Chapter 6: Quality Management © Holmes Miller 1999

Quality Specifications Design quality: Inherent value of the product in the marketplace Dimensions include: Performance Features Reliability/Durability Serviceability Aesthetics Perceived Quality. Conformance quality: Degree to which the product or service design specifications are met 7

Importance of Quality Costs & market share Market Gains Reputation Volume Price Improved Increased Quality Profits Lower Costs Productivity Rework/Scrap Warranty

The Concept of Consistency: Who is the Better Target Shooter? Not just the mean is important, but also the variance Need to look at the distribution function

Funnel Experiment (Deming) Tampering with a stable system only increases the production of faulty items and mistakes. Tampering is taking action based on the belief that a common cause is a special cause. Improvement of a stable system nearly always means reduction of variation. One necessary qualification of anyone in management is -- -- stop asking people to explain ups and downs that come from random variation.

Basic Forms of Variation Example: A poorly trained employee that creates variation in finished product output. Assignable variation is caused by factors that can be clearly identified and possibly managed Common variation is inherent in the production process Example: A molding process that always leaves “burrs” or flaws on a molded item. 3

Two Types of Causes for Variation Common Cause Variation (low level) Common Cause Variation (high level) Assignable Cause Variation Need to measure and reduce common cause variation Identify assignable cause variation as soon as possible

Taguchi’s View of Variation Traditional view is that quality within the LS and US is good and that the cost of quality outside this range is constant, where Taguchi views costs as increasing as variability increases, so seek to achieve zero defects and that will truly minimize quality costs. High Incremental Cost of Variability High Zero Lower Spec Target Upper Taguchi’s View Incremental Cost of Variability Zero Lower Spec Target Spec Upper Spec Traditional View 30

Internal Failure Costs Costs of Quality Appraisal Costs External Failure Costs Prevention Costs Costs of Quality Internal Failure Costs

Six Sigma Quality A philosophy and set of methods companies use to eliminate defects in their products and processes Seeks to reduce variation in the processes that lead to product defects The name, “six sigma” refers to the variation that exists within plus or minus six standard deviations of the process outputs

The Statistical Meaning of Six Sigma Process capability measure Lower Specification Limit (LSL) Upper Specification Limit (USL) Process A (with st. dev sA) x Cp P{defect} ppm 1 0.33 0.317 317,000 2 0.67 0.0455 45,500 3 1.00 0.0027 2,700 4 1.33 0.0001 63 5 1.67 0.0000006 0.6 6 2.00 2x10-9 0.00 X-3sA X-2sA X-1sA X X+1sA X+2s X+3sA 3 Process B (with st. dev sB) X-6sB X X+6sB Don’t confuse control limits with specification limits: a process can be in control, yet be incapable of meeting customer specs

Six Sigma Quality (Continued) Six Sigma allows managers to readily describe process performance using a common metric: Defects Per Million Opportunities (DPMO)

Six Sigma Quality (Continued) Example of Defects Per Million Opportunities (DPMO) calculation. Suppose we observe 200 letters delivered incorrectly to the wrong addresses in a small city during a single day when a total of 200,000 letters were delivered. What is the DPMO in this situation? So, for every one million letters delivered this city’s postal managers can expect to have 1,000 letters incorrectly sent to the wrong address. Cost of Quality: What might that DPMO mean in terms of over-time employment to correct the errors? Other costs?

Six Sigma Quality: DMAIC Cycle Define, Measure, Analyze, Improve, and Control (DMAIC) Developed by General Electric as a means of focusing effort on quality using a methodological approach Overall focus of the methodology is to understand and achieve what the customer wants A 6-sigma program seeks to reduce the variation in the processes that lead to these defects DMAIC consists of five steps….

