Chapter Topics Total Quality Management (TQM) Theory of Process Management (Deming’s Fourteen points) The Theory of Control Charts Common Cause Variation.

Slides:



Advertisements
Similar presentations
© 1997 Prentice-Hall, Inc. S3 - 1 Principles of Operations Management Quality Via Statistical Process Control Chapter S3.
Advertisements

Operations Management Statistical Process Control Supplement 6
Chapter 9A Process Capability and Statistical Quality Control
Quality Assurance (Quality Control)
1 DSCI 3123 Statistical Process Control Take periodic samples from a process Plot the sample points on a control chart Determine if the process is within.
Copyright 2006 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Statistical Process Control Operations Management - 5 th Edition.
BMM 3633 Industrial Engineering
Statistical Process Control Operations Management - 5 th Edition Chapter 4 Roberta Russell & Bernard W. Taylor, III.
2000 by Prentice-Hall, Inc1 Statistical Process Control Take periodic samples from processTake periodic samples from process Plot sample points on control.
Statistical Process Control. 4-2 Lecture Outline  Basics of Statistical Process Control  Control Charts  Control Charts for Attributes  Control Charts.
1 Manufacturing Process A sequence of activities that is intended to achieve a result (Juran). Quality of Manufacturing Process depends on Entry Criteria.
Chapter 14 Statistical Applications in Quality Management
Statistical Process Control. Overview Variation Control charts – R charts – X-bar charts – P charts.
Copyright ©2011 Pearson Education 17-1 Chapter 17 Statistical Applications in Quality Management Statistics for Managers using Microsoft Excel 6 th Global.
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall8-1 Chapter 8: Statistical Quality Control.
CD-ROM Chap 17-1 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. A Course In Business Statistics 4 th Edition CD-ROM Chapter 17 Introduction.
Chapter 18 Introduction to Quality
Statistical Process Control Operations Management Dr. Ron Tibben-Lembke.
Statistical Process Control
Statistical Process Control Managing for Quality Dr. Ron Lembke.
Statistical Process Control Dr. Ron Lembke. Statistics.
originally developed by Walter A. Shewhart
Process Improvement Dr. Ron Tibben-Lembke. Statistics.
CHAPTER 8TN Process Capability and Statistical Quality Control
Transparency Masters to accompany Operations Management, 5E (Heizer & Render) 4-20 © 1998 by Prentice Hall, Inc. A Simon & Schuster Company Upper Saddle.
Irwin/McGraw-Hill 1 TN7: Basic Forms of Statistical Sampling for Quality Control Acceptance Sampling: Sampling to accept or reject the immediate lot of.
Process Improvement Dr. Ron Tibben-Lembke. Quality Dimensions  Quality of Design Quality characteristics suited to needs and wants of a market at a given.
Module 3: Statistical Quality Control Operations Management as a Competitive Weapon.
MIM 558 Comparative Operations Management Dr. Alan Raedels, C.P.M.
Using Control Charts to Keep an Eye on Variability Operations Management Dr. Ron Lembke.
NATIONAL PRODUCTIVITY COUNCIL WELCOMES YOU TO A PRESENTATION ON
Chapter 17 Statistical Applications in Quality Management
Statistics for Managers Using Microsoft® Excel 4th Edition
Statistical Process Control
Chapter 13 Quality Control and Improvement COMPLETE BUSINESS STATISTICSby AMIR D. ACZEL & JAYAVEL SOUNDERPANDIAN 7th edition. Prepared by Lloyd Jaisingh,
Statistical Applications in Quality and Productivity Management Sections 1 – 8. Skip 5.
