1 Chapter 8 Design for Six Sigma

Design for Six Sigma (DFSS) represents a set of tools and methodologies used in product development for ensuring that goods and services will meet customer needs and achieve performance objectives and that the processes used to make and deliver them achieve six sigma capability. Design for Six Sigma (DFSS) represents a set of tools and methodologies used in product development for ensuring that goods and services will meet customer needs and achieve performance objectives and that the processes used to make and deliver them achieve six sigma capability. 22

DFSS Methodology: DMADV Define – establish goals Define – establish goals Measure – identify voice of the customer and define CTQ measures Measure – identify voice of the customer and define CTQ measures Analyze – propose and evaluate high-level design concepts Analyze – propose and evaluate high-level design concepts Design – design the details of the product and processes used to produce it Design – design the details of the product and processes used to produce it Verify – ensure that the product performs as expected and meets customer requirements Verify – ensure that the product performs as expected and meets customer requirements 3

Features of DFSS A high-level architectural view of the design A high-level architectural view of the design Use of CTQs with well-defined technical requirements Use of CTQs with well-defined technical requirements Application of statistical modeling and simulation approaches Application of statistical modeling and simulation approaches Predicting defects, avoiding defects, and performance prediction using analysis methods Predicting defects, avoiding defects, and performance prediction using analysis methods Examining the full range of product performance using variation analysis of subsystems and components Examining the full range of product performance using variation analysis of subsystems and components 4

Concept Development applying scientific, engineering, and business knowledge to produce a basic functional design that meets both customer needs and manufacturing or service delivery requirements. Concept development – the process of applying scientific, engineering, and business knowledge to produce a basic functional design that meets both customer needs and manufacturing or service delivery requirements. 5

Innovation Innovation involves the adoption of an idea, process, technology, product, or business model that is either new or new to its proposed application. Innovation involves the adoption of an idea, process, technology, product, or business model that is either new or new to its proposed application. The outcome of innovation is a discontinuous or breakthrough change that results in new and unique goods and services that delight customers and create competitive advantage. The outcome of innovation is a discontinuous or breakthrough change that results in new and unique goods and services that delight customers and create competitive advantage. 6

Types of Innovation 1. An entirely new category of product (for example, Twitter) 2. First of its type on the market in a product category already in existence (for example, the DVD player) 3. A significant improvement in existing technology (for example, the Blu-ray disc technology) 4. A modest improvement to an existing product (for example, the latest iPad) 7

Creativity Creativity is seeing things in new or novel ways. Creativity is seeing things in new or novel ways. Creativity tools, such as brainstorming and “brainwriting,” are designed to help change the context in which one views a problem or opportunity, thereby leading to fresh perspectives. Creativity tools, such as brainstorming and “brainwriting,” are designed to help change the context in which one views a problem or opportunity, thereby leading to fresh perspectives. 8

Understanding the Voice of the Customer What is the product (good or service) intended to do? What is the product (good or service) intended to do? Technical requirements, sometimes called design characteristics, translate the voice of the customer into technical language, specifically into measures of product performance. Technical requirements, sometimes called design characteristics, translate the voice of the customer into technical language, specifically into measures of product performance. 9

Design Development Design development - the process of applying scientific, engineering, and business knowledge to produce a basic functional design that meets all CTQs – both customer needs and manufacturing or service delivery requirements. Design development - the process of applying scientific, engineering, and business knowledge to produce a basic functional design that meets all CTQs – both customer needs and manufacturing or service delivery requirements. Design development usually starts with a high-level design and then moves toward more detail design of components or subsystems. Design development usually starts with a high-level design and then moves toward more detail design of components or subsystems. 10

Axiomatic Design Axiomatic design (developed by Dr. Nam Suh at MIT) is based on the premise that good design is governed by laws similar to those in natural science. Axiomatic design (developed by Dr. Nam Suh at MIT) is based on the premise that good design is governed by laws similar to those in natural science. 1. Independence Axiom: good design occurs when the functional requirements of the design are independent of one another. 2. Information Axiom: good design corresponds to minimum complexity. 11

Quality Function Deployment (QFD) QFD is a planning process to guide the design, manufacturing, and marketing of goods by integrating the voice of the customer throughout the organization. QFD is a planning process to guide the design, manufacturing, and marketing of goods by integrating the voice of the customer throughout the organization. Through QFD, every design, manufacturing, and control decision is made to meet the expressed needs of customers. Through QFD, every design, manufacturing, and control decision is made to meet the expressed needs of customers. 12

