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Statistical Process Control (SPC)

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Statistical Process Control (SPC) Page Statistical Process Control (SPC) Page 2 Table of Contents Introduction to Continuous Improvement and Statistical Process Control ........ Module 1 Basic Statistics for Statistical Process Control ............................................... Module 2 Sources of Variations: Common and Special Causes ....................................... Module 3 Distribution and Statistics for Normally Distributed Data................................. Module 4 Evaluation of Capability for a Stable Process ........ ....................................... Module 5 Average and Range Charts ............................................................................ Module 6 Interpretation of Control Charts ..................................................................... Module 7 Strategies for Sampling Data ........................................................................ Module 8 Average and Standard Deviation Charts ........................................................ Module 9 . Median and Range Charts ............................................................................. Module 10 Individual and Moving Range Chart ...................... ....................................... Module 11 Proportion and Number of Nonconforming Charts ...................................... Module 12 Number of Nonconformities and Nonconformities per unit Charts ............. Module 13 Application Guidelines ................................................................................. Module 14 Application Examples .................................................................................. Module 15 Appendices ................................................................................................... Module 16 R. Roy/Nutek, Inc. Statistical Process Control – Management Overview Version 0509 Page 3 Short List of Notations x = a number (data, sample reading). x = the average (mean) of a set of x. x = the average of the averages x , also called grand average. ≈ X = the median of the numbers x. (Symbol ≈ used for median) ≈ X = the average of the medians ∑ X = the sum of numbers x n = the total number of data K = the number of samples (if 100 parts are grouped into 20 groups of 5 each for measurement purposes, then K = 20, n = 5 for group, n = 100 for all data.) M = the mode of numbers S = the standard deviation of numbers ( SX , S X , SR , etc.). S = the average of the Standard deviation (S) R = the range of numbers R = the average of the ranges (R). µ X = The average of all possible number (even of parts that are not included in measurement) σ X = the standard deviation of all possible numbers < = less than < = less than or equal to > = greater than > = greater than or equal to = square root of quantity under the radical sign R. Roy/Nutek, Inc. Statistical Process Control – Management Overview Version 0509 Page 4 Course Overview Industrial production often involves mass production of the same part. For such parts to properly assemble and function in the final product, it is necessary to keep the variation in quality characteristic to a minimum. The variation in quality characteristics are caused mainly by two sources; known as common and special causes. Statistical process control (SPC) is used to study the process performance and understand sources of variation with the intention of making corrective actions to reduce variation. This brief session covers the basic concepts of statistical analysis and their application to practical problems in process control. It will deal with such standard tools as histograms, X-bar and R charts, process capability studies and sampling plans. It is intended to help attendees decide if SPC will be helpful their activities and whether further training should be sought before applications. Attendees to this session learn how to use histograms, Pareto charts, scatter diagrams, etc. The primary focus of the course will be to help attendees develop a working level understanding of the normal distribution and how to construct control charts for variable and attribute data. The attendees are expected to gather understanding of how to use DOE results for SPC, calculate process capabilities, and learn how to communicate with design engineering in terms of process capabilities. Instructor Ranjit K. Roy, Ph.D., P.E. (M.E.) is an engineering consultant specializing in Taguchi approach of quality improvement. Dr. Roy has achieved international recognition as a consultant and trainer for his down-to-earth teaching style of the Taguchi experimental design technique , project management , and several other quality engineering topics. Dr. Roy began his career as senior design engineer with Burroughs Corporation following completion of graduate studies in engineering at the University of Missouri-Rolla in 1972. He then worked for General Motors Corp. (1976-1987) assuming various engineering responsibilities with his last position as that of reliability manager. Dr. Roy is a fellow of the American Society of Quality. R. Roy/Nutek, Inc. Statistical Process Control – Management Overview Version 0509 Page 5 SPC STEP 6 Learning Steps Learn the rules of out-of-control STEP 5 detection based on probability of Understand the logic occurrence. behind Examine control standardization of charts carefully data collection and simplification of STEP 4 formula for Learn what are: calculations of limits - In control for control charts. - Stable - In specification - Capable STEP 3 Understand that process variation is the result of COMMON- CAUSE and SPECIAL-CAUSE variations (Fundamental Equation of SPC) STEP 2 Learn the Normal Theory and the Central Limit Theorem and their implication well. - if X is normal the distribution of the process STEP 1 average is also normal. Understand - If distribution of X is not properties of normal, the distribution of normal sample mean is still distribution. approximatly normal . - All data to fall within +/- 3 Std. Dev. under common cause variations R. Roy/Nutek, Inc. Statistical Process Control – Management Overview Version 0509 Page 6 SPC Application Steps (Observe the Process - Define Standard -Compare Performance) Carefully examine data for out-of- control situations. Mark points based on the “Rules”. 3 Calculate limits and construct the desired control charts. Plot data. 2 Collect data and calculate sample averages, ranges, grand average, 1 average range, etc. R. Roy/Nutek, Inc. Statistical Process Control – Management Overview Version 0509 Page 7 What is Statistical Process Control ? Control Process What does it mean? What does it mean? To correct: Statistical - Correct to what? Any task that affects - How do would we cost and performance What does it mean? know that it is not of products or services: right? - Incoming order Inexact: - How bad are we? processing It is never the exact - How far off is it from - Payroll checks value. what it should be? - Accounts payable - How fast do we need - Part fabrication Predicted value based to correct the situation? (milling, turning, on more than one welding, molding, etc) observed data: To keep it where it - Typing/data entry Data used for - Assembly of parts should be: calculating any statistic - Soldering - How do we find out (numeric value) are where should it be? more than one. Any operation or - What can we do to sequence of operation bring it where it should Estimate based on a with measurable be? small data sample from output: - How do we know it is the whole: not where it should be? Valid for average performance: Conclusions based on past observations: R. Roy/Nutek, Inc. Statistical Process Control – Management Overview Version 0509 Page 8 Module 1 Introduction to Continuous Improvement and Statistical Process Control R. Roy/Nutek, Inc. Statistical Process Control – Management Overview Version 0509 Page 9 Introduction to Continuous Improvement and Statistical Process Control What is Quality? - Meeting Specifications - Preventing Defects - Practicing Continuous Improvement “Quality is meeting or exceeding customer expectations at all times in regards to performance, durability, reliability, and delivery at a cost that represents value.” “Quality is producing a reliable & durable product to exact standard at the lowest cost for the customers.” How? - Product Control - Process Control In 1970’s W. Deming, J. Juran and others emphasized the need to shift focus from product control to process control. Stop depending on inspection to achieve quality. Eliminate the need for extensive inspection programs by designing and building quality into the product or service in the first place. - W. Edward Deming A Sample Process R. Roy/Nutek, Inc. Statistical Process Control – Management Overview Version 0509 Page 10 Transformation Machine * Input * Output * Products * People - Work process * Services * Machine - Add value to input * Materials * Customer - Assemble materials satisfaction Product Control Vs. Process Control Items/Activities How it is done Product Control Process Control Practical Objectives Keep Product Characteristics Try to be on target with within specifications minimum variation satisfying the quality standard Ideal Objectives Detect and eliminate non- Assure that non-conforming conforming products products are not produced Improvement Strategy Inspect and maintain outgoing Institute and maintain product quality continuous quality improvement procedures Statistical Techniques Acceptance Sampling Control Charts (SPC) R. Roy/Nutek, Inc. Statistical Process Control – Management Overview Version 0509 Page 11 Module 2 Basic
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