Course Title Production and Operations Management Course Code

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

Chapter 6: Managing Quality 6 -2

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

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

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

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 6 -6

Determinants of Service Quality Reliability Consistency of performance and dependability Responsiveness Willingness or readiness of employees Competence Required skills and knowledge Access Approachability and ease of contact Courtesy Politeness, respect, consideration, friendliness Communication Keeping customers informed Credibility Trustworthiness, believability, honesty Security Freedom from danger, risk, or doubt Understanding/ knowing the customer Understand the customer’s needs Tangibles Physical evidence of the service Table 6. 5 6 -7

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

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

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

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

Chapter 6 S: Statistical Process Control S 6 - 12

Outline u Statistical Process Control (SPC) u Control Charts for Variables u The Central Limit Theorem u Setting Mean Chart Limits (x-Charts) u Setting Range Chart Limits (R-Charts) u Using Mean and Range Charts u Control Charts for Attributes u Managerial Issues and Control Charts S 6 - 13

Outline – Continued u Process Capability Ratio (Cp) u Process Capability Index (Cpk ) u Acceptance Sampling u Operating Characteristic Curve u Average Outgoing Quality S 6 - 14

Statistical Process Control The objective of a process control system is to provide a statistical signal when assignable causes of variation are present S 6 - 15

Statistical Process Control (SPC) u Variability is inherent in every process u Natural or common causes u Special or assignable causes u Provides a statistical signal when assignable causes are present u Detect and eliminate assignable causes of variation S 6 - 16

Natural Variations u Also called common causes u Affect virtually all production processes u Expected amount of variation u Output measures follow a probability distribution u For any distribution there is a measure of central tendency and dispersion u If the distribution of outputs falls within acceptable limits, the process is said to be “in control” S 6 - 17

Assignable Variations u Also called special causes of variation u Generally this is some change in the process u Variations that can be traced to a specific reason u The objective is to discover when assignable causes are present u Eliminate the bad causes u Incorporate the good causes S 6 - 18

Samples To measure the process, we take samples and analyze the sample statistics following these steps Figure S 6. 1 Frequency (a) Samples of the product, say five boxes of cereal taken off the filling machine line, vary from each other in weight Each of these represents one sample of five boxes of cereal # # # # # # # Weight S 6 - 19

Samples To measure the process, we take samples and analyze the sample statistics following these steps Figure S 6. 1 Frequency (b) After enough samples are taken from a stable process, they form a pattern called a distribution The solid line represents the distribution Weight S 6 - 20

Samples To measure the process, we take samples and analyze the sample statistics following these steps Frequency (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 Figure S 6. 1 Central tendency Weight Variation Weight Shape Weight S 6 - 21

Samples (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 Frequency To measure the process, we take samples and analyze the sample statistics following these steps Prediction e m i T Weight Figure S 6. 1 S 6 - 22

Samples To measure the process, we take samples and analyze the sample statistics following these steps Prediction Frequency (e) If assignable causes are present, the process output is not stable over time and is not predicable ? ? ? ? ? e m i T Weight Figure S 6. 1 S 6 - 23

Control Charts Constructed from historical data, the purpose of control charts is to help distinguish between natural variations and variations due to assignable causes S 6 - 24

Process Control Frequency Lower control limit (a) In statistical control and capable of producing within control limits Upper control limit (b) In statistical control but not capable of producing within control limits (c) Out of control Size (weight, length, speed, etc. ) Figure S 6. 2 S 6 - 25