Abstract
Statistical process control (SPC) and automatic process control (APC) are two important methods that have been used for improving product quality and process productivity. SPC is used for process monitoring, while APC is used for process adjustment. SPC reduces process variability by detecting and eliminating special causes of process variation, while APC reduces variability by adjusting the process to keep the product variability on target. Both the methods were initially thought to be in conflict with each other, but in recent years, many researchers have shown their interest in integrating SPC and APC techniques to reduce total variability of the process. They have found that the techniques used in these two methods are complementary rather than contradictory. A considerable amount of work has appeared in the literature about methods that combine SPC and APC techniques for the same process. In this paper, we will cover preliminaries on SPC and APC and outline the major techniques applied by both. Literature survey related to the issues facing their integration will be outlined. We will also summarise different strategies followed to achieve their integration. Possible future directions of research will be highlighted and our concluding remarks will be indicated.
| Original language | English |
|---|---|
| Pages (from-to) | 375-405 |
| Number of pages | 31 |
| Journal | International Journal of Industrial and Systems Engineering |
| Volume | 11 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jun 2012 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- APC
- Automatic process control
- EWMA
- Exponentially weighted moving average
- Feedback control loop
- PID controller
- SPC
- SPC tools
- Shewhart control chart
- Statistical process control
ASJC Scopus subject areas
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
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