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Managing Quality
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What Is “Quality?” We all know what we mean by “quality” Yet it is often difficult to define Sometimes it is easier to use examples to translate the ideas, like metaphors… Example: Name a QUALITY automobile…
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Definitions of Quality American Society for Quality (ASQ) defines quality as “the totality of features and characteristics of a product or service that bears on its ability to satisfy stated or implied needs” We will accept the above as our working definition of quality
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Definitions of Quality (cont.) User-Based: Quality “lies in the eye of the beholder”- quality is what the consumer says it is Manufacturing-Based: Degree to which a product conforms to design specification- “make it right the first time” Product-Based: Level of measurable product characteristic- “a precise and measurable variable”
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1. Performance- A product’s primary operating characteristic. Examples are automobile acceleration and a television’s picture clarity 2. Features- Supplements to a product’s basic functioning characteristics, such as power windows on a car 3. Reliability- A probability of not malfunctioning during a specified period 4. Conformance- The degree to which a product’s design and operating characteristics meet established standards 5. Durability- A measure of product life 6. Serviceability- The speed and ease of repair 7. Aesthetics- How a product looks, feels, tastes, and smells 8. Perceived quality- As seen by a customer Dimensions of Quality for Goods
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Importance of Quality Costs & market share Company’s reputation Product liability International implications… Increased Profits Lower Costs Productivity Rework/Scrap Warranty Market Gains Reputation Volume Price Improved Quality
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Named after former Secretary of Commerce Established in 1988 by the U.S. government Designed to promote TQM practices Some criteria: Senior executive leadership Strategic planning Management of process quality Quality results Customer satisfaction Recent winners: Corning Inc., GTE, AT&T, Eastman Chemical, Cadillac, Ritz- Carlton Malcom Baldrige Award
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International Quality Standards Industrial Standard Z8101-1981 (Japan) Specification for TQM ISO 9000 series (Europe/EC) Common quality standards for products sold in Europe (even if made in U.S.) ISO 14000 series (Europe/EC) Standards for recycling, labeling etc. ASQC Q90 series; MILSTD (U.S.)
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ISO 14000 series EC environmental standards Core elements: Environmental management Auditing Performance evaluation Labeling Life-cycle assessment
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Costs of poor quality “are huge, but the amounts are not known with precision. In most companies, the accounting system provides only a minority of the information needed to quantify this cost of poor quality” Joseph Juran on Quality (1992)
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Philip Crosby on Quality (1980) The cost of quality is "the expense of nonconformance - the cost of doing things wrong"
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Armand Feigenbaum on Quality The originator of Total Quality Control at MIT (1963) Developed the idea of “quality in source,” that each worker (including white-collar) should be responsible for performing their jobs with perfect quality
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W. Edwards Deming on Quality Created a new quality philosophy with his 14 principles (1950) emphasizing: Do not sacrifice quality for the short term Production must be stable for quality Use of statistical process controls Kaizen Quality cannot “be inspected into products” Team work Workers must have the right tools Workers can only correct 15% of problems
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Deming’s Fourteen Points 1. Create consistency of purpose 2. Lead to promote change 3. Build quality into the products 4. Build long term relationships 5. Continuously improve product, quality, and service 6. Start training 7. Emphasize leadership
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Deming’s Fourteen Points (cont.) 8. Drive out fear 9. Break down barriers between departments 10. Stop haranguing workers 11. Support, help, improve 12. Remove barriers to pride in work 13. Institute a vigorous program of education and self-improvement 14. Put everybody in the company to work on the transformation
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Costs of Quality Prevention costs - reducing the potential for defects Appraisal costs - evaluating products Internal failure - of producing defective parts or service External costs - occur after delivery
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Total Quality Management (TQM) Encompasses entire organization, from supplier to customer Stresses a commitment by management to have a continuing, company-wide, drive toward excellence in all aspects of products and services that are important to the customer
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Flow of Activities to Achieve TQM Organizational Practices Quality Principles Employee Fulfillment Customer Satisfaction
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Organizational Practices Leadership Mission statement Effective operating procedure Staff support Training Yields: What is important and what is to be accomplished
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Quality Principles Customer focus Continuous improvement Employee empowerment Benchmarking Just-in-time Tools of TQM Yields: How to do what is important and to be accomplished
