Stevenson 9 Management of Quality
Learning Objectives § § § § Define the term quality. Explain why quality is important and the consequences of poor quality. Identify the determinants of quality. Describe the costs associated with quality. Describe TQM. Describe Lean Production. Give an overview of problem solving. Describe and use various quality tools. 9 -2
Key Contributors to Quality Management 9 -3
Quality Management What does the term quality mean? § Quality is the ability of a product or service to consistently meet or exceed customer expectations. 9 -4
Quality Assurance vs. Strategic Approach § Quality Assurance § Emphasis on finding and correcting defects before reaching market § Strategic Approach § Proactive, focusing on preventing mistakes from occurring § Greater emphasis on customer satisfaction 9 -5
Dimensions of Quality § Performance - main characteristics of the product/service § Aesthetics - appearance, feel, smell, taste § Special Features - extra characteristics § Conformance - how well product/service conforms to customer’s expectations § Reliability - consistency of performance 9 -6
Dimensions of Quality (Cont’d) § Durability - useful life of the product/service § Perceived Quality - indirect evaluation of quality (e. g. reputation) § Serviceability - service after sale 9 -7
Examples of Quality Dimensions 9 -8
Examples of Quality Dimensions (Cont’d) 9 -9
Service Quality § § § § Convenience Reliability Responsiveness Time Assurance Courtesy Tangibles 9 -10
Examples of Service Quality Dimension Examples 1. Convenience Was the service center conveniently located? 2. Reliability Was the problem fixed? 3. Responsiveness Were customer service personnel willing and able to answer questions? 4. Time How long did the customer wait? 5. Assurance Did the customer service personnel seem knowledgeable about the repair? 6. Courtesy Were customer service personnel and the cashier friendly and courteous? 7. Tangibles Were the facilities clean, personnel neat? 9 -11
Challenges with Service Quality § Customer expectations often change § Different customers have different expectations § Each customer contact is a “moment of truth” § Customer participation can affect perception of quality § “Fail-safe” must be designed into the system (for customer self-service) 9 -12
Determinants of Quality § Quality of design § Intention of designers to include or exclude features in a product or service § Quality of conformance § The degree to which goods or services conform to the intent of the designers 9 -13
The Consequences of Poor Quality § § Loss of business Liability Productivity Costs 9 -14
Responsibility for Quality § § § § Top management Design Procurement Production/operations Quality assurance Packaging and shipping Marketing and sales Customer service § IDEALLY, EVERYONE IS RESPONSIBLE FOR QUALITY 9 -15
Costs of Quality § Failure Costs - costs incurred by defective parts/products or faulty services. § 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. 9 -16
Costs of Quality (continued) § Appraisal Costs § Costs of activities designed to ensure quality or uncover defects § Prevention Costs § All TQ training, TQ planning, customer assessment, process control, and quality improvement costs to prevent defects from occurring 9 -17
Ethics and Quality § Substandard work § § § Defective products Substandard service Poor designs Shoddy workmanship Substandard parts and materials Having knowledge of this and failing to correct and report it in a timely manner is unethical. 9 -18
Quality Certification § ISO 9000 § Set of international standards on quality management and quality assurance, critical to international business § ISO 14000 § A set of international standards for assessing a company’s environmental performance 9 -19
ISO 9000 Quality Management Principles § § § § Customer focus Leadership People involvement Process approach A systems approach to management Continual improvement Factual approach to decision making Mutually beneficial supplier relationships 9 -20
ISO 14000 § Management systems § Systems development and integration of environmental responsibilities into business planning § Operations § Consumption of natural resources and energy § Environmental systems § Measuring, assessing and managing emissions, effluents, and other waste 9 -21
Total Quality Management A philosophy that involves everyone in an organization in a continual effort to improve quality and achieve customer satisfaction. T Q M 9 -22
The TQM Approach 1. Find out what the customer wants 2. Design a product or service that meets or exceeds customer wants 3. Design processes that facilitates doing the job right the first time 4. Keep track of results 5. Extend these concepts to suppliers 9 -23
