CHAPTER 1. Introduction

Transcription

1 CHAPTER 1 Introduction This introductory chapter provides an overview of quality and reliability engineering techniques, the relationship between reliability and cost, and reliability, design, and assessment. This chapter also presents the scope and organization of the book. 1.1 INTRODUCTION Design involves innovation and requires knowledge from the science and engineering fields. It includes the selection of materials, parts, and tentative parameter values in the product design stage and the selection of production equipment and tentative values for process factors in the process design stage. The term quality has been defined in different ways by various authors. Crosby (1979) defines quality as, quality is conformance to requirements or specifications. Juran (1974) proposes the definition for quality as quality is fitness for use. A more general definition for quality is given as follows: the quality of a product or service is the fitness of that product or service for meeting or exceeding its intended use as required by the customer. The term quality implies different levels of expectations for different groups of consumers or customers. Quality should be designed into a product. There are three aspects generally associated with the definition of quality. They are: (a) quality of design (b) quality of conformance (c) quality of performance Quality of Design: Quality of design focuses on the stringent conditions that the product must minimally possess to satisfy the requirements of a customer. In other words, the product must be designed to meet at least the minimal needs of the customer. Quality of design is generally influenced by factors including the type of product, cost, profit policy or criteria, product demand, materials and parts availability, and product safety. In general, the effect of an increase in the designed quality level will increase the cost at an exponential rate. On the other hand, the value of the product increases at a decreasing rate. The rate of increase approaches zero beyond a certain designed quality level. Quality of Conformance: Quality of conformance requires that the manufactured product must meet the standards selected in the design phase. This would involve defect prevention, defect finding, and defect analysis and rectification. Defect prevention is accomplished using statistical process control techniques. Defects are usually located using inspection, test, and statistical analysis of data from the process. Once the sources or causes for the presence of defects are determined, then corrective measures or actions are taken accordingly. 1

2 2 PRODUCT AND PROCESS DESIGN FOR QUALITY, ECONOMY AND RELIABILITY Quality of Performance: Quality of performance focuses on how well the product performs when put to use. Quality of performance is a function of both quality of design and the quality of conformance. If a product does not meet the specified expectations, then adjustments are to be made in the design or conformance phase. Reliability is described as quality in the time dimension. Reliability of an item or a product is defined as the probability that the item or the product will perform satisfactorily for a specified period of time under a stated set of use conditions. An item must also operate satisfactorily for an acceptable period of time in the field application for which the item is intended. This definition of reliability stresses the following four elements: probability, performance requirements, time, and use conditions. Probability is the likelihood of an event s occurrence or nonoccurrence. The value of probability is between 0 and 1. Performance requirements clearly define or describe what is considered to be satisfactory operation. Time is the period during which satisfactory performance is expected, and use conditions to describe the environmental conditions under which the item is expected to function. To ensure customer satisfaction in the performance phase, measures to improve reliability in the design stage need to be addressed. In order to determine the reliability of a component, product or process, improvement is stressed to understand its design functionality. Invariably, the functionality relating to the concept of failure rate needs to be understood. A failure rate is a measure of the number of malfunctions occurring per unit of time. Most products, involve many components and require calculating the system reliability. Once designed and produced most components or products go through three distinct phases from product inception to wearout. They are the debugging phase, the chance-failure phase, and the wear-out phase as shown in Fig This curve is often referred to as the bathtub curve. Figure 1.1 is a typical life-cycle curve or the life-characteristic curve showing the failure rate as a function of increasing age (hours/cycles). The debugging phase is also known as the early-mortality phase or the burn-in period. This phase shows a rapid decrease in the failure rate due to the fact that the initial problems found during the course of prototype testing are fixed. This phase stabilizes at an Burn-in phase or Early mortality period or Debugging phase Useful life period or Chance-failure phase End of life period or Wear-out phase Failure rate ( ) t 1 t 2 Increasing age (Hours/Cycles) Fig. 1.1 A Typical Life-cycle Curve (Bathtub Curve).

