Business Decision Making ADMN2167 Quality

1. Business Decision Making ADMN2167Quality Professor: Bob Carpenter

2. A. Introduction Quality is the ability of a product or service to consistently meet or exceed customer expectations.

3. Quality: The Basics • Dimensions of Quality • Determinants of Quality • Consequences of Poor Quality • Costs of Quality

4. Dimensions of Quality • Product quality • Performance, Aesthetics, Special Features, Safety, Reliability, Durability, Perceived quality, Service after Sale • Service quality • Tangibles, Convenience, Reliability, Responsiveness, Time, Assurance, Courtesy

5. Group Exercise • Consider a related product and service of your choice. • E.g. a guitar and music lessons • Construct a chart of the dimensions of quality and give examples.

6. Examples of Quality Dimensions, Products

7. C1. Examples of Quality Dimensions, Services

8. Examples of Quality Dimensions, Products

9. Examples of Quality Dimensions, Services

10. Determinants of Quality • Design • Quality of Design: Characteristics designers specify for a product or service • Conformity • Quality of Conformance: The degree to which goods or services conform to the specifications of the designers • Ease of use • Good instructions and labels • Service after delivery • Recall, repair, replacement, refund

11. The Consequences of Poor Quality • Loss of business • Liability • Productivity • Costs A recent study showed that, while a satisfied customer will tell a few people about his or her experience, a dissatisfied person will tell an average of 19 others

12. Costs of Quality • Internal Failure Costs • External Failure Costs • Appraisal Costs • Prevention Costs

13. Costs of Quality • Internal Failure Costs • Costs incurred to fix problems that are detected before the product/service is delivered to the customer. • External Failure Costs • All costs incurred to fix problems that are detected after the product/service is delivered to the customer.

14. Costs of Quality • Appraisal Costs • All product and/or service inspection costs. • Prevention Costs • All TQ training, TQ planning, customer assessment, process control, and quality improvement costs to prevent defects from occurring

15. Quality Control

16. Introduction • Inspection • Statistical process Control • Process Capability • Design of Experiments

17. A. Introduction • What does the term quality control mean? • Quality Control is an activity that evaluates quality characteristics relative to a standard, and takes corrective action when they do not meet standards • How is quality control accomplished? • by monitoring and inspecting the product during process

18. Inspection before/after production Corrective action during production Quality built into the process Acceptance sampling Process control Continuous improvement The least progressive The most progressive A. Phases of Quality Assurance

19. Inputs Transformation Outputs Acceptance sampling Acceptance sampling Process control B. Inspection Inspection: appraisal of goods or services against standards • How Much/How Often • Where/When • Centralized vs. On-site

20. Total Cost Cost Cost of inspection Cost of passing defectives Optimal Amount of Inspection B. How Much to Inspect and How Often?

21. B. Where to Inspect in the Process • Raw materials and purchased parts • Finished products • Before a costly operation • Before an irreversible process • Before a covering process

22. B. Examples of Inspection Points

23. C. Statistical Process Control Statistical Process Control: Statistical evaluation of the output of a process during production • The Quality Control Steps • Type of Variations • Control Charts • Designing Control Charts • Individual Unit and Moving Range Charts • Control Charts for Attributes • Managerial Considerations

24. C1. The Quality Control Steps • Define the quality characteristics to monitor • Measure the characteristics • Compare to a standard and evaluate • Take corrective action if necessary • Evaluate corrective action

25. Samplingdistribution Processdistribution Mean C2. Types of Variations • Random variation: Natural variations in the output of process, created by countless minor factors • Assignable variation: A variation whose source can be identified

26. Standard deviation     Mean 95.44% 99.74% C2. Normal Distribution

27. C3. Control Charts • Control Chart: A time ordered plot of sample statistics, used to distinguish between random and non random variability • Control Limits: The dividing lines between random and nonrandom deviations from the mean of the sampling distribution • Type I error: concluding that a process has changed when it has not • Type II error: concluding a process is in control when it is actually not

28. /2 /2 Mean LCL UCL Probabilityof Type I error C3. Type I Error

29. Abnormal variationdue to assignable sources Out ofcontrol UCL Mean Normal variationdue to chance LCL Abnormal variationdue to assignable sources 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Sample number C3. Control Chart

30. UCL LCL 1 2 3 4 Sample number C3. Observations from Sample Distribution

31. C4. Designing Control Charts • Determine a sample size • Obtain 20 to 25 samples • Establish preliminary control limits and graph them • Plot the sample statistic values on a control chart, and note whether any points fall outside control limits (CL) • If no points outside CL assume there is no assignable cause. If points are outside CL investigate and correct • Operators use control chart by recording the value of sample statistic which is periodically taken

32. (process mean is shifting upward) Sampling Distribution UCL Detects shift x-Chart LCL UCL Does notdetect shift R-chart LCL C5. Mean and Range Charts

33. Sampling Distribution (process variability is increasing) UCL Does notreveal increase x-Chart LCL UCL R-chart Reveals increase LCL C5. Mean and Range Charts

34. C6. Control Chart for Attributes • Use of p-Charts • When observations can be placed into two categories: Good or bad, Pass or fail, Operate or don’t operate • When the data consists of multiple samples of several observations each • Use of c-Charts • Use only when the number of occurrences per unit of measure can be counted; non-occurrences cannot be counted: scratches, chips, dents, or errors per item, cracks or faults per unit of distance, breaks or tears per unit of area, bacteria or pollutants per unit of volume, calls, complaints, failures per unit of time

35. C6. Managerial Considerations • Decisions • At what points in the process to use control charts. Focus on those aspects that: • Have a tendency to go out of control • Are critical to the successful production • What type of control chart to use • The manager must weight the time and cost of sampling against the information provided

36. D. Process Capability • Specifications • A range of acceptable values established by engineering design or customer requirements • Control limits • Statistical limits • Process variability • Natural or inherent variability in a process • Process capability • The inherent variability of process output relative to the variation allowed by the design specification

37. LowerSpecification UpperSpecification Process variability matches specifications LowerSpecification UpperSpecification Process variability well within specifications LowerSpecification UpperSpecification Process variability exceeds specifications D. Capability Analysis

38. D. Process Capability Ratio