Elements of TQM 1. Continual improvement 2. Competitive benchmarking 3. Employee empowerment 4. Team approach 5. Decisions based on facts 6. Knowledge of tools 7. Supplier quality 8. Champion 9. Quality at the source 10. Suppliers 9 -24
Continuous Improvement § Philosophy that seeks to make neverending improvements to the process of converting inputs into outputs. § Kaizen: Japanese word for continuous improvement. 9 -25
Quality at the Source The philosophy of making each worker responsible for the quality of his or her work. 9 -26
Six Sigma § Statistically § Having no more than 3. 4 defects per million § Conceptually § Program designed to reduce defects § Requires the use of certain tools and techniques Six sigma: A business process for improving quality, reducing costs, and increasing customer satisfaction. 9 -27
Six Sigma Programs § Six Sigma programs § Improve quality § Save time § Cut costs § Employed in § § § Design Production Service Inventory management Delivery 9 -28
Six Sigma Management § § Providing strong leadership Defining performance metrics Selecting projects likely to succeed Selecting and training appropriate people 9 -29
Six Sigma Technical § § Improving process performance Reducing variation Utilizing statistical models Designing a structured improvement strategy 9 -30
Six Sigma Team § § § Top management Program champions Master “black belts” “Black belts” “Green belts” 9 -31
Six Sigma Process § § § Define Measure Analyze Improve Control DMAIC 9 -32
Obstacles to Implementing TQM § Lack of: § § § § Company-wide definition of quality Strategic plan for change Customer focus Real employee empowerment Strong motivation Time to devote to quality initiatives Leadership 9 -33
Obstacles to Implementing TQM § § Poor inter-organizational communication View of quality as a “quick fix” Emphasis on short-term financial results Internal political and “turf” wars 9 -34
Basic Steps in Problem Solving 1. Define the problem and establish an improvement goal 2. Define measures and collect data 3. Analyze the problem 4. Generate potential solutions 5. Choose a solution 6. Implement the solution 7. Monitor the solution to see if it accomplishes the goal 9 -35
The PDSA Cycle Plan Act Do Study 9 -36
Process Improvement § Process Improvement: A systematic approach to improving a process § Process mapping § Analyze the process § Redesign the process 9 -37
The Process Improvement Cycle Select a process Document Study/document Evaluate Seek ways to Improve it Implement the Improved process Design an Improved process 9 -38
Basic Quality Tools § § § § Flowcharts Check sheets Histograms Pareto Charts Scatter diagrams Control charts Cause-and-effect diagrams Run charts 9 -39
Check Sheet Billing Errors Monday Wrong Account Wrong Amount A/R Errors Wrong Account Wrong Amount 9 -40
80% of the problems may be attributed to 20% of the causes. Number of defects Pareto Analysis Off Smeared Missing Loose Other center print label 9 -41
Control Chart 1020 UCL 1010 1000 990 LCL 980 970 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 9 -42
Cause-and-Effect Diagram Methods Cause Environment Materials Cause Cause People Cause Effect Cause Equipment 9 -43
Diameter Run Chart Time (Hours) 9 -44
Tracking Improvements UCL LCL Process centered Process not centered and stable and not stable UCL LCL Additional improvements made to the process 9 -45
Methods for Generating Ideas § Brainstorming § Quality circles § Interviewing § Benchmarking 9 -46
Benchmarking Process § Identify a critical process that needs improving § Identify an organization that excels in this process § Contact that organization § Analyze the data § Improve the critical process 9 -47
Lean Production § “A systematic approach to identifying and eliminating waste(non-value-added activities) through continuous improvement by flowing the product at the pull of the customer in pursuit of perfection. ” 9 -48
Basic Elements of Lean 9 -49
Waste in Operations 9 -50
Waste in Operations 9 -51
Pull System Basics § Material is pulled through the system when needed § Reversal of traditional push system where material is pushed according to a schedule § Forces cooperation § Prevent over and underproduction § While push systems rely on a predetermined schedule, pull systems rely on customer requests 9 -52
Benefits of Lean Systems § § § Reduced inventory Improved quality Lower costs Reduced space requirements Shorter lead time Increased productivity Greater flexibility Better relations with suppliers Simplified scheduling and control activities Increased capacity Better use of human resources More product variety 9 -53
Stevenson 10 Quality Control
Learning Objectives § § § List and briefly explain the elements of the control process. Explain how control charts are used to monitor a process, and the concepts that underlie their use. Use and interpret control charts. Use run tests to check for nonrandomness in process output. Assess process capability. 10 -55