3 INTRODUCTION 3 approximate value of time t 1 when the weak units have died out as shown in Fig This may be the result of design compromises or flaws due to faulty workmanship, transportation damage or installation or setup errors. This initial failure rate is usually found in new components, products or systems. Examples of these failures are: poor welds, seals, solder joints, contamination on surfaces or in materials, voids, cracks in insulation or coatings, and chemical impurities in metals etc. These early failures can be avoided by improving the manufacturing processes or in design phase itself. These early failures are discovered during in-process and final tests, life tests, environmental tests and process audits. During the chance-failure phase or the useful-life period, failures occur randomly and independently. The failure rate is constant and corresponds to the useful life of the component or the product. This period is characterized mainly by the occurrence of stress related failures. The exponential failure distribution is commonly used to approximate the time period. This period depends on the component, product or process and is considered the most significant period for reliability prediction and assessment activities. Humidity, vibration, shock and altitude contribute to the failure of components, products or systems. Point t 2 in Fig. 1.1 indicates the end of useful life or the start of wear out. Beyond this point, the failure rate increases rapidly. In the wear out phase or the end-of-life period, an increase in the failure rate is noticed. In this situation, components or products or systems age and wear out at the end of their useful life. When the components, products or systems failure rate due to wear out becomes unacceptably high, replacement, or repair of that component or product or system should be made. Wear out failures are mainly due to deterioration of the design strength of the item as a consequence of operation and exposure to environmental fluctuations. Some of the chemical or physical phenomena causing the deterioration of the design strength of the product or component are corrosion or oxidation, insulation breakdown or leakage, frictional wear or fatigue, shrinkage and cracking in plastic materials and ironic migration of metals in vacuum or on surfaces. Reliability is an inherent attribute of a system. The reliability level is established at the design phase. The designer in order to engineer reliability into products or processes during its basic design stage requires design data, guidelines for safety, mission, maintenance and cost factors together with basic elements of concepts of reliability, engineering, system engineering and cost effectiveness. 1.2 RELATIONSHIP BETWEEN RELIABILITY DESIGN AND COST Design to cost represents a constraint added to the task of designing a system or component, which will meet performance, reliability, maintainability and cost goals. This means that during design stage one must aim at a balanced design, which will (1) maximize performance within unit cost goals and (2) minimize support cost in order to minimize life-cycle costs. A design that minimizes support cost involves the application of reliability principles during the design phase. Life cycle cost represents all costs incurred from the point at which a decision is made to acquire a system through operational life and eventual disposal of the system. A total life cycle cost is represented by costs collected in two categories: (1) system acquisition costs, and (2) logistics and support costs. The total life cycle cost can be expressed as LCC = AC + LSC...(1.1)

4 4 PRODUCT AND PROCESS DESIGN FOR QUALITY, ECONOMY AND RELIABILITY where, LCC = life cycle cost AC = acquisition cost LSC = logistic support cost Acquisition cost elements include design and development (basic engineering, test and evaluation, experimental tooling, system management), manufacturing and quality engineering, fabrication, production tooling, quality control, test equipment, facilities, initial spares, and training. The major elements comprising the logistic and support cost include spares, personnel and training, overhaul and lower echelon maintenance facilities, and logistic factors. 1.3 RELIABILITY ASSESSMENT There are three steps used in the assessment of the reliability of a system. These steps are as follows: 1. Development of a reliability model based on system (design) functionality The developed model should be comprehensive enough to represent the main operational and other features of the system. The validity of the assumptions should be checked carefully. The developed model represents subsystems or subunits, with individual models and structural diagrams interconnected to emulate the overall behavior of the complete system under study. It is recommended to model the system into several blocks that are functionally independent of one another if possible. 2. Analyze the model The analysis of the model includes the determination of the reliability performance measures from the block diagrams and the corresponding reliability parameters and functions. Generally, probabilistic and combinatorial aspects of the system reliability and approximate methods are used in this step. 3. Evaluation and interpretation of results If the results obtained are not accurate and precise enough, the statistical techniques are used to establish their confidence intervals or significance levels. The validation of the model results can be accomplished by comparisons with data from field tests for similar systems or the same system. The determination of the system reliability also depends on a variety of economic and other considerations. 1.4 SCOPE AND ORGANIZATION OF THE BOOK Noting that the role of management is to plan and organize activities that effectively apply and control the use of necessary resources, in order to achieve desired outcomes, the objectives of this text are established so that readers may learn methods by which this may be accomplished, in context with the activities of design and manufacturing. Particular emphasis is placed upon the creation of reliable and cost-effective products. Specific objectives for learning are as follows: 1. To understand the techniques for planning projects and the methods by which the critical functions of design and manufacturing may be unified in order to achieve a design activity that smoothly evolves into an efficient manufacturing process in which critical considerations may be concurrently addressed to the full capability of all necessary resources. The expected learning outcomes are:

5 INTRODUCTION 5 (a) How to plan project activities? (b) How to plan cross-functional activities to achieve an efficient concurrent engineering process? (c) To understand the process and methodology for functional and conceptual design. 2. To learn methods for assessing the progress of on-going activities and instituting actions to control them. The expected learning outcomes are: (a) When and how to apply the design review process? (b) How to initiate and control cross-functional design activities? 3. To learn and apply appropriate analytical and experimental methods leading to the creation of reliable and robust products. The expected learning outcomes are: (a) How to apply effective methods of concept formulations? (b) How to apply Quality Function Deployment (QFD)? (c) How to access and improve manufacturing process capability? (d) How to affect Robust Design using orthogonal arrays in Design of Experiment techniques? 4. To learn and apply appropriate procedures for assuring the cost effectiveness of new products. The expected learning outcomes are: (a) How to treat cost as explicit design criteria? (b) How cost estimation is accomplished? (c) How to apply the Loss Function to assure that quality is not compromised? Chapter 1: Introduction This introductory chapter provides an overview of quality and reliability engineering techniques, design, the relationship between reliability and cost, reliability assessment, and the scope and organization of the book. Chapter 2: Basic Probability and Statistics This chapter introduces the reader to the basic concepts and definitions, population and sample, types of variables, graphical representation of qualitative and quantitative data, numerical summary measures, measures of central tendency for ungrouped data (mean, median and mode), measures of dispersion for ungrouped data (range, variance and standard deviation), mean, variance and standard deviation for grouped data, measures of position including quartiles, percentiles and box plot. The basics on probability, events (simple and compound), Venn diagram, tree diagram, approaches to probability (classical, relative, frequency concept of probability, subjective probability, marginal probability and conditional probability) are presented. Special multiplication rule and Baye s Formula are also briefly presented. Random variables (both discontinuous and continuous) and their mean and standard deviation are discussed. Permutations and combinations are defined briefly. Discrete probability distributions (hypergeometric, binomial and Poisson distributions) and their mean and standard deviations are derived. Continuous probability distribution, namely, the normal distribution, its properties, mean and variance and the standard normal distribution are presented. Approximate probability distributions are also presented. They include binomial approximation to the hyper-geometric, Poisson approximate to the binomial and normal approximation to the binomial are briefly discussed. Chebyshev s theorem and empirical rule for distribution are presented.