The House of Quality 13

Building the House of Quality 1. Identify customer requirements. 2. Identify technical requirements. 3. Relate the customer requirements to the technical requirements. 4. Conduct an evaluation of competing products or services. 5. Evaluate technical requirements and develop targets. 6. Determine which technical requirements to deploy in the remainder of the production/delivery process. 14

Example: Designing a Fitness Center Identify customer requirements 15

Example Identify technical requirements 16

Example Relate customer requirements to technical requirements 17

Example Conduct competitive evaluation 18

Example Develop deployment targets 19

The Four Linked Houses of Quality 20

Detailed Design and Analysis Manufacturing specifications consist of nominal dimensions and tolerances. Manufacturing specifications consist of nominal dimensions and tolerances. –Nominal refers to the ideal dimension or the target value that manufacturing seeks to meet. –Tolerance is the permissible variation, recognizing the difficulty of meeting a target consistently. 21

Tolerance Design Tolerance design involves determining the permissible variation in a dimension. Tolerance design involves determining the permissible variation in a dimension. –Narrow tolerances tend to raise manufacturing costs but they also increase the interchangeability of parts within the plant and in the field, product performance, durability, and appearance. –Wide tolerances increase material utilization, machine throughput, and labor productivity, but have a negative impact on product characteristics 22

Traditional Economic View of Conformance to Specifications 23

The Taguchi Loss Function Taguchi measured quality as the variation from the target value of a design specification, and then translated that variation into an economic “loss function” that expresses the cost of variation in monetary terms. Taguchi measured quality as the variation from the target value of a design specification, and then translated that variation into an economic “loss function” that expresses the cost of variation in monetary terms. Taguchi assumes that losses can be approximated by a quadratic function so that larger deviations from target correspond to increasingly larger losses. Taguchi assumes that losses can be approximated by a quadratic function so that larger deviations from target correspond to increasingly larger losses. 24

Nominal-Is-Best Loss Function 25

Expected Loss A measure of variation that is independent of specification limits, showing the average loss over the distribution of output A measure of variation that is independent of specification limits, showing the average loss over the distribution of output Expected loss = k(  2 + D 2 ) Expected loss = k(  2 + D 2 ) where  2 is the process variation and D is the deviation from the target. where  2 is the process variation and D is the deviation from the target. 26

Design for Manufacturability (DFM) Design for manufacturability (DFM) is the process of designing a product for efficient production at the highest level of quality. Design for manufacturability (DFM) is the process of designing a product for efficient production at the highest level of quality. DFM is intended to prevent DFM is intended to prevent –product designs that simplify assembly operations but require more complex and expensive components, –designs that simplify component manufacture while complicating the assembly process, and –designs that are simple and inexpensive to produce but difficult or expensive to service or support 27

Design Reviews Design review – a structured review of design progress intended to stimulate discussion, raise questions, and generate new ideas and solutions to help designers anticipate problems before they occur Design review – a structured review of design progress intended to stimulate discussion, raise questions, and generate new ideas and solutions to help designers anticipate problems before they occur 28

DFMEA Design failure mode and effects analysis (DFMEA) – identification of all the ways in which a failure can occur, to estimate the effect and seriousness of the failure, and to recommend corrective design actions. 29

DFMEA Elements Failure modes Failure modes Effect of failures on customers Effect of failures on customers Severity, likelihood of occurrence, and detection rating (risk priority) Severity, likelihood of occurrence, and detection rating (risk priority) Potential causes of failure Potential causes of failure Corrective actions or controls Corrective actions or controls 30

Scoring Rubric for DFMEA 31

32 Reliability Prediction Reliability - the ability of a product to perform as expected over time Reliability - the ability of a product to perform as expected over time –Formally defined as the probability that a product, piece of equipment, or system performs its intended function for a stated period of time under specified operating conditions

Types of Failures Functional failure – failure that occurs at the start of product life due to manufacturing or material detects Functional failure – failure that occurs at the start of product life due to manufacturing or material detects Reliability failure – failure after some period of use Reliability failure – failure after some period of use 33

Types of Reliability Inherent reliability – determined by product design Inherent reliability – determined by product design Achieved reliability – observed during use Achieved reliability – observed during use 34

Mathematics of Reliability Reliability is determined by the number of failures per unit time during the duration under consideration (called the failure rate,λ). Reliability is determined by the number of failures per unit time during the duration under consideration (called the failure rate,λ). –For items that must be replaced when a failure occurs, the reciprocal of the failure rate (having dimensions of time units per failure) is called the mean time to failure (MTTF). –For repairable items, the mean time between failures (MTBF) is used. 35