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Employee Fulfillment Empowerment Organizational commitment Yields: Employees’ attitudes that they can accomplish what is important and to be accomplished
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Customer Satisfaction Winning orders Repeat customers Yields: An effective organization with a competitive advantage
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Concepts of TQM Continuous improvement Employee empowerment Benchmarking Just-in-time (JIT) Taguchi concepts Knowledge of TQM tools
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Continuous Improvement Represents continual improvement of process & customer satisfaction Involves all operations & work units Kaizen:
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Shewhart’s PDCA Model 4.Act: Implement the plan 1.Plan: Identify the improvement and make a plan 3.Check: Is the plan working 2.Do: Test the plan
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Employee Empowerment Getting employees involved in product & process improvements 85% of quality problems are due to process & material Techniques Support workers Let workers make decisions Build teams & quality circles
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Quality Circles Group of 6-12 employees from same work area Meet regularly to solve work-related problems 4 hours/month Facilitator trains & helps with meetings
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Benchmarking Selecting best practices to use as a standard for performance Determine what to benchmark Form a benchmark team Identify benchmarking partners Collect and analyze benchmarking information: Examine everyone who performs similar activities Determine who “does it best” Set the “best” as the standard: the benchmark Take action to match or exceed the benchmark
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Best Practices in Customer Service Make it easy for clients to complain Respond quickly to complaints Resolve complaints on the first contact Use computers to manage complaints Recruit the best for customer service jobs
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Just-in-Time (JIT) Relationship to quality: JIT cuts cost of quality JIT improves quality Better quality means less inventory and better, easier-to-employ JIT system Requires “zero” defects Allows for no underage or overage
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Just-in-Time (JIT) ‘Pull’ system of production/purchasing Customer starts production with an order Involves ‘vendor partnership programs’ to improve quality of purchased items Reduces all inventory levels Inventory hides process & material problems Improves process & product quality
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Just-In-Time (JIT) Example Scrap Work in process inventory level (hides problems) Unreliable Vendors Capacity Imbalances
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Just-In-Time (JIT) Example Scrap Reducing inventory reveals problems so they can be solved. Unreliable Vendors Capacity Imbalances
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Six Major Tools for TQM 1. Quality Function Deployment 2. Taguchi techniques 3. Pareto charts 4. Process charts 5. Cause-and-effect diagrams 6. Statistical process controls
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Quality Function Deployment Determines what will satisfy the customer Translates those customer desires into the target design Allows the company to assess its product offerings in relation to those of its rivals Formal process aids in continuous improvement
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House of Quality
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Taguchi Techniques Experimental design methods to improve product & process design Identify key component & process variables affecting product variation Taguchi Concepts Quality robust design Quality loss function Target-oriented quality
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Ability to produce products uniformly and consistently regardless of adverse manufacturing and environmental conditions Put robustness in House of Quality matrices beside functionality Quality Robustness
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Shows social cost ($) of deviation from target value Assumptions Most measurable quality characteristics (e.g., length, weight) have a target value Deviations from target value are undesirable Equation: L = D 2 C L = Loss ($) D = Deviation C = Cost Quality Loss Function
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Target-Oriented Quality Low loss High loss Frequency Lower Target Upper Specification Loss (to producing organization, customer, and society) Quality Loss Function (a) Unacceptable Poor Fair Good Best Target-oriented quality yields more product in the “best” category Target-oriented quality brings products toward the target value Conformance-oriented quality keeps product within three standard deviations Distribution of specifications for product produced (b)
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A study found U.S. consumers preferred Sony TV’s made in Japan to those made in the U.S. Both factories used the same designs & specifications. The difference in quality goals made the difference in consumer preferences. Japanese factory (Target-oriented) U.S. factory (Conformance-oriented) Target-Oriented Quality Example
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Tools of TQM Tools for generating ideas Check sheet Scatter diagram Cause and effect diagram Tools to organize data Pareto charts Process charts (Flow diagrams) Tools for identifying problems Histograms Statistical process control chart
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Tools of TQM (cont.)
