Total Quality Management (TQM)

1. Total Quality Management(TQM) Dr. Gene Fliedner Decision and Information Sciences School of Business Administration Oakland University

2. TQM • Quality: a powerful competitive weapon • Importance evidenced by variety of industrial awards (e.g., Baldrige Award, Deming Prize) • Complex and multifaceted concept • TQM is a continuous, organization-wide effort to total customer satisfaction and continuous process improvement • Is the customer always right? • The underlying principle of TQM programs is to produce products of high quality in the first place, rather than depend on detecting defective products later through inspection.

3. Alternative Quality Definitions? • Product-based definition - quality is a precise and measurable variable where differences in quality reflect differences in the quantity of some ingredient or attribute possessed by a product. Example: content of multivitamins • User-based definition - in terms of satisfying the consumers’ wants, needs and preferences. Example: brand name manufacturer versus generic drugs • Manufacturing-based definition - conformance to requirements, meeting specifications. Example: interior diameter of pipe • Value-based definition - in terms of costs and prices. Quality is value for the dollar spent • Elimination of variability.

4. Garvin’s “Dimensions of Quality” • Performance – product/service primary characteristics • Reliability – consistency of performance • Durability – length of useful life • Conformance to specifications • Aesthetics – appearance, feel, smell, taste • Special features - extras • Safety • After sale service • Perceptions – indirect evaluation of quality

5. Costs of Quality • Internal failure costs • External failure costs • Appraisal costs • Prevention costs

6. 5 TQM “Gurus” • Shewhart: “grandfather of SPC,” Shewhart cycle • Deming: 14 points; “father of quality control,” known for: appreciation of a system, knowledge of variation, theory of knowledge, knowledge of psychology • Juran: Pareto principle; trilogy or cross-functional management approach comprised of quality planning, quality control, and quality improvement • Crosby: Quality is Free; “do it right the first time” • Feigenbaum: total quality control (systems view)

7. 6 TQM Programs Elements • Top Management Leadership and Commitment • Mission statement: is quality a corporate objective? • Leadership: Remember 3 points • Definition: “interpersonal influence, exercised in situations and directed through the communication process, toward the attainment of a specified goal or goals.” • Influence = the numerous “leadership theories” and various leadership styles • Leadership includes setting the direction the organization through a thorough, long-term vision of the organization’s value-producing processes. • Long-term commitment to continuous improvement (kaizen) • Product design: Manufacturability and conformance to specifications • Idea: design and build in quality rather than inspect it in; nonconformance is $$$ • Practices: product standardization; simplicity or fewer parts, where for n independent components, system reliability Rs = (R1)(R2)(Rn); robotics; vertical insertion; redundancies, where for a system with a back-up, Rs = R1+{R2*(1-R1)}; improved supplier relations; preventative maintenance • Cpk: ratio of allowable process variability to actual variability (versus Cp ratio) • Process design • Practices: ISO 9000/TS 16949 (standardized thinking); recognizing value of employees (education and training programs, participative management, quality circles, “quality at the source,” Plan-Do-Study-Act ); organizational structure (teams based matrix approach, fewer management levels, increased span of control); technology and tools; and through the customer focus (see next slide)

8. 6 TQM Programs Elements • Customer Focus: Internal and External Customers a. Internal: Engaged employees(an understanding of their importance and a demonstration of this through practices such as participative management and teamwork) (1) Quality at the Source (empowered employees) • Authority is the power granted to individuals so that they can make final decisions to complete their assignments • Responsibility is the obligation incurred by individuals in their roles in the formal organization in order to effectively perform assignments. • Accountability is the state of being totally answerable for the satisfactory completion of a specific assignment. • Accountability = Authority + Responsibility (2) Employee skills: education, training (tool kits), standardized thinking (3) Technology and tools (4) Quality Circles • A decentralization of management responsibility; a group of 3 to 10 employees doing related work; meets at regular intervals; objectives of increased productivity and quality; direct employee involvement; provide for substantial individual motivation; improve managerial decision-making b. External customers: consumers, customers, vendors (1) Quality Function Deployment (QFD) (2) Conformance to specifications (3) Engaging suppliers and managing the supply chain quality

9. 6 TQM Programs Elements • After-the-sale service quality: distribution, installation, after-the-sale support • Use of Quality Tools; 2 categories • Process Improvement Tools: attempt to reduce the causes of variation before it happens • Statistical Process Control (SPC) Tools or Techniques: attempt to identify assignable causes of variation so that it eventually may be eliminated • Variation caused by chance causes (random variation) and assignable (attributable) causes • Process Improvement Tool examples (1) Benchmarking (2) Brainstorming (3) Process Mapping (flow charting); example follows (4) Pareto Analysis and Histograms; example follows (5) Cause-and-Effect Diagrams (a.k.a., Ishikawa diagram, 4M diagram, fishbone diagram) ; example follows (6) Check Sheets (checklists); example follows (7) Scatter Diagrams ; example follows • Statistical Process Control (SPC) Tools or Techniques: 2 subcategories (1) Control charts: used for higher volume, repetitive processes (2) Acceptance plans: used for lower volume, batch processes

10. Process Improvement Tool: Process Mapping (Flowcharting) Different shapes represent different types of process flow tasks, e.g., rectangle represents a task while triangle represents assessment. Diagram to left is an example of an “engineering” process map. There is also a “flow” process map that depicts items in 1 of 5 states during flow: (1) in process, (2) being moved, (3) being stored or in inventory, (4) waiting to be moved, or (5) in inspection.