6 6 PRODUCT AND PROCESS DESIGN FOR QUALITY, ECONOMY AND RELIABILITY Chapter 3: Product and Process Design This chapter introduces a number of topics, such as Important Approaches in Product Development, Stages in Product Development Process, Tools and Techniques used in Product Development, Technical Risk Assessment in Product Development, Analysis of Customer Needs and Product Development, Common Approaches for Customer Needs Analysis, Conceptual Design Stage, Detailed Design including Design Analysis, Modeling and Simulation, Test and Evaluation, and Manufacturing. This chapter discusses in detail the various aspects of product and process design. In view of critical importance of product development and its contribution to a company s ability to succeed in a fiercely competitive market of a global economy, it is essential that the designers use a number of approaches at different stages of product development. Several tools and techniques commonly used in this context are described. Comparisons between the traditional serial engineering and simultaneous or concurrent engineering are clearly indicated. Technical risk assessment, a critical issue at product and process design, is emphasized in the approaches mentioned, and common approaches for customer needs analysis are described in detail. The reasons for forming design teams when the design is complex requiring inter-disciplinary approach are mentioned. Various stages in product development are mentioned and explained in detail. Highlighting the important aspects and difficulties, and problems in the conceptual design stage, the activities in detailed design, such as modeling and simulation as well as test and evaluation are elaborately discussed. Different manufacturing tools and techniques as practised in modern organizations are briefly presented in this chapter. Chapter 4: Quality Principles in Design This chapter discusses the various principles that have been introduced and practised by organizations worldwide to design, produce, and maintain quality of products and services. Emphasizing the importance of quality in engineering design, the evolution of quality over the years in modern organizations is discussed, and the concept of quality loop and its elements, from marketing through production to disposal, are explained with identification of qualityrelated activities at all elements. Comparing an inspection-based quality control with a prevention-based quality control, and elaborating the systems approach for quality problem solving at all three aspects quality of design, of conformance, and of performance, several quality principles for product development, such as extended process, customer-driven improvement cycle, constancy and consistency of purpose for quality improvement, rules for inspection, principles of supplier selection, process improvement cycle, variability reduction including loss function, and principles of zero defects are discussed in this chapter. Basic issues related to Taguchi s concept of quality engineering, Juran s quality trilogy process, and Crosby s absolutes of quality management, that are useful for creation and management of both product and process quality are presented in the context of quality control and improvement in modern business and manufacturing organizations. Chapter 5: Engineering Economic Analysis In this chapter we consider the subject of engineering economic analysis, with particular emphasis on economic analysis in design and manufacturing. Economic analysis involves techniques for comparing and making decisions between alternatives on the basis of monetary and economic objectives. With the ever increasing complexity of our manufacturing and

7 INTRODUCTION 7 industrial technology, economic decision-making is becoming more critical and essential. In addition, investment decisions are important in determining the success or failure and profitability of a firm. Engineering economic decisions between alternatives can be made by the engineer or manager of technology considering options in the design of components, systems, facilities or man-machine systems. However, considering a number of investment opportunities and alternatives within each opportunity, best makes these decisions. Our objectives are the following: 1. The fundamental concepts involving the time value of money. 2. Various economic measures for determining a projects worth. The measures considered are the annual worth, future worth, present worth, rates of return, and payback period. 3. Comparing investment alternatives, sensitivity analysis and replacing capital assets. 4. Incorporation of depreciation allowances and income taxes in economic analyses. 5. Benefit cost analysis for the economic analysis of projects. 6. Profitability of investments. 7. Sensitivity and break-even analysis. 8. Capitalized cost analysis. 9. Uncertainty and risk in economic analysis. Chapter 6: Cost Evaluation The American Association of Cost Engineers (AACE) defines cost engineering as that area of engineering practice where engineering judgment and experience are utilized in the application of scientific principles and techniques to the problems of cost estimation, cost control and profitability. Cost estimation is a complex process and requires knowledge of principles of engineering, materials, manufacturing processes, quality control and inspection methods, product and environmental safety, repair and servicing and principles of costing. Cost estimation is an important aspect of the product evaluation process. It is advisable to generate a cost estimate early in the design process in order to compare the product design with original objectives. The design of new components or products requires cost estimates from scratch while redesigns preliminary cost estimates will serve the purpose as the current costs are known. The design engineer shares the responsibility of generating the cost of manufactured products or components and selling prices of the products or components along with the costestimating department. Cost is next to performance in importance. Lowest cost design stands a good chance to be successful in a free market place. In this chapter, we consider the subject of economy, with particular emphasis on cost evaluation in design and manufacturing. The identification of the elements of costs, general concepts of cost evaluation and some of the more generally accepted cost evaluation methods and models are described. Chapter 7: Design for Reliability Predictions and Models Although it is possible in some cases to develop failure models based on the mechanics of failure, the procedure is rather complex and needs a considerable amount of study and analysis. Four reliability functions are: the failure density function f(t), hazard function (t), failure distribution function Q(t) and reliability function R(t) were defined. They were developed as

