OM-4.2 Quality Management - Process Control.pptx - STATISTICAL QUALITY MANAGEMENT STSTISTICAL PROCESS CONTROL KRIPA SHANKER Ph D(Cornell FNAE FIE(I

OM-4.2 Quality Management - Process Control.pptx -...

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Unformatted text preview: STATISTICAL QUALITY MANAGEMENT STSTISTICAL PROCESS CONTROL KRIPA SHANKER Ph D (Cornell) FNAE, FIE(I), FITEE(I), LMISTE, LMIIIE, MORSI, MORSA, SMIIE Visiting Faculty Department of Mechanical Engineering Indian Institute of Technology (BHU) Varanasi Former Emeritus Fellow Industrial and Management Engineering Department Indian Institute of Technology Kanpur Former Vice Chancellor, Uttar Pradesh Technical University Lucknow Former Deputy Director, Indian Institute of Technology 1 Kripa Shanker Kanpur 2 Prof Kripa Shanker Mechanical Engineering IIT (BHU) Varanasi STATISTICAL PROCESS CONTROL All processes are subject to a certain degree of variability - (a fact about the nature !) • Causes of Variation : Common (natural) (chance) (random) Special (assignable) • Control Chart (Walter Shewhart, 1920s, Bell Laboratories) Separates the two causes of variation. Kripa Shanker 3 STATISTICAL PROCESS CONTROL • PROCESS CONTROL A process is said to be operating in statistical control when the source of variation is only the common (natural) (chance) (random) causes. Process must first be brought into statistical control by detecting and eliminating special (assignable) causes. Kripa Shanker 4 STATISTICAL PROCESS CONTROL • PROCESS CONTROL Once the process is under control, then its performance is predictable, its ability to meet the customer expectations can be assessed. The objective of a process control system is to provide a statistical signal when assignable causes of variation are present. Kripa Shanker 5 STATISTICAL PROCESS CONTROL NATURAL VARIATIONS (common) (chance) (random) variations affect almost every • Natural process and, are to be expected. are many sources of natural • There variation that occur within a process (even when the process is under statistical control !). Natural variations form a pattern (can be described as distribution) As long as the distribution (output • measurements) remains within specified limits, the process is said to be “in control“,6 Kripa Shanker STATISTICAL PROCESS CONTROL ASSIGNABLE VARIATIONS variations in a process can • Assignable be traced to a specific reason : • • • • • machine wear, mis-adjustment in equipment, fatigued or untrained worker, new batches of materials), etc. Kripa Shanker 7 STATISTICAL PROCESS CONTROL QUALITY MANAGEMENT TASKS Natural and Assignable variations distinguish two tasks : (1) to ensure that the process is capable of operating under control (with only natural variations.) (2) to identify and eliminate assignable variations so that the process remains under control. Kripa Shanker 8 STATISTICAL PROCESS CONTROL QUALITY MANAGEMENT TASKS Measurements - Samples vs Individual Because of natural and assignable variations, statistical process control (SPC) uses statistics (eg. average, range, etc.) of samples (often 4 to 8) as opposed to data on individual parts. Individual pieces tend to be two erratic to make trends quickly visible. Kripa Shanker 9 STATISTICAL PROCESS CONTROL CONTROL CHARTS Control Chart (Walter Shewhart, 1920s, Bell Laboratories) Separates the two causes of variation. → A statistical tool to determine if a process is in • Because of natural and assignable control. variations, statistical process control (SPC) uses statistics (eg. average, range, etc.) of samples (often 4 to 8) as opposed to data on individual parts. • Individual pieces tend to be two erratic to 10 Kripa Shanker make trends quickly visible. STATISTICAL PROCESS CONTROL CONTROL CHARTS Theory of Control Chart X : Quality Characteristic (length, diameter, weight, surface finish, …..) • UCL = Process Average + 3 Standard Deviations • LCL = Process Average - 3 Standard Deviations X UCL = Upper Control Limit + 3X Process Average : Central Line - 3X LCL = Lower Control Limit TIME 11 Thank You ...
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  • Winter '15
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