11. Process Improvement Tool: Histogram • Along the x-axis you find the categories of concern, e.g., repair times for various failures • If you read over to the y-axis you find the frequency (or the probability) of the category occurring • The idea is to help direct improvement efforts

12. Process Improvement Tool: Pareto Chart • A variant of an histogram • Categories are arranged from greatest frequency of occurrence to least frequent • The cumulative frequency is 1 or 100%

13. Process Improvement Tool: Cause and Effect Diagram • Also called Ishikawa diagram, 4M diagram, and fishbone diagram • Process: work back from the effect to attempt to identify the cause • Common to find more than 4 categories; e.g., 5th M may be “metrics”; 6th M may be “mother nature”

14. Process Improvement Tool: Check sheet • You’re keeping a running tally of the issue or defect type, typically by date, time, and location, so that the frequencies can be ultimately determined

15. Process Improvement Tool: Scatter Diagram • Diagram makes relationships (correlation) clearer

16. SPC Tool: Control Charts • A graphical tool for describing the state of control of a process • Basic control charts consists of UCL, LCL and centerline (process mean) • X-axis is time while the Y-axis is generally the mean of the quality characteristic being measured • It is used to monitor the output of high volume (repetitive) production processes • Sample values are used to monitor process performance • It’s a confidence interval designed to achieve desired level of producer (type I error) and consumer risk (type II error) • Construction varies with data type Variable (continuous) or Attribute (0-1) • Variable Data: Means chart and Range chart • Attribute Data: P-chart, nP-chart, c-chart and u-chart • Because it’s a confidence interval, the UCL and LCL are typically process mean + some number of standard deviations (z-scores).

17. Statistical Process Control (SPC) Techniques • Remember: The underlying principle of the quality management process is to produce products of high quality in the first place, rather than depend on detecting defective products later through inspection. • Note: A process is in statistical control if the variation in the process is due to common causes (random causes) alone. When special causes (assignable causes) are present, the process is deemed to be out of control. • Process Control attempts to identify assignable causes of variation so that it eventually may be eliminated. Control charts and acceptance plans are used for this purpose. • The limits of SPC Control charts are determined from the output of the production process itself. • SPC depends upon sampling.

18. Sampling • The timing, location and amount of sampling is governed by the cost of sampling versus the expected cost of passing on defective items. • Strategic locations of sampling? • The costs of undetected defects and sampling are inversely related. • Two data types a. Variable (continuous) b. Attribute (0-1) • Type I and Type II Errors - sampling leads to incorrect decisions • Type I Error - a decision that the production process is out of control when in reality it is in control (producer’s risk). Cost of a Type I error: lost production time, cost of testing for an absent (ghost) problem • Type II Error - a decision that the production process is in control when in reality it is out of control (consumer’s risk). Cost of a Type II error: scrap, rework, after-the-sale service costs (difficult to measure)  • Controlling for Type I and II Errors • Increase amount of inspection – frequency or sample size • Reduce size of control limits

19. 2 Causes of Variation • Random versus Assignable Variation

20. Interpretation and Use of Control Charts • Observations should fall within the limits • Data points should not reflect any trends • Low degree of variability should be observed in the data points • No evidence of “runs” in the data

21. Control Charts for Variable (Continuous) Data • Means Chart: used to monitor the average value of the variable being measured  • Center line, x (mean of sample means) • UCL = x + Z(x) where, x = /n and it is the standard deviation of the distribution of sample means • LCL = x - Z(x) • Alternatively: UCL = x + A2(R) and LCL = x - A2(R) • Range Chart: measures variability within a sample • Center line, R • UCL = D4R • LCL = D3R

22. Control Charts for Attribute (0-1) Data • Control chart for proportion (fraction) defective, 1 defect per unit of output, p-Chart • Center line is process mean, p _______ • UCL and LCL = p + Z  p(1-p)/n (where n is sample size) • Control chart for number defective, 1 defect per unit of output, np-Chart • Center line is process mean, np ______ b. UCL and LCL = np+ Z np(1-p) • Control chart for total number of defects in a sample, multiple defects per unit of output, c-Chart • Center line is process mean, c _ b. UCL and LCL = c +Z√c • Control chart for the avg number of defects in a sample, multiple defects per unit of output, u-Chart • Center line is process mean, u (where u is x/n and x is number of defects in sample) ___ b. UCL and LCL = u +Z√u/N

23. Control Chart Construction Guidelines • If cost of investigating cause of “out-of-control” decision is high, a Type I error is important and should be avoided. Use wider control limits. • If cost of passing on defectives is high, Type II error is important and should be avoided. Use narrower limits. • If costs of Type I and Type II errors are high, wide control limits should be used and consideration should be given to increasing sample size and increasing frequency of taking samples. • Based upon actual experience, if out-of-control conditions arise frequently, narrower control limits should be favored.

24. Acceptance Sampling • Acceptance Sampling: process of randomly inspecting a certain number of items (sample size of n) from a batch of items (N) to determine acceptance/rejection of the lot based upon observed number of defects versus acceptance/rejection criteria. • Sampling Plans: identify N, n, accept/reject criteria, single, double, multiple-sampling • Operating Characteristic Curve: demonstrates the discriminating power of the sampling plan; x-axis is proportion of defective items in lot, y-axis is probability of lot acceptance • Acceptable Quality Level (AQL): the percentage of defects consumers are willing to accept • Lot Tolerance Percent Defective (LTPD): threshold (maximum) level of defective items consumers tolerate • Average Outgoing Quality (AOQ): assuming all lots have same proportion defective (p), the overall average outgoing quality where Pac is probability of acceptance is: AOQ = (Pac)p(N-n/N)