Why Statistical Process Control (SPC)?

Extensive logging of data and monitoring of production processes doesn’t automatically lead to good process control. For effective process control, the most important parameters must be monitored in a way that highlights early on process performance and deviant situations. The right information must be provided at the right moment in order that operators can intervene in time, and prevent production disruptions without any downtime or loss of quality, and at minimal cost. The strength of SPC lies in recognizing and repairing deviant situations and disruptions to production as quickly as possible. Making it the cornerstone of good process control.


Step-by-step plan for the introduction of Statistical Process Control

To implement SPC you need to undergo the following steps:

  1. Process analysis: process characteristics and the risks of process disruptions are mapped by teams of operators and process technologists. Where necessary, other functions are involved, such as maintenance and quality.
  2. Identifying measurement types: determine for the most important risks which process parameters are best suited to signaling process disruption.
  3. Analysis of measurements: on the basis of collected data, determine what would be a good frequency and sample size to achieve accurate and timely signaling.
  4. Determining SPC limits and OCAPs: the process control system is made operational for application by the operators by designing Control Charts (when to intervene) and Out of Control Action Plans (OCAPs: how to intervene).


Observations from practicing Statistical Process Control

The following observations from practice can help you introduce SPC successfully and create additional added value during this process.

  • Joint development of the control methodology by the employees directly involved leads to a good understanding of the concept, and ensures that the available knowledge of the operators and process technologists is utilized effectively.
  • To get a good insight into the most important sources of variance, and into the relationships between process parameters and the end result, it’s vital to select suitable statistical analysis methods. Wrong choices here will lead to an insufficiently understood, and therefore badly controlled, process.
  • OCAPs seem to play a remarkably useful role in harmonizing the working methods of operators and in aiding the discussion about how to improve how operator deal with process disruption.
  • On the basis of the results of the process control, process technologists and quality staff work closely with production. This means they can take action quickly with operators to achieve process improvements. SPC fits perfectly here with the lean approach to production.
  • The approach to process control is tested for a limited time within existing production and can thereafter be fully included in the operational management and the review of the processes. When a new production line is launched, SPC can be used to detect deviations from the normal process, and to test the OCAPs and, if necessary, adapt them to the new installation or conditions.


CQM can help you optimize your process management

Our SPC-based approach to process control has proven itself over recent decades to be a solid foundation for quality assurance and process improvement on the work floor. In many situations, it proves possible to improve or make ways of working more efficient. To achieve such improvements, involvement of operators and process technologists, as well as a clear approach based on a good understanding of the process, are all essential. Our approach delivers good results and wide acceptance, and can thus form a solid basis for managing your processes.

Are you interested in optimizing your control methodology based on the possibilities offered by the SPC method? We’d be delighted to explain and discuss things with you in greater detail. To arrange an informal discussion, please contact one of our experts.

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Bert Schriever
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