Computing the Failure Rate 36

Product Life Characteristics Curve Many electronic components commonly exhibit a high, but decreasing, failure rate early in their lives, followed by a period of a relatively constant failure rate, and ending with an increasing failure rate. Many electronic components commonly exhibit a high, but decreasing, failure rate early in their lives, followed by a period of a relatively constant failure rate, and ending with an increasing failure rate. 37

Reliability Function The reliability function, R(T), characterizes the probability of survival to time T. The reliability function, R(T), characterizes the probability of survival to time T. Properties: Properties: 1. R(0) = 1 2. As T becomes larger, R(T) is non-increasing 3. R(T) = 1 - F(T), where F(T) is the cumulative probability distribution of failures 38

Exponential Reliability Exponential probability density function of failures Exponential probability density function of failures f(t) = e - t for t ≥ 0 Probability of failure from (0, T) Probability of failure from (0, T) F(t) = 1 – e - T F(t) = 1 – e - T Probability of failure during the interval (t 1, t 2 ) Probability of failure during the interval (t 1, t 2 ) F(t 2 ) - F(t 1 ) = e -λ(t2 –t1) Reliability function (probability of survival) Reliability function (probability of survival) R(T) = 1 – F(T) = e - T R(T) = 1 – F(T) = e - T 39

Hazard Function The hazard function is the probability that an item that has not failed up to time t will fail immediately after time t. The hazard function is the probability that an item that has not failed up to time t will fail immediately after time t. For the exponential distribution, the hazard function is For the exponential distribution, the hazard function is 40

System Reliability Series system: all components must function or the system will fail. Series system: all components must function or the system will fail. the reliability of the system is the product of the individual reliabilities the reliability of the system is the product of the individual reliabilities 41

Series Systems with Exponential Reliability 42

System Reliability Parallel system: uses redundancy. Parallel system: uses redundancy. The system will successfully operate The system will successfully operate as long as one component functions. as long as one component functions. The reliability is calculated as The reliability is calculated as If all components have identical reliabilities R, then If all components have identical reliabilities R, then 43

Series-Parallel Systems To compute the reliability of systems with both series and parallel components, decompose the system into smaller series and/or parallel subsets of component, compute the reliabilities of these subsets, and continue until you are left with a simple series or parallel system. To compute the reliability of systems with both series and parallel components, decompose the system into smaller series and/or parallel subsets of component, compute the reliabilities of these subsets, and continue until you are left with a simple series or parallel system. 44

Series-Parallel Example 45

Design Optimization Robust design refers to designing goods and services that are insensitive to variation in manufacturing processes and when consumers use them. Robust design refers to designing goods and services that are insensitive to variation in manufacturing processes and when consumers use them. –Robust design is facilitated by design of experiments and alternative Taguchi methods

Design for Reliability Reliability requirements are determined during the product design phase. Reliability requirements are determined during the product design phase. Techniques used to improve designs and optimize reliability include: Techniques used to improve designs and optimize reliability include: –Standardization –Redundancy –Physics of failure

Design Verification Design verification is necessary to ensure that designs meet customer requirements and can be produced to specifications. Design verification is necessary to ensure that designs meet customer requirements and can be produced to specifications. –The purpose of verification is to validate product and process designs and to prepare procedures and documentation for full-scale production rollout. 48

Reliability Evaluation Life testing – running devices until they fail, is designed to measure the distribution of failures to better understand and eliminate their causes. Life testing – running devices until they fail, is designed to measure the distribution of failures to better understand and eliminate their causes. Accelerated life testing involves overstressing components to reduce the time to failure and find weaknesses. Accelerated life testing involves overstressing components to reduce the time to failure and find weaknesses. Environmental testing involves testing products for temperature, shock-resistance, and other environmental conditions. Environmental testing involves testing products for temperature, shock-resistance, and other environmental conditions. Burn-in, (component stress testing), involves exposing integrated circuits to elevated temperatures in order to force latent defects to occur. Burn-in, (component stress testing), involves exposing integrated circuits to elevated temperatures in order to force latent defects to occur. 49

Simulation Simulation is an approach to building a logical model of a real business system and experimenting with it to obtain insight about the behavior of the system or to evaluate the impact of changes in assumptions or potential improvements to it. Simulation is an approach to building a logical model of a real business system and experimenting with it to obtain insight about the behavior of the system or to evaluate the impact of changes in assumptions or potential improvements to it. –Process simulation models the dynamics and behavior over time of interacting elements in a system such as a manufacturing facility or a call center. –Monte-Carlo simulation is based on repeated sampling from probability distributions of model inputs to characterize the distributions of model outputs, usually in a spreadsheet environment. 50