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Introduction to Statistical Quality Control, 4 th Edition. Douglas C. Montgomery Arizona State University. Chapter 1. Quality Improvement in the Modern Business Environment. 1-1. The Meaning of Quality and Quality Improvement. 1-1.1 Dimensions of Quality
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Introduction to Statistical Quality Control, 4th Edition Douglas C. Montgomery Arizona State University Introduction to Statistical Quality Control, 4th Edition
Chapter 1 Quality Improvement in the Modern Business Environment Introduction to Statistical Quality Control, 4th Edition
1-1. The Meaning of Quality and Quality Improvement 1-1.1 Dimensions of Quality 1-1.2 Quality Engineering Technology Introduction to Statistical Quality Control, 4th Edition
Performance Reliability Durability Serviceability Aesthetics Features Perceived Quality Conformance to standards 1-1.1 Dimensions of Quality Introduction to Statistical Quality Control, 4th Edition
1-1.1 Dimensions of Quality • Definitions of Quality Quality means fitness for use - quality of design - quality of conformance Quality is inversely proportional to variability. Introduction to Statistical Quality Control, 4th Edition
1-1.1 Dimensions of Quality • Quality Improvement Quality improvementis the reduction of variability in processes and products. Alternatively, quality improvementis also seen as “waste reduction”. Introduction to Statistical Quality Control, 4th Edition
1-1.1 Dimensions of Quality – Transmission Example Introduction to Statistical Quality Control, 4th Edition
1-1.2 Quality Engineering Terminology Quality Characteristics • Physical - length, weight, voltage, viscosity • Sensory - taste, appearance, color • Time Orientation - reliability, durability, serviceability Introduction to Statistical Quality Control, 4th Edition
1-1.2 Quality Engineering Terminology Quality engineeringis the set of operational, managerial, and engineering activities that a company uses to ensure that the quality characteristics of a product are at the nominal or required levels. Introduction to Statistical Quality Control, 4th Edition
1-1.2 Quality Engineering Terminology Two types of data • Attributes Data - discrete data, often in the form of counts. • Variables Data - continuous measurements such as length, weight. Introduction to Statistical Quality Control, 4th Edition
1-1.2 Quality Engineering Terminology Specifications Quality characteristics being measured are often compared to standards or specifications. • Nominal or target value • Upper Specification Limit (USL) • Lower Specification Limit (LSL) Introduction to Statistical Quality Control, 4th Edition
1-1.2 Quality Engineering Terminology • When a component or product does not meet specifications, they are considered to be nonconforming. • A nonconforming product is considered defective if it has one or more defects. • Defects are nonconformities that may seriously affect the safe or effective use of the product. Introduction to Statistical Quality Control, 4th Edition
1-1.2 Quality Engineering Terminology • Concurrent Engineering Team approach to design. Specialists from manufacturing, quality engineering, management, etc. work together for product or process improvement. Introduction to Statistical Quality Control, 4th Edition
1-2. A Brief History of Quality Control and Improvement (Refer to Table 1-1) • Walter Shewhart (1924) introduced statistical control chart concepts. • The American Society for Quality Control formed in 1946 (now known as the American Society for Quality (ASQ)). • 1950s and 1960s saw an increase in reliability engineering, experimental design, and statistical quality control Introduction to Statistical Quality Control, 4th Edition
1-2. A Brief History of Quality Control and Improvement (Refer to Table 1-1) • Competition from foreign industries (Japan) increases during the 1970s and 1980s. • Statistical methods for quality improvement use increases in the United States during the 1980s • Total Quality Management (TQM) emerges during 1970s and into the 1980s as an important management tool to implement statistical methods. Introduction to Statistical Quality Control, 4th Edition
1-2. A Brief History of Quality Control and Improvement • Malcolm Baldridge National Quality Award is established in 1988. • ISO 9000 certification activities increase in U.S. industry in the 1990s. • Motorola’s Six-Sigma initiative begins in the 1990s. Introduction to Statistical Quality Control, 4th Edition
1-3. Statistical Methods for Quality Control and Improvement Three major areas: • Statistical process control (SPC) • Design of experiments (DOX) • Acceptance sampling Introduction to Statistical Quality Control, 4th Edition
1-3. Statistical Methods for Quality Control and Improvement Statistical Process Control (SPC) • Control charts are used for process monitoring and variability reduction. • SPC is an on-line quality control tool. Introduction to Statistical Quality Control, 4th Edition
1-3. Statistical Methods for Quality Control and Improvement Design of Experiments • Experimental design is an approach to systematically varying the controllable input factors in the process and determine the effect these factors have on the output responses. • Experimental designs are off-line quality tools. • Crucial for variability reduction. Introduction to Statistical Quality Control, 4th Edition
1-3. Statistical Methods for Quality Control and Improvement Acceptance Sampling • Acceptance samplingis the inspection and classification of a sample of the product selected at random from a larger batch or lot and the ultimate decision about disposition of the lot. • Two types: 1. Outgoing inspection - follows production 2. Incoming inspection - before use in production Introduction to Statistical Quality Control, 4th Edition
1-4. Other Aspects of Quality Control and Improvement Total Quality Management (TQM) • TQM is a managerial framework to accomplish quality improvement. • Other names and related approaches: • Company-Wide Quality Control (CWQC) • Total Quality Assurance (TQA) • Six-Sigma Introduction to Statistical Quality Control, 4th Edition
1-4. Other Aspects of Quality Control and Improvement 1-4.1 Quality Philosophy and Management Strategies 1-4.2 The Link Between Quality and Productivity 1-4.3 Quality Costs 1-4.4 Legal Aspects of Quality 1-4.5 Implementing Quality Improvement Introduction to Statistical Quality Control, 4th Edition
1-4.1Quality Philosophy and Management Strategies Three Important Leaders • W. Edwards Deming - Emphasis on statistical methods in quality improvement (see Deming’s 14 points) • Joseph Juran - Emphasis on managerial role in quality implementation • Armand V. Feigenbaum - Emphasis on organizational structure Introduction to Statistical Quality Control, 4th Edition
1-4.1 Quality Philosophy and Management Strategies • Total Quality Management (TQM) • Quality Standards and Registration • ISO 9000 • Six Sigma • Just-In-Time, Lean Manufacturing, Poka-Yoke, etc. Introduction to Statistical Quality Control, 4th Edition
1-4.2 The Link Between Quality and Productivity • Effective quality improvement can be instrumental in increasing productivity and reducing cost. • The cost of achieving quality improvements and increased productivity is often negligible. Introduction to Statistical Quality Control, 4th Edition
1-4.3 Quality Costs Quality Costsare those categories of costs that are associated with producing, identifying, avoiding, or repairing products that do not meet requirements. These costs are: • Prevention Costs • Appraisal Costs • Internal Failure Costs • External Failure Costs Introduction to Statistical Quality Control, 4th Edition
1-4.4 Legal Aspects of Quality The re-emergence of quality assurance as an important business strategy is in part a result of • Consumerism • Product Liability Introduction to Statistical Quality Control, 4th Edition
1-4.5 Implementing Quality Improvement • Strategic Management of Quality • Almost all successful efforts have been management-driven. • Too much emphasis on registration and certification programs (ISO, QS) • Insufficient focus on quality planning and design, quality improvement, overemphasis on quality assurance • Poor use of available resources Introduction to Statistical Quality Control, 4th Edition