McGraw-Hill/Irwin  The McGraw-Hill Companies, Inc. 2007, All Rights Reserved Quality Control and Improvement Chapter 9

9-2 Chapter 9 Outline Design of Quality Control Systems Process Quality Control Attribute Control Variables Control Using Control Charts Continuous Improvement Six Sigma Quality Control in Industry

9-3 Design of Quality Control Systems Break down production process into subprocesses and “internal customers.” Identify “Critical points” where inspection or measurement should take place Four steps in designing QC systems.

9-4 Steps in Designing QC Systems  Identify critical points Incoming materials & servicesIncoming materials & services Work in processWork in process Finished product or serviceFinished product or service  Decide on the type of measurement variablevariable attributeattribute  Decide on the amount of inspection to be used.  Decide who should do the inspection

Types Of Measurement Attribute measurement –Product characteristic evaluated with a discrete choice: Good/bad, yes/no Variable measurement –Product characteristic that can be measured on a continuous scale: Length, size, weight, height, time, velocity

9-6 When the Inspector Finds a Defect… 1. Containment: Keep the defective items from getting to the customer 2. Correction: Find the cause of the defect and correct it. 3. Prevention: Prevent the cause from happening again. 4. Continuously improve the system.

9-7 When the Inspector Finds a Defect e.g. Strap on backpack comes loose  Containment: pull the bad backpacks from the line.  Correction: sewing machine misaligned; fix it.  Prevention: why was it misaligned? Find out and change system to prevent it happening again.  Continuously monitor and improve system.

9-8 Process Quality Control Basic assumptions (tenets) of Process Quality Control: –Every process has random variation in it. –Production processes are not usually found in a state of control. “State of Control”; what does it mean? –Unnecessary variation is eliminated. –Remaining variation is because of random causes.

9-9 Process Quality Control Assignable (special) causes –Can be identified and corrected Common causes –Occur randomly –Cannot be changed unless process is redesigned

9-10 Process Control Chart (Figure 9.1) x y Time

9-11 Quality Measurement UCL LCL CL Sample Quality Control Chart (Figure 9.2) Stop the process; look for assignable cause

9-12 Attributes & Variables Attributes are counts, such as the number (or proportion) of defects in a sample. Variables are measures (mean & range or standard deviation) of critical characteristics in a sample.

9-13 Formulas for SPC (3 Sigma) p-Chart x-Bar Chart R-Chart

9-14 Issues in Using Control Charts Sample Size –large enough to detect defectives –defect rate has time dimension How often to sample? –Depends upon cost Control limits vs. product specifications –Is the process capable of producing to specs? –Are the specifications appropriate?

9-15 Continuous Improvement Aim of continuous improvement is to reduce the variability of the product or process Techniques for continuous improvement –Pareto analysis –Cause-and-effect (fish-bone) diagrams –Process capability charts

9-16 Pareto Analysis Note: 40 percent of the items cause 78.6 percent of the defects

9-17 Pareto Diagram (Figure 9.3)

9-18 Cause-and-effect (Fish-bone, Ishikawa) diagram (Figure 9.4)

9-19 Process Capability Index Examples (Figure 9.5) frequency process measure

9-20 Computation of C pk (Figure 9.6) frequency process measure

9-21 Six-Sigma Quality Pioneered by Motorola in 1988 (Juran claims credit for the idea). 3.4 defects per million Sample size rules become unusable Most process are 4 sigma, e.g. payroll, prescriptions, baggage handling, journal vouchers, restaurant bills. Airline fatalities are 6.4 sigma IRS tax advice is less than 2 sigma Criticism: accepts 3.4 defects/million. Is not zero defects.

9-22 Six Sigma Quality Process Improvement steps of Six Sigma (DMAIC): 1.Define 2.Measure 3.Analyze 4.Improve 5.Control

9-23 Quality Control in Industry 75% use process control charts. More use of variable (x-bar and R) charts than attribute (p) charts. “The Seven Tools of Quality Control” (see Figure 9.7) Quality control in the service industry (SERVQUAL)

9-24 Summary Design of Quality Control Systems Process Quality Control Attribute Control Variables Control Using Control Charts Continuous Improvement Six Sigma Quality Control in Industry

9-25 End of Chapter Nine