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Design for Six Sigma - IDOV Methodology
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"DFSS and DMADV are NOT the same thing. At my company, DMADV is used to assist in developing new processes (and is light on statistics) whereas DFSS is used to optimize product designs before launch (and is heavy on statistics). All DMADV can be construed as DFSS, but not all DFSS is DMADV..."
DFSS Versus DMADV
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By Dr. David Woodford Design for Six Sigma (DFSS) can be accomplished using any one of many methodologies. IDOV is one popular methodology for designing products and services to meet six sigma standards. IDOV is a four-phase process that consists of Identify, Design, Optimize and Verify. These four phases parallel the four phases of the traditional Six Sigma improvement methodology, MAIC - Measure, Analyze, Improve and Control. The similarities can be seen below. Identify Phase
The Identify phase begins the process with a formal tie of design to Voice of the Customer. This phase involves developing a team and team charter, gathering VOC, performing competitive analysis, and developing CTQs. Crucial Steps:
Identify customer and product requirementsEstablish the business caseIdentify technical requirements (CTQ variables and specification limits)Roles and responsibilitiesMilestonesKey Tools:
QFD (Quality Function Deployment)FMEA (Failure Means and Effects Analysis)SIPOC (Supplier, Input, Product, Output, Customer product map)IPDS (Integrated Product Delivery System)Target CostingBenchmarkingDesign Phase
The Design phase emphasizes CTQs and consists of identifying functional requirements, developing alternative concepts, evaluating alternatives and selecting a best-fit concept, deploying CTQs and predicting sigma capability. Crucial Steps:
Formulate concept designIdentify potential risks using FMEAFor each technical requirement, identify design parameters (CTQs) using engineering analysis such as simulationRaw materials and procurement planManufacturing planUse DOE (design of experiments) and other analysis tools to determine CTQs and their influence on the technical requirements (transfer functions)Key Tools:
Smart simple designRisk assessmentFMEAEngineering analysisMaterials selection softwareSimulationDOE