Transcript The Scope and Language of Operations Management
Chapter 12
Design for Six Sigma
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DFSS Activities
Concept development , determining product functionality based upon customer requirements, technological capabilities, and economic realities Design development or delivery , focusing on product and process performance issues necessary to fulfill the product and service requirements in manufacturing Design optimization “robust” design , seeking to minimize the impact of variation in production and use, creating a Design verification level , ensuring that the capability of the production system meets the appropriate sigma
Key Idea
Like Six Sigma itself, most tools for DFSS have been around for some time; its uniqueness lies in the manner in which they are integrated into a formal methodology, driven by the Six Sigma philosophy, with clear business objectives in mind.
Tools for Concept Development
Concept development requirements. – 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 – Quality function deployment (QFD) – Concept engineering
Key Idea
Developing a basic functional design involves translating customer requirements into measurable technical requirements and, subsequently, into detailed design specifications.
Quality Function Deployment
technical requirements component characteristics process operations quality plan 6
Key Idea
QFD benefits companies through improved communication and teamwork between all constituencies in the value chain, such as between marketing and design, between design and manufacturing, and between purchasing and suppliers.
House of Quality
Interrelationships Technical requirements Customer requirement priorities Voice of the customer Relationship matrix Technical requirement priorities Competitive evaluation 8
Building the House of Quality
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Identify customer requirements.
Identify technical requirements.
Relate the customer requirements to the technical requirements.
Conduct an evaluation of competing products or services.
Evaluate technical requirements and develop targets.
Determine which technical requirements to deploy in the remainder of the production/delivery process.
Concept Engineering
Understanding the customer’s environment.
Converting understanding into requirements. Operationalizing what has been learned.
Concept generation.
Concept selection.
Tools for Design Development
Tolerance design Design failure mode and effects analysis Reliability prediction
Key Idea
Manufacturing specifications consist of nominal dimensions and tolerances. Nominal manufacturing seeks to meet; of meeting a target consistently.
refers to the ideal dimension or the target value that tolerance is the permissible variation, recognizing the difficulty
Tolerance Design
Determining permissible variation in a dimension Understand tradeoffs between costs and performance
Key Idea
Tolerances are necessary because not all parts can be produced exactly to nominal specifications because of natural variations (common causes) in production processes due to the “5 Ms”: men and women, materials, machines, methods, and measurement.
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.
Reliability Prediction
Reliability – Generally defined as the ability of a product to perform as expected over time – Formally defined as the product, piece of equipment, or system performs its intended function for a stated period of time probability that a under specified operating conditions 17
Types of Failures
Functional failure detects – failure that occurs at the start of product life due to manufacturing or material Reliability failure – failure after some period of use
Types of Reliability
Inherent reliability product design Achieved reliability during use – predicted by – observed
Reliability Measurement
Failure rate ( l ) – number of failures per unit time Alternative measures – Mean time to failure – Mean time between failures
Cumulative Failure Rate Curve
Key Idea
Many electronic components commonly exhibit a high, but decreasing, failure rate early in their lives (as evidenced by the steep slope of the curve), followed by a period of a relatively constant failure rate, and ending with an increasing failure rate.
Failure Rate Curve
“Infant mortality period”
Average Failure Rate
Reliability Function
Probability density function of failures f(t) = l e l t for t > 0 Probability of failure from (0, T) F(t) = 1 – e l T Reliability function R(T) = 1 – F(T) = e l T
Series Systems
1 2 R S = R 1 R 2 ... R n n 26
Parallel Systems
1 2 n R S = 1 - (1 - R 1 ) (1 - R 2 )... (1 - R n ) 27
Series-Parallel Systems
R A A R B B C R C R D D C R C Convert to equivalent series system R A A R B B C’ R D D R C’ = 1 – (1-R C )(1-R C )
Tools for Design Optimization
Taguchi loss function Optimizing reliability
Key Idea
Design optimization includes setting proper tolerances to ensure maximum product performance and making designs robust environment.
, that is, insensitive to variations in manufacturing or the use
Loss Functions
Traditional View
loss no loss nominal tolerance loss
Taguchi’s View
loss loss 31
Taguchi Loss Function Calculations
Loss function: L(x) = k(x - T) 2 Example k(.020) 2 : Specification = .500 function is: .020. Failure outside of the tolerance range costs $50 to repair. Thus, 50 = . Solving for k yields k = 125,000. The loss L(x) = 125,000(x - .500) 2 Expected loss = k( 2 + D 2 ) where D is the deviation from the target.
Optimizing Reliability
Standardization Redundancy Physics of failure
Tools for Design Verification
Reliability testing Measurement systems evaluation Process capability evaluation
Key Idea
Design verification is necessary to ensure that designs will meet customer requirements and can be produced to specifications.
Reliability testing
Life testing Accelerated life testing Environmental testing Vibration and shock testing Burn-in (component stress testing)
Measurement System Evaluation
Whenever variation is observed in measurements, some portion is due to measurement system error. Some errors are systematic (called bias); others are random. The size of the errors relative to the measurement value can significantly affect the quality of the data and resulting decisions.
Metrology - Science of Measurement
Accuracy between an observed value and a standard - closeness of agreement Precision - closeness of agreement between randomly selected individual measurements
Repeatability and Reproducibility
Repeatability (equipment variation) variation in multiple measurements by an individual using the same instrument. – Reproducibility (operator variation) variation in the same measuring instrument used by different individuals -
Repeatability & Reproducibility Studies
Quantify and evaluate the capability of a measurement system – – – – Select m operators and n parts Calibrate the measuring instrument Randomly measure each part by each operator for r trials Compute key statistics to quantify repeatability and reproducibility
Spreadsheet Template
R&R Evaluation
Under 10% error - OK 10-30% error may be OK over 30% error - unacceptable
Key Idea
One of the most important functions of metrology is calibration —the comparison of a measurement device or system having a known relation-ship to national standards against another device or system whose relationship to national standards is unknown.
Process Capability
The range over which the natural variation of a process occurs as determined by the system of common causes Measured by the proportion of output that can be produced within design specifications 44
Types of Capability Studies
Peak performance study - how a process performs under ideal conditions Process characterization study process performs under actual operating conditions - how a Component variability study measurement system) - relative contribution of different sources of variation (e.g., process factors,
Process Capability Study
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Choose a representative machine or process Define the process conditions Select a representative operator Provide the right materials Specify the gauging or measurement method Record the measurements Construct a histogram and compute descriptive statistics: mean and standard deviation Compare results with specified tolerances
Process Capability
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specification natural variation
(c)
specification natural variation
(b)
specification natural variation
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specification natural variation
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Key Idea
The process capability index, Cp (sometimes called the process potential index), is defined as the ratio of the specification width to the natural tolerance of the process. Cp relates the natural variation of the process with the design specifications in a single, quantitative measure.
Process Capability Index
C C C p pu pl = UTL - LTL 6 = = UTL 3 m 3 m - LTL C pk = min{ C pl , C pu } 49
Spreadsheet Template