1. 6 - 1 Course Title: Production and Operations Management Course Code: MGT 362 Course Book: Operations Management 10 th Edition. By Jay Heizer & Barry Render

2. 6 - 2 Chapter 6: Managing Quality

3. 6 - 3 Source Inspection  Also known as source control  The next step in the process is your customer  Ensure perfect product to your customer Poka-yoke is the concept of foolproof devices or techniques designed to pass only acceptable product

4. 6 - 4 Attributes Versus Variables  Attributes  Items are either good or bad, acceptable or unacceptable  Does not address degree of failure  Variables  Measures dimensions such as weight, speed, height, or strength  Falls within an acceptable range  Use different statistical techniques

5. 6 - 5 TQM In Services  Service quality is more difficult to measure than the quality of goods  Service quality perceptions depend on  Intangible differences between products  Intangible expectations customers have of those products

6. 6 - 6 Service Quality The Operations Manager must recognize: 1.The service process is important 2.The service is judged against the customer’s expectations 3.Exceptions will occur

7. 6 - 7 Determinants of Service Quality ReliabilityConsistency of performance and dependability ResponsivenessWillingness or readiness of employees CompetenceRequired skills and knowledge AccessApproachability and ease of contact CourtesyPoliteness, respect, consideration, friendliness CommunicationKeeping customers informed CredibilityTrustworthiness, believability, honesty SecurityFreedom from danger, risk, or doubt Understanding/ knowing the customer Understand the customer’s needs TangiblesPhysical evidence of the service Table 6.5

8. 6 - 8 Service Recovery Strategy  Managers should have a plan for when services fail  Marriott’s LEARN routine  Listen  Empathize  Apologize  React  Notify

9. 6 - 9 Summary  Total Quality Management  Continuous Improvement  Six Sigma  Employee Empowerment  Benchmarking  Just-in-Time (JIT)  Taguchi Concepts  Knowledge of TQM Tools

10. 6 - 10 Summary  Tools of TQM  Check Sheets  Scatter Diagrams  Cause-and-Effect Diagrams  Pareto Charts  Flowcharts  Histograms  Statistical Process Control (SPC)

11. 6 - 11 Summary  The Role of Inspection  When and Where to Inspect  Source Inspection  Service Industry Inspection  Inspection of Attributes versus Variables  TQM in Services

12. S6 - 12 Chapter 6S: Statistical Process Control

13. S6 - 13 Outline  Statistical Process Control (SPC)  Control Charts for Variables  The Central Limit Theorem  Setting Mean Chart Limits (x-Charts)  Setting Range Chart Limits (R-Charts)  Using Mean and Range Charts  Control Charts for Attributes  Managerial Issues and Control Charts

14. S6 - 14 Outline – Continued  Process Capability  Process Capability Ratio (C p )  Process Capability Index (C pk )  Acceptance Sampling  Operating Characteristic Curve  Average Outgoing Quality

15. S6 - 15 Statistical Process Control The objective of a process control system is to provide a statistical signal when assignable causes of variation are present

16. S6 - 16  Variability is inherent in every process  Natural or common causes  Special or assignable causes  Provides a statistical signal when assignable causes are present  Detect and eliminate assignable causes of variation Statistical Process Control (SPC)

17. S6 - 17 Natural Variations  Also called common causes  Affect virtually all production processes  Expected amount of variation  Output measures follow a probability distribution  For any distribution there is a measure of central tendency and dispersion  If the distribution of outputs falls within acceptable limits, the process is said to be “in control”

18. S6 - 18 Assignable Variations  Also called special causes of variation  Generally this is some change in the process  Variations that can be traced to a specific reason  The objective is to discover when assignable causes are present  Eliminate the bad causes  Incorporate the good causes

19. S6 - 19 Samples To measure the process, we take samples and analyze the sample statistics following these steps (a)Samples of the product, say five boxes of cereal taken off the filling machine line, vary from each other in weight Frequency Weight # ## # ## ## # ### #### ######### # Each of these represents one sample of five boxes of cereal Figure S6.1

20. S6 - 20 Samples To measure the process, we take samples and analyze the sample statistics following these steps (b)After enough samples are taken from a stable process, they form a pattern called a distribution The solid line represents the distribution Frequency Weight Figure S6.1

21. S6 - 21 Samples To measure the process, we take samples and analyze the sample statistics following these steps (c)There are many types of distributions, including the normal (bell-shaped) distribution, but distributions do differ in terms of central tendency (mean), standard deviation or variance, and shape Weight Central tendency Weight Variation Weight Shape Frequency Figure S6.1

22. S6 - 22 Samples To measure the process, we take samples and analyze the sample statistics following these steps (d)If only natural causes of variation are present, the output of a process forms a distribution that is stable over time and is predictable Weight Time Frequency Prediction Figure S6.1

23. S6 - 23 Samples To measure the process, we take samples and analyze the sample statistics following these steps (e)If assignable causes are present, the process output is not stable over time and is not predicable Weight Time Frequency Prediction ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? Figure S6.1

24. S6 - 24 Control Charts Constructed from historical data, the purpose of control charts is to help distinguish between natural variations and variations due to assignable causes

25. S6 - 25 Process Control Figure S6.2 Frequency (weight, length, speed, etc.) Size Lower control limit Upper control limit (a) In statistical control and capable of producing within control limits (b) In statistical control but not capable of producing within control limits (c) Out of control