Phases of Quality Assurance Inspection of lots before/after production Acceptance sampling The least progressive Inspection and corrective action during production Process control Quality built into the process Continuous improvement The most progressive 10 -56
Inspection § How Much/How Often § Where/When § Centralized vs. On-site Inputs Acceptance sampling Transformation Process control Outputs Acceptance sampling 10 -57
Cost Inspection Costs Total Cost of inspection Cost of passing defectives Optimal Amount of Inspection 10 -58
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 (e. g. , painting/final assembly) 10 -59
Examples of Inspection Points 10 -60
Statistical Control § Statistical Process Control: Statistical evaluation of the output of a process during production § Quality of Conformance: A product or service conforms to specifications 10 -61
Control Chart § Purpose: to monitor process output to see if it is random § A time ordered plot representative sample statistics obtained from an on going process (e. g. sample means) § Upper and lower control limits define the range of acceptable variation 10 -62
Control Chart Abnormal variation due to assignable sources Out of control UCL Mean Normal variation due to chance LCL Abnormal variation due to assignable sources 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Sample number 10 -63
Statistical Process Control § The essence of statistical process control is to assure that the output of a process is random so that future output will be random. 10 -64
Statistical Process Control § The Control Process § § § Define Measure Compare Evaluate Correct Monitor results 10 -65
Statistical Process Control § Variations and Control § § Random variation: Natural variations in the output of a process, created by countless minor factors Assignable variation: A variation whose source can be identified 10 -66
Normal Distribution Standard deviation Mean 95. 44% 99. 74% 10 -67
Control Limits Sampling distribution Process distribution Mean Lower control limit Upper control limit 10 -68
SPC Errors § Type I error § Concluding a process is not in control when it actually is. § Type II error § Concluding a process is in control when it is not. 10 -69
Type I and Type II Errors 10 -70
Type I Error /2 Mean Probability of Type I error LCL UCL 10 -71
Observations from Sample Distribution UCL LCL 1 2 3 4 Sample number 10 -72
Control Charts for Variables generate data that are measured. § Mean control charts § Used to monitor the central tendency of a process. § X bar charts § Range control charts § Used to monitor the process dispersion § R charts 10 -73
Mean Control Chart for Variables § 10 -74
Mean Control Chart for Variables § 10 -75
Range Control Chart for Variables Monitors Process Dispersion D 3 and D 4 are found in the Table for 3 -σ Control Limits 10 -76
Table for 3 -σ Control Limits 10 -77
Mean and Range Charts (process mean is shifting upward) Sampling Distribution UCL Detects shift x-Chart LCL UCL R-chart LCL Does not detect shift 10 -78
Mean and Range Charts Sampling Distribution (process variability is increasi UCL x-Chart LCL Does not reveal increase UCL R-chart Reveals increase LCL 10 -79
Control Chart for Variables/Example A quality inspector took five samples, each with four observations (n = 4), of the length of time for glue to dry. The analyst computed the mean of each sample and then computed the grand mean. All values are in minutes. Use this information to obtain three-sigma (i. e. , z = 3) control limits for means of future times. It is known from previous experience that the standard deviation of the process is. 02 minute. 10 -80
Control Chart for Variables/Example 10 -81
Control Chart for Variables/Example A quality inspector took five samples, each with four observations (n = 4), of the length of time for glue to dry. The analyst computed the mean of each sample and then computed the grand mean. All values are in minutes. Use this information to obtain three-sigma (i. e. , z = 3) control limits for means of future times. 10 -82
Control Chart for Variables/Example Standard Deviation is not given 10 -83
Control Chart for Variables/Example Plot the sample means in to control chart. 10 -84
Control Chart for Variables/Example For previous example, construct a Range chart From the Table for 3 -σ Control Limits, for n= 4 (observations per sample), D 4 = 2. 28 and D 3=0 UCL = 2. 28(0. 046) = 0. 105 LCL = 0(0. 046) = 0 Note that each sample’s range falls within these Control Limits 10 -85
Control Chart for Attributes § p-Chart - Control chart used to monitor the proportion of defectives in a process § c-Chart - Control chart used to monitor the number of defects per unit § Note for both p-Charts and c-Charts, if LCL is negative, then set LCL to zero. Attributes generate data that are counted. 10 -86