Six Sigma Quality: DMAIC Cycle (Continued) 1. Define (D) Customers and their priorities 2. Measure (M) Process and its performance 3. Analyze (A) Causes of defects 4. Improve (I) Remove causes of defects 5. Control (C) Maintain quality

Example to illustrate the process… We are the maker of this cereal. Consumer Reports has just published an article that shows that we frequently have less than 15 ounces of cereal in a box. Exercise: What should we do? Define -- What is the critical-to-quality characteristic? Measure -- How would we measure to evaluate the extent of the problem? Analyze -- How can we improve the capability of our cereal box filling process? Improve -- How good is good enough? Motorola’s “Six Sigma” Control -- Statistical Process Control (SPC)

Analytical Tools for Six Sigma and Continuous Improvement: Flow Chart No, Continue… Material Received from Supplier Inspect Material for Defects Defects found? Yes Can be used to find quality problems Return to Supplier for Credit 4

Analytical Tools for Six Sigma and Continuous Improvement: Run Chart Can be used to identify when equipment or processes are not behaving according to specifications 0.44 0.46 0.48 0.5 0.52 0.54 0.56 0.58 1 2 3 4 5 6 7 8 9 10 11 12 Time (Hours) Diameter

Analytical Tools for Six Sigma and Continuous Improvement: Pareto Analysis Can be used to find when 80% of the problems may be attributed to 20% of the causes 80% Frequency Design Assy. Instruct. Purch. Training 12

Analytical Tools for Six Sigma and Continuous Improvement: Checksheet Can be used to keep track of defects or used to make sure people collect data in a correct manner Monday Billing Errors Wrong Account Wrong Amount A/R Errors 16

Analytical Tools for Six Sigma and Continuous Improvement: Histogram Can be used to identify the frequency of quality defect occurrence and display quality performance Number of Lots 1 2 3 4 Defects in lot Data Ranges 14

Analytical Tools: Cause and Effect Diagrams (Fishbone Diagrams) Materials Machines Specifications / information People Vise position set incorrectly Machine tool coordinates set incorrectly Vice position shifted during production Part clamping surfaces corrupted Part incorrectly positioned in clamp Clamping force too high or too low Cutting tool worn Dimensions incorrectly specified in drawing Dimension incorrectly coded In machine tool program Material too soft Extrusion stock undersized Extrusion die undersized Extrusion rate too high Extrusion temperature too high Error in measuring height Steer support height deviates from specification Can be used to systematically track backwards to find a possible cause of a quality problem (or effect) 17

Types of Statistical Sampling Attribute (Go or no-go information) Defectives refers to the acceptability of product across a range of characteristics. Defects refers to the number of defects per unit which may be higher than the number of defectives. p-chart application Variable (Continuous) Usually measured by the mean and the standard deviation. X-bar and R chart applications 6

Analytical Tools for Six Sigma and Continuous Improvement: Control Charts Can be used to monitor ongoing production process quality and quality conformance to stated standards of quality 970 980 990 1000 1010 1020 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 LCL UCL

Statistical Process Control (SPC) Charts Normal Behavior UCL Normal Behavior LCL 1 2 3 4 5 6 Samples over time UCL Possible problem, investigate LCL 1 2 3 4 5 6 Samples over time UCL Possible problem, investigate LCL 1 2 3 4 5 6 Samples over time 16

Process Capability Process limits Specification limits How do the limits relate to one another? 28

Process Capability Index, Cpk Capability Index shows how well parts being produced fit into design limit specifications. As a production process produces items small shifts in equipment or systems can cause differences in production performance from differing samples. Shifts in Process Mean 29

The Cereal Box Example We are the maker of this cereal. Consumer reports has just published an article that shows that we frequently have less than 15 ounces of cereal in a box. We would like to have 16 ounces in each box. Let’s assume that the government says that we must be within ± 5 percent of the weight advertised on the box. Upper Tolerance Limit = 16 + .05(16) = 16.8 ounces Lower Tolerance Limit = 16 – .05(16) = 15.2 ounces We go out and buy 1,000 boxes of cereal and find that they weight an average of 15.875 ounces with a standard deviation of .529 ounces.

Cereal Box Process Capability Specification or Tolerance Limits Upper Spec = 16.8 oz Lower Spec = 15.2 oz Observed Weight Mean = 15.875 oz Std Dev = .529 oz What does a Cpk of .4253 mean? This is a process that will produce a relatively high number of defects. Many companies look for a Cpk of 1.3 or better… 6-Sigma company wants 2.0!

Basic Forms of Statistical Sampling for Quality Control Acceptance Sampling is sampling to accept or reject the immediate lot of product at hand Statistical Process Control is sampling to determine if the process is within acceptable limits 3