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Pareto Analysis of Wine Glass Defects (Total Defects = 75) 72%16%5%4%3%
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Shows sequence of events in process Depicts activity relationships Has many uses: Identify data collection points Find problem sources Identify places for improvement Identify where travel distances can be reduced Process Chart
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Process Chart Example
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Used to find problem sources/solutions Other names Fish-bone diagram, Ishikawa diagram Steps Identify problem to correct Draw main causes for problem as ‘bones’ Ask ‘What could have caused problems in these areas?’ Repeat for each sub-area. Cause and Effect Diagram
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Too many defects Problem Ishikawa Diagram Example
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MethodManpower Material Machinery Too many defects Main Cause Ishikawa Diagram Example
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MethodManpower Material Machinery DrillDrill OvertimeOvertime SteelSteel WoodWood LatheLathe Too many defects Sub-Cause Ishikawa Diagram Example
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MethodManpower Material MachineryDrillDrillOvertimeOvertime SteelSteel WoodWood LatheLathe Too many defects TiredTiredOldOld SlowSlow Ishikawa Diagram Example
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Airline Customer Service Example
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Uses statistics & control charts to tell when to adjust process Developed by Shewhart in 1920’s Involves: Creating standards (upper & lower limits) Measuring sample output (e.g. mean wgt.) Taking corrective action (if necessary) Done while product is being produced Statistical Process Control (SPC)
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Show changes in data pattern e.g., trends Make corrections before process is out of control Show causes of changes in data Assignable causes Data outside control limits or trend in data Natural causes Random variations around average Control Chart Purposes
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SPC Charts Control charts are used to indicate when a production process may have changed to the degree to affect quality Variable charts (X, R) track variations in measurements within samples Attribute charts (p, c) track whether attributes exist within samples
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Control Charts R Chart Variable Charts Attribute Charts X Chart p c Continuous Numerical Data Categorical or Discrete Numerical Data Control Chart Types
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Characteristics that either exist, or do not Classify products as either ‘good’ or ‘bad’, or count # defects e.g., radio works or does not Categorical or discrete random variablesAttributesVariables SPC Quality Characteristics Characteristics that you measure, e.g., weight, length May be in whole or in fractional numbers Continuous random variables
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Produce Good Provide Service Stop Process Yes No Assign. Causes? Take Sample Inspect Sample Find Out Why Create Control Chart Start Statistical Process Control Steps
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Process Control Chart
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Control Chart Example:
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Patterns in Control Charts
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Type of variables control chart Interval or ratio scaled numerical data e.g., dimensions, weight, etc. Shows sample means over time Monitors process average Example: Weigh samples of coffee & compute means of samples; Plot X Chart
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X Chart Control Limits Range for sample i # Samples Mean for sample i From Table S6.1
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Type of variables control chart Interval or ratio scaled numerical data Shows sample ranges over time Difference between smallest & largest values in inspection sample Monitors variability in process Example: Weigh samples of coffee & compute ranges of samples; Plot R Chart
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R Chart Control Limits Range for Sample i # Samples From Table S6.1
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Control Chart Factors (p. 227)
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X and R Charts Example A control process consists of 12 samples (with 20 units in a sample) with different means and sample ranges: #MeanRange#MeanRange 116.22.0716.02.9 215.92.1816.11.8 316.31.8916.31.5 416.43.01016.31.0 515.83.51116.41.0 615.93.11216.50.9
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X and R Charts Example Construct: X Chart R Chart Use the following factors: A 2 = 0.18 D 3 = 0.41 D 4 = 1.59 Is the process in control?
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POM for Windows Results
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POM for Windows X Chart
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POM for Windows R Chart
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Type of attributes control chart Nominally scaled categorical data e.g., good-bad Shows % of nonconforming items Example: Count # defective chairs & divide by total chairs inspected; Plot Chair is either defective or not defective p Chart
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p Chart Control Limits # Defective Items in Sample i Size of sample i z = 2 for 95.5% limits; z = 3 for 99.7% limits
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Type of attributes control chart Discrete quantitative data Shows number of nonconformities (defects) in a unit Unit may be chair, steel sheet, car etc. Size of unit must be constant Example: Count # defects (scratches, chips etc.) in each chair of a sample of 100 chairs; Plot c Chart
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c Chart Control Limits # Defects in Unit i # Units Sampled Use 3 for 99.7% limits
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p and c Charts Example (p. 231) Data entry clerks key in thousands of records each day. Samples of the work of 20 clerks are shown here. 100 records by each clerk were carefully examined to make sure they contained no errors. Construct a control chart with a 99.7 % level of confidence. Is the process in control? #Errors# 16116 25121 30138 41147 54155 62164 751711 83183 93190 102204
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POM for Windows Results
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POM for Windows p Chart
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Deciding Which Chart to Use Using an X and R chart: Observations are variables Collect 20-25 samples of n=4, or n=5, or more each from a stable process and compute the mean for the X chart and range for the R chart. Track samples of n observations each.
