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Unformatted text preview: NATIONAL PRODUCTIVITY COUNCIL WELCOMES YOU TO A PRESENTATION ON CONTROL CHARTS By B.Girish Dy. Director Three SQC Categories Traditional descriptive statistics e.g. the mean, standard deviation, and range Acceptance sampling used to randomly inspect a batch of goods to determine acceptance/rejection Does not help to catch inprocess problems Statistical process control (SPC) Involves inspecting the output from a process Quality characteristics are measured and charted Helpful in identifying inprocess variations Statistical Process Control (SPC) A methodology for monitoring a process to identify special causes of variation and signal the need to take corrective action when appropriate SPC relies on control charts SPC Implementation Requirements Top management commitment Project champion Initial workable project Employee education and training Accurate measurement system Traditional Statistical Tools The Mean measure of central tendency The Range difference between largest/smallest observations in a set of data Standard Deviation measures the amount of data dispersion around mean n x x n 1 i i = = ( 29 1 n X x n 1 i 2 i = = Distribution of Data Normal distributions Skewed distribution Sources of Variation Common causes of variation Random causes that we cannot identify Unavoidable e.g. slight differences in process variables like diameter, weight, service time, temperature Assignable causes of variation Causes can be identified and eliminated e.g. poor employee training, worn tool, machine needing repair Common Causes Special Causes Histograms do not take into account changes over time. Control charts can tell us when a process changes Introduction to Control Charts Important uses of the control chart 1. Most processes do not operate in a state of statistical control 2. Consequently, the routine and attentive use of control charts will identify assignable causes. If these causes can be eliminated from the process, variability will be reduced and the process will be improved 3. The control chart only detects assignable causes. Management, operator, and engineering action will be necessary to eliminate the assignable causes. Monitor Variation in Data Exhibit trend  make correction before process is out of control A Process  A Repeatable Series of Steps Leading to a Specific Goal Introduction to Control Charts Show When Changes in Data are Due to: Special or assignable causes Fluctuations not inherent to a process Represent problems to be corrected Data outside control limits or trend Chance or common causes Inherent random variations Consist of numerous small causes of random variability (continued) Introduction to Control Charts Graph of sample data plotted over time...
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 Spring '11
 AK

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