8 8 PRODUCT AND PROCESS DESIGN FOR QUALITY, ECONOMY AND RELIABILITY limiting cases of the respective p-linear functions constructed using catastrophic failure data. The mean time to failure (MTTF), median time to failure and average failure rate over time interval were introduced and their determination using reliability functions was presented. Both constant failure rate (CFR) models and time-dependent failure models were presented and discussed. Complex systems are decomposed into functional entities composed of components, units, and subsystems for the purpose of reliability analysis. Combinational aspects of reliability analysis are used to connect the components in series, parallel, series-parallel or meshed structures, or in any combination of these. Probability concepts are applied to determine the reliability of systems in terms of the reliabilities of its subsystems. Reliability allocation methods including the Aeronautical Radio Inc. (ARINC) method and the Advisory Group on Reliability of Electronic Equipment (AGREE) methods were presented and discussed. Fault trees, which are used to analyze complex systems, are presented. Chapter 8: Quality by Experimental Design This chapter discusses the fundamental concepts of experimental design in the context of everincreasing demand of improved quality in products and services by the customers. Highlighting the important features and terminologies in experimental design and its uses and advantages, this chapter explains in detail the traditional experimental designs, such as completely randomized design, randomized block design, and Latin square design. The procedure of measuring the main and interaction effects on the response or output variable in an experiment is clearly described. The evaluation process using ANOVA procedures in this context is illustrated with examples. The procedures and significance of conducting factorial experiment are presented in this chapter. While a full factorial experiment represents all possible treatment combinations of the factors considered, it may not be desirable because of time and resource constraints in many situations. A fractional factorial experiment, which is a subset of the full factorial design, selects the treatment combinations in such a way that the desirable effects can be estimated. For factorial experiments, the role of contrasts including orthogonal contrasts in estimating the treatment effects is explained in detail. The procedure of blocking by using the principle of confounding to increase the precision of the experiment is illustrated with a number of examples. The procedures for selecting the fractional replicates of the full factorial design to reduce the size of the experiment are also presented in this chapter. Overall, the experimental designs, as they are used in achieving the objective of improving and sustaining the quality of products and processes with reduced cost, are discussed at length in this chapter. Chapter 9: Robust Design and Taguchi Methods Taguchi has made a significant contribution in quality improvement and statistical methods. Taguchi s quality improvement activities which include product and process design provide a system to develop functional specifications, incorporate those specifications into a product and/or process and optimize the system to surpass the desired specifications. Quality engineering has the objective of designing quality into every product and corresponding process. Quality engineering directs quality improvement efforts from the manufacturing process to the design phase and hence is often called as an off-line quality control method. The techniques of statistical process control that are discussed in Chapter 8 are referred to as on-line quality control methods. Off-line methods reduce product development and lifetime costs and improve product manufacturability. Taguchi method seeks to minimize the effects of noise and to determine the optimal level of the important controllable factors based on the concept of robustness. In

9 INTRODUCTION 9 Taguchi s method, quality is measured by the deviation of a characteristic from its target value. Uncontrollable factors also called as noise cause these deviations and thereby lead to a loss. A loss function is defined for this deviation. Thus, Taguchi s method seeks to create a product/process design that is insensitive to all possible combinations of the uncontrollable noise factors and at the same time is effective and cost efficient as a result of setting the key controllable factors at certain levels. Cost is a key consideration in Taguchi s method, with the objective of obtaining the best possible design at the lowest possible cost. 1.5 FURTHER READING This book is intended as an introduction to the vast subject of design for quality, economy and reliability. Many excellent books and articles are available that deal with individual topics or branches of quality, economy, reliability, design, applications and related fields at varying levels of treatment. The list of references at the end of each chapter of this book is extensive, although not necessarily exhaustive, and will serve the reader well to gain further knowledge about and insight into the subject matter.