Statistical process control

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Template:Infobox Quality Management

Statistical Process Control (SPC) is a method used in quality control and manufacturing to ensure that processes operate efficiently, producing more specification-conforming products with less waste (rework or scrap). SPC uses statistical methods to monitor and control a process. This helps to ensure the process operates efficiently, producing more specification-conforming products with less waste (rework or scrap). SPC can be applied to any process where the "conforming product" (product meeting specifications) output can be measured.

Overview[edit | edit source]

The key elements of SPC are to monitor the process behavior using control charts and to reduce process variation including both common causes and special causes of variation. This approach uses a continuous feedback loop to detect and correct deviations from a stable process.

History[edit | edit source]

SPC was pioneered by Walter A. Shewhart in the early 1920s. Shewhart developed the control chart as a statistical heuristic to distinguish between the two types of variation. Later, W. Edwards Deming popularized SPC in Japanese manufacturing facilities after World War II. The techniques have since been widely adopted throughout various industries to improve product quality and process efficiency.

Control Charts[edit | edit source]

Control charts, also known as Shewhart charts or process-behavior charts, are a statistical tool used in SPC to determine whether a manufacturing or business process is in a state of control. It is more efficient to draw a control chart and to use it to monitor the process to detect significant changes in the process mean or variability.

Types of Control Charts[edit | edit source]

  • Individuals Chart (I-chart): Used when one data point is collected at each time from a continuous shift.
  • Moving Range Chart (MR-chart): Used to monitor the variability of the process.
  • X-bar and R Chart: Used when subgroups of a larger sample are taken at regular intervals.

Implementation[edit | edit source]

The implementation of SPC involves selecting the appropriate control chart, determining the proper sampling strategies, and establishing clear criteria for interventions. Training for process operators on how to read and respond to the control charts is also crucial.

Applications[edit | edit source]

SPC is used in a variety of industries including manufacturing, finance, healthcare, and information technology to improve product and service quality by reducing variability.

Challenges[edit | edit source]

Challenges in implementing SPC include resistance to change, lack of management commitment, poor training, and inadequate understanding of statistical methods.

Benefits[edit | edit source]

The primary benefit of SPC is the potential for significant improvements in quality and efficiency, leading to reduced waste, improved consistency, and increased customer satisfaction.

See Also[edit | edit source]

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Contributors: Prab R. Tumpati, MD