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Statistical Process Control in Automated Manufacturing features time series applications in discrete manufacturing such as Kalman filter approach....introduces generalized control charting as an alternative to traditional charts....considers multivariate techniques, including a generalization of narrow-limit gaging...suggests a taxonomy for sensor fusion....explains how symbolic and mathematical processes work together for process control...and describes real-time sensory-based control of a CNC machine tool.
Statistical Process Control in Automated Manufacturing serves as an authoritative reference for quality control, process, mechanical, manufacturing, industrial, automation, and electrical engineers as well as applied and industrial statisticians, software developers, and manufacturers of data collection equipment.