The need for integrating statistical process control and automatic process control
Abdul‐Wahid A. Saif
Abstract
Abdul‐Wahid A. Saif
Abstract
Statistical Process Control (SPC) and Automatic Process Control (APC) are two different methods for quality improvement and process adjustment that have been developed in isolation from each other and applied within different industries. SPC minimizes variability by monitoring and eliminating the assignable causes of variation whereas APC achieves the same objective by handling manipulated process variables to keep the process outputs on target. Initially, both methods were considered to be in conflict with each other, until their advocates realized the fact that the techniques being applied were complementary. Consequently, a considerable amount of work has appeared in the literature regarding the joint use of APC and SPC that provided a breakthrough in the field of process control. This paper highlights the developments and the need for the integration of this two techniques Also it highlights the associated issues and possible future directions of research. An example that require the integration of both methods is presented.
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Statistical Process Control (SPC) and Automatic Process Control (APC) are two different methods for quality improvement and process adjustment that have been developed in isolation from each other and applied within different industries. SPC minimizes variability by monitoring and eliminating the assignable causes of variation whereas APC achieves the same objective by handling manipulated process variables to keep the process outputs on target. Initially, both methods were considered to be in conflict with each other, until their advocates realized the fact that the techniques being applied were complementary. Consequently, a considerable amount of work has appeared in the literature regarding the joint use of APC and SPC that provided a breakthrough in the field of process control. This paper highlights the developments and the need for the integration of this two techniques Also it highlights the associated issues and possible future directions of research. An example that require the integration of both methods is presented.
Key concepts: Statistical process control, Process (computing), Process control, Computer science, Process capability, Control chart, Work in process, Control (management)