To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 17-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ Chapter 17.
IES 303 Engineering Management & Cost Analysis | Dr. Karndee Prichanont, SIIT 1 IES 303 Chapter 5: Process Performance and Quality Objectives: Understand.
© 2004 Prentice-Hall, Inc. Basic Business Statistics (9 th Edition) Chapter 18 Statistical Applications in Quality and Productivity Management Chap 18-1.
Statistical Process Control Chapters A B C D E F G H.
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 17-1 Business Statistics: A Decision-Making Approach 6 th Edition Chapter.
© 2003 Prentice-Hall, Inc.Chap 13-1 Business Statistics: A First Course (3 rd Edition) Chapter 13 Statistical Applications in Quality and Productivity.
Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc. Chapter 14 Statistical Applications in Quality Management Business Statistics: A First.
© 2002 Prentice-Hall, Inc.Chap 15-1 Statistics for Managers Using Microsoft Excel 3 rd Edition Chapter 15 Statistical Applications in Quality and Productivity.
© 2006 Prentice Hall, Inc.S6 – 1 Operations Management Supplement 6 – Statistical Process Control © 2006 Prentice Hall, Inc. PowerPoint presentation to.
Statistical Process Control (SPC)
Chapter 7 Statistical Quality Control. Quality Control Approaches l Statistical process control (SPC) Monitors the production process to prevent poor.
© 2003 Prentice-Hall, Inc. Quantitative Analysis Chapter 17 Statistical Quality Control Chap 17-1.
Managing Quality CHAPTER SIX McGraw-Hill/Irwin Statistical Process control.
Business Statistics, A First Course (4e) © 2006 Prentice-Hall, Inc. Chap 14-1 Chapter 14 Statistical Applications in Quality and Productivity Management.
Copyright 2009, John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Statistical Process Control Operations Management - 5 th Edition.
Statistical Process Control. A process can be described as a transformation of set of inputs into desired outputs. Inputs PROCESSOutputs What is a process?
Statistical Process Control Chapter 4. Chapter Outline Foundations of quality control Product launch and quality control activities Quality measures and.
Statistical Process Control. Overview Variation Control charts – R charts – X-bar charts – P charts.
1 Slides used in class may be different from slides in student pack Technical Note 8 Process Capability and Statistical Quality Control  Process Variation.
Inspection- “back-end quality control” BUT, Start by designing quality into the front end of the process- the design QFD (Quality Function Deployment)
Quality Control  Statistical Process Control (SPC)
© 1998 Prentice-Hall, Inc. Statistics for Managers Using Microsoft Excel, 1/e Statistics for Managers Using Microsoft Excel Statistical Applications.
MOS 3330 Operations Management Professor Burjaw Fall/Winter
Chapter 16 Introduction to Quality ©. Some Benefits of Utilizing Statistical Quality Methods Increased Productivity Increased Sales Increased Profits.
Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc. Chap 18-1 Chapter 18 Statistical Applications in Quality and Productivity Management Basic Business.
McGraw-Hill/Irwin  The McGraw-Hill Companies, Inc. 2007, All Rights Reserved Quality Control and Improvement Chapter 9.
Yandell – Econ 216 Chapter 17 Statistical Applications in Quality Management Chap 17-1.
POPULATION VERSUS SAMPLE
Statistical Process Control (SPC)
Statistics for Managers Using Microsoft Excel 3rd Edition
Chapter 18 Statistical Applications in Quality Management
Statistical Process Control
Statistical Process Control
Statistical Quality Control
Presentation transcript:

Chapter Topics Total Quality Management (TQM) Theory of Process Management (Deming’s Fourteen points) The Theory of Control Charts Common Cause Variation Vs Special Cause Variation Control Charts for the Proportion of Nonconforming Items Process Variability Control charts for the Mean and the Range

Control Charts Monitors Variation in Data –Exhibits Trend - Make Correction Before Process is Out of control Show When Changes in Data Are Due to –Special or Assignable Causes Fluctuations Not Inherent to a Process Represents Problems to be Corrected Data Outside Control Limits or Trend –Chance or Common Causes Inherent Random Variations

Graph of sample data plotted over time Assignable Cause Variation Random Variation Process Average  Mean Process Control Chart UCL LCL

Control Limits UCL = Process Average + 3 Standard Deviations LCL = Process Average - 3 Standard Deviations Process Average UCL LCL X + 3  - 3  TIME

Types of Error First Type: Belief that Observed Value Represents Special Cause When in Fact it is Due to Common Cause Second Type: Treating Special Cause Variation as if it is Common Cause Variation

Comparing Control Chart Patterns XXX Common Cause Variation: No Points Outside Control Limit Special Cause Variation: 2 Points Outside Control Limit Downward Pattern: No Points Outside Control Limit

When to Take Corrective Action 1. Eight Consecutive Points Above the Center Line (or Eight Below) 2. Eight Consecutive Points that are Increasing (Decreasing) Corrective Action should be Taken When Observing Points Outside the Control Limits or When a Trend Has Been Detected:

p Chart Control Chart for Proportions Shows Proportion of Nonconforming Items – e.g., Count # defective chairs & divide by total chairs inspected Chair is either defective or not defective Used With Equal or Unequal Sample Sizes Over Time – Unequal sizes should not differ by more than ± 25% from average sample size

p Chart Control Limits Average Group Size Average Proportion of Nonconforming Items # Defective Items in Sample i Size of Sample i # of Samples LCL p =UCL p = p _

p Chart Example You’re manager of a 500-room hotel. You want to achieve the highest level of service. For 7 days, you collect data on the readiness of 200 rooms. Is the process in control?

p Chart Hotel Data # Not Day# RoomsReadyProportion

n n k p X n p i i k i i k i i k              or,.0268 p Chart Control Limits Solution  ( ) ( ) _

p Chart Control Chart Solution UCL LCL P Day Mean p _

Variable Control Charts: R Chart Monitors Variability in Process Characteristic of interest is measured on interval or ratio scale. Shows Sample Range Over Time Difference between smallest & largest values in inspection sample e.g., Amount of time required for luggage to be delivered to hotel room

UCLDR LCLD R R R k R R i i k      R Chart Control Limits Sample Range at Time i # Samples From Table

R Chart Example You’re manager of a 500-room hotel. You want to analyze the time it takes to deliver luggage to the room. For 7 days, you collect data on 5 deliveries per day. Is the process in control?

R Chart & Mean Chart Hotel Data SampleSample DayAverageRange

R R k UCLD R LCLD R i i k R R         R Chart Control Limits Solution From Table E.9 (n = 5)   _

R Chart Control Chart Solution UCL Minutes Day LCL R _

Mean Chart (The X Chart) Shows Sample Means Over Time – Compute mean of inspection sample over time – e.g., Average luggage delivery time in hotel Monitors Process Average

UCL X A R LCLXA R X X k R R k X X i i k i i k        and Mean Chart Sample Range at Time i # Samples Sample Mean at Time i Computed From Table _ _ _ _ _ _ _ _ _ __ _

Mean Chart Example You’re manager of a 500- room hotel. You want to analyze the time it takes to deliver luggage to the room. For 7 days, you collect data on 5 deliveries per day. Is the process in control?

R Chart & Mean Chart Hotel Data SampleSample DayAverageRange

X X R X R R X k R k UCL A LCLA i i k i i k X X                Mean Chart Control Limits Solution From Table E.9 (n = 5)   _ _ _ _ __ _ __ _ _ _

Mean Chart Control Chart Solution UCL LCL Minutes Day X _ _

Six sigma SIGMAPPM (best case) PPM (worst case) MisspellingsExamples 1 sigma317,400697, words per pageNon-competitive 2 sigma45,600308,73325 words per pageIRS Tax Advice (phone-in) 3 sigma2,70066, words per pageDoctors prescription writing (9,000 ppm) 4 sigma646,2001 word per 30 pages (1 per chapter) Industry average 5 sigma word in a set of encyclopedias Airline baggage handling (3,000 ppm) 6 sigma in all of the books in a small library World class