Use of p-Charts § When observations can be placed into two categories. § Good or bad § Pass or fail § Operate or don’t operate 10 -87
p-Charts § 10 -88
p-Chart Example An inspector counted the number of defective monthly billing statements of a company telephone in each of 20 samples. Using the following information, construct a control chart that will describe 99. 74 percent of the chance variation in the process when the process is in control. Each sample contained 100 statements. 10 -89
p-Chart Example 10 -90
p-Chart Example § 10 -91
p-Chart Example Plot the sample proportions in the Control Chart 10 -92
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 10 -93
c-Charts § 10 -94
c-Chart Example Rolls of coiled wire are monitored using a c-chart. Eighteen rolls have been examined, and the number of defects per roll has been recorded in the following table. Is the process in control? Plot the values on a control chart using three standard deviation control limits 10 -95
c-Chart Example 10 -96
Use of Control Charts § At what point in the process to use control charts § What size samples to take § What type of control chart to use § Variables § Attributes 10 -97
Run Tests § Run test – a test for randomness § Any sort of pattern in the data would suggest a non-random process § All points are within the control limits - the process may not be random 10 -98
Nonrandom Patterns in Control charts § § § Trend Cycles Bias Mean shift Too much dispersion 10 -99
Counting Runs Counting Above/Below Median Runs B A A B B B (7 runs) A A Counting Up/Down Runs U U D U B (8 runs) D U U D 10 -100
Non. Random Variation § Managers should have response plans to investigate cause § May be false alarm (Type I error) § May be assignable variation 10 -101
Determine whether a process is in control? § Transform the data into As and Bs, and Us and Ds. § Count the number of Runs in each case § N is number of observations 10 -102
Determine whether a process is in control § Expected number of Runs § Standard Deviation of Runs § Z of Runs 10 -103
Determine whether a process is in control 10 -104
Example Twenty sample means have been taken from a process. The means are shown in the following table. Use median and up/down run tests with z = 2 to determine if assignable causes of variation are present. Assume the median is 11. 0 10 -105
Example Although the median test does not reveal any pattern, because its ztest value is within the range ± 2, the up/down test does; its value exceeds +2. Consequently, nonrandom variations are probably present in the data and, hence, the process is not in control 10 -106
Process Capability § Tolerances or specifications § Range of acceptable values established by engineering design or customer requirements § Process variability § Natural variability in a process § Process capability § Process variability relative to specification § For a process to be capable, its capability index (ideally) should be 1. 33 or higher 10 -107
Process Capability Lower Specification Upper Specification A. Process variability matches specifications Lower Specification Upper Specification B. Process variability Lower Upper well within specifications Specification C. Process variability exceeds specifications 10 -108
Process Capability Ratio If the process is centered use Cp specification width Process capability ratio, Cp = process width Cp = Upper specification – lower specification 6 If the process is not centered use Cpk 10 -109
Process Capability Ratio Example 1 Determine the capability of each process (i. e. , six standard deviations) and compare that value to the specification difference of. 80 mm Process capability for Process A is 0. 13 x 6=0. 78. Similarly, Process B capability is 0. 48, and Process C capability is 0. 96 10 -110
Process Capability Ratio Example 1 § 10 -111
Process Capability Ratio Example 2 A process has a mean of 9. 20 grams and a standard deviation of. 30 gram. The lower specification limit is 7. 50 grams and the upper specification limit is 10. 50 grams. Compute Cpk The smaller of the two indexes is 1. 44, so this is the Cpk. Because the Cpk is more than 1. 33, the process is capable 10 -112
Limitations of Capability Indexes 1. Process may not be stable 2. Process output may not be normally distributed 3. Process not centered but Cp is used 10 -113
3 Sigma and 6 Sigma Quality Upper specification Lower specification 1350 ppm 1. 7 ppm Process mean +/- 3 Sigma +/- 6 Sigma 10 -114
Improving Process Capability § § § Simplify Standardize Mistake-proof Upgrade equipment Automate 10 -115
Taguchi Loss Function Traditional cost function Cost Taguchi cost function Lower spec Target Upper spec 10 -116
NEXT SESSION QUIZ QUALITY MANAGEMENT AND CONTROL (STEVENSON CHAPTERS 9 & 10) 10 -117
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