Statistical process control


Statistical process control (SPC) is defined as the use of statistical techniques to control a process or production method. SPC tools and procedures can help you monitor process behavior, discover issues in internal systems, and find solutions for production issues. 

Why use Statistical Process Control

Today companies face increasing competition and operational costs, including raw materials increasing. So, it is beneficial for organizations to have control over their operation.

Organizations must try to continuously improve quality, efficiency, and cost reduction. Many organizations still follow inspection after production for quality-related issues.

SPC helps companies to move towards prevention-based quality control instead of detection-based quality controls. By monitoring SPC graphs, organizations can easily predict the behavior of the process.

Statistical Process Control Benefits

  • Reduce scrap and rework
  • Increase productivity
  • Improve overall quality
  • Match process capability to product requirement
  • Continuously monitor processes to maintain control
  • Provide data to support decision making
  • Streamline the process
  • Increase in product reliability
  • Opportunity for company-wide improvements

Statistical Process Control Objective

SPC focuses on optimizing continuous improvement by using statistical tools to analyze data, make inferences about process behavior, and then make appropriate decisions.

The basic assumption of SPC is that all processes are generally subject to variation. To that end, Variation measures how data are spread around the central tendency. Moreover, variation may be classified as one of two types, random or chance cause variation and assignable cause variation.

Common Cause: A cause of variation in the process is due to chance but not assignable to any factor. It is the variation that is inherent in the process. Likewise, a process under the influence of a common cause will always be stable and predictable.

Assignable Cause: It is also known as “special cause.” Therefore, the variation in a process that is not due to chance can be identified and eliminated. In this case, a process under the influence of a special cause will not be stable and predictable.

International Conference on Statistical Methods for Analyzing Engineering Data

4th Edition of Statistics | 23-24 June 2023 | San Francisco United States (Hybrid)






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