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Deciding Which Chart to Use Using the P-Chart: We deal with fraction, proportion, or percent defectives Observations are attributes that can be categorized in two states Have several samples, each with many observations Assume a binomial distribution unless the number of samples is very large – then assume a normal distribution. Using a C-Chart: Observations are attributes whose defects per unit of output can be counted The number counted is often a small part of the possible occurrences Assume a Poisson distribution Defects such as: number of blemishes on a desk, number of typos in a page of text, flaws in a bolt of cloth
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Involves examining items to see if an item is good or defective Detect a defective product Does not correct deficiencies in process or product Issues When to inspect Where in process to inspect Inspection
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When and Where to Inspect At the supplier’s plant while the supplier is producing At your facility upon receipt of goods from the supplier Before costly or irreversible processes During the step-by-step production processes When production or service is complete Before delivery from your facility At the point of customer contact
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Form of quality testing used for incoming materials or finished goods e.g., purchased material & components Procedure Take one or more samples at random from a lot (shipment) of items Inspect each of the items in the sample Decide whether to reject the whole lot based on the inspection results What Is Acceptance Sampling?
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Set of procedures for inspecting incoming materials or finished goods Identifies Type of sample Sample size (n) Criteria (c) used to reject or accept a lot Producer (supplier) & consumer (buyer) must negotiate What Is an Acceptance Plan?
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Shows how well a sampling plan discriminates between good & bad lots (shipments) Shows the relationship between the probability of accepting a lot & its quality Operating Characteristics Curve
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Acceptable quality level (AQL) Quality level of a good lot Producer (supplier) does not want lots with fewer defects than AQL rejected Lot tolerance percent defective (LTPD) Quality level of a bad lot Consumer (buyer) does not want lots with more defects than LTPD accepted AQL & LTPD
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Producer's risk ( ) Probability of rejecting a good lot Probability of rejecting a lot when fraction defective is AQL Consumer's risk (ß) Probability of accepting a bad lot Probability of accepting a lot when fraction defective is LTPD Producer’s & Consumer’s Risk
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An Operating Characteristic (OC) Curve Showing Risks = 0.05 producer’s risk for AQL = 0.10 Consumer’s risk for LTPD Probability of Acceptance Percent Defective Bad lots Indifference zone Good lots LTPD AQL 0 1 2 3 4 5 6 7 8 100 95 75 50 25 10 0
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Average Outgoing Quality Where: P d = true percent defective of the lot P a = probability of accepting the lot N = number of items in the lot n = number of items in the sample
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Service quality is more difficult to measure than for goods Service quality perceptions depend on Expectations versus reality Process and outcome Types of service quality Normal: Routine service delivery Exceptional: How problems are handled TQM In Services
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Goods vs. Services Can be resold Can be inventoried Some aspects of quality measurable Selling is distinct from production Reselling unusual Difficult to inventory Quality difficult to measure Selling is part of service Good Service Good Service
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Goods vs. Services (cont.) Product is transportable Site of facility important for cost Often easy to automate Revenue generated primarily from tangible product Provider, not product is transportable Site of facility important for customer contact Often difficult to automate Revenue generated primarily from intangible service Good Service
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Determinants of Service Quality Reliability – consistency and dependability Responsiveness – willingness/readiness of employees to provide service; timeliness Competence – possession of skills and knowledge required to perform service Access – approachability and ease of contact Courtesy – politeness, respect, consideration, friendliness of contact personnel
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Determinants of Service Quality Communication – keeping customers informed in languages they understand Credibility – trustworthiness, believability, honesty Security – freedom from danger, risk or doubt Understanding/knowing the customer – making the effort to understands the customer’s needs Tangibles – the physical evidence of the service
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