based on process control results, process technologists and quality staff collaborate closely with production teams, enabling them to quickly initiate process improvement actions alongside operators; SPC thus aligns perfectly with the lean production approach.
- The process control strategy is tested within the existing production environment for a limited period before being fully integrated into operational management and process reviews. When launching new production lines, SPC can be used to detect deviations from standard operations, test OCAPs, and where necessary adjust them to suit the new equipment and conditions.
CQM can help you optimize your process control
Over the past few decades, our Statistical Process Control (SPC) methodology has proven to be a solid foundation for quality assurance and process improvement on the shop floor. In many situations, there is scope to improve the method or use it more efficiently. Operator and process technologist involvement combined with a clear approach based on a thorough understanding of the process proves essential for achieving these improvements. Our approach delivers excellent results and high levels of acceptance, thereby serving as a solid basis for managing your processes.
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