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 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 11 - 1 Chapter 11 Statistically-Based Quality Improvement for Variables.

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Presentation on theme: " Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. 11 - 1 Chapter 11 Statistically-Based Quality Improvement for Variables."— Presentation transcript:

1  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Chapter 11 Statistically-Based Quality Improvement for Variables

2  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Chapter 11  Statistical Fundamentals  Control Charts  Some Control Chart Concepts for Variables  Process Capability for Variables  A Closer Look at Quality  Other Statistical Techniques in Quality Management

3  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Statistical Thinking  All work occurs in a system of interconnected processes  All process have variation (The amount … tends to be underestimated)  Understanding variation and reducing variation are important keys to success

4  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Why do statistics sometimes fail in the workplace?  Lack of knowledge about the tools  General disdain for all things mathematical  Cultural barriers in a company  Statistical specialists have trouble communicating

5  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Why do statistics sometimes fail in the workplace?  Statistics generally are poorly taught, emphasizing mathematical development rather than application  People have a poor understanding of the scientific method

6  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Why do statistics sometimes fail in the workplace?  Organizations lack patience in collecting data. All decisions have to be made “yesterday”  Statistics are viewed as something to buttress an already-held opinion  People fear using statistics

7  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Why do statistics sometimes fail in the workplace?  Most people don’t understand random variation  Statistical tools often are reactive and focus on effects rather than causes

8  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Type I and Type II Errors  Type I error  Producers risk  Probability that a good product will be rejected  Type II error  Consumers risk  Probability that a nonconforming product will be available for sale

9  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Understanding Process Variation  Random variation  Centered around the mean  Consistent amount of dispersion

10  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Understanding Process Variation  Nonrandom variation  “Special Causes”  Results from some event  Dispersion and average of the process are changing  Process that is not repeatable

11  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Understanding Process Variation  Process stability  Random Variation  Not nonrandom variation  Process Charts

12  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals Understanding Process Variation  Sampling Methods  Samples are cheaper  Take less time  Less intrusive  Destructive tests may destroy the sample

13  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals  Random Samples  Each piece has an equal chance of being selected for inspection  Systematic Samples  According to time or sequence  Rational subgroups  A group of data that is logically homogeneous  Computing variation between subgroups

14  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Statistical Fundamentals  Planning for Inspection  What type of planning will be used  Who will perform the inspection  What critical attributes to be inspected are

15  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Control Charts Variables and attributes control charts  You must understand this generic process for implementing process charts  You must know how to interpret process charts

16  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Control Charts Variables and attributes control charts  You need to know when different process charts are used  You need to know how to computer limits for the different type of process chart

17  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Control Charts A generalized procedure for developing process charts  Identify critical operations in the process  Identify critical product characteristics  Determine whether the critical product characteristic is a variable or an attribute

18  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Control Charts A generalized procedure for developing process charts  Select the appropriate process control chart  Establish the control limits and use the chart to continually monitor and improve  Update the limits when changes have been made to the process

19  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Control Charts Understanding control charts A control chart is an application of hypothesis testing where: The null hypothesis is that the process is stable

20  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Some Control Chart Concepts for Variables  Choosing the correct variables control chart  Are the data variable?  Is it homogeneous in nature or not conducive to subgroup sampling?

21  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Some Control Chart Concepts for Variables  When a process is out of control some corrective action is needed:  Identify the quality problem  Form the correct team to evaluate and solve the problem  Use structured brainstorming  Brainstorm to identify potential solutions

22  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Some Control Chart Concepts for Variables  When a process is out of control some corrective action is needed:  Eliminate the cause  Restart the process  Document the problem, root cause and solutions  Communicate the results

23  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Process Capability for Variables A highly capable process produces high volumes with few or no defects World-class levels of process capability are measured by parts per million (ppm) defect levels

24  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Process Capability for Variables Six Sigma A design program which emphasized engineering parts so that they are highly capable

25  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Process Capability for Variables Capability Studies Two purposes to determine whether a process is capable  To determine whether a process consistently results in products that meet specifications  To determine whether a is in need of monitoring

26  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Process Capability for Variables The difference between capability and stability A process is capable if individual products consistently meet specification A process is stable only if common variation is present in the process

27  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Strategic Quality Planning Statistically-Based Quality Improvement for Variables Summary You need:  To know the generic process for developing charts  To be able to interpret charts  To be able to choose which chart to use  The formulas to derive the charts  To understand the purposes and assumptions underlying the charts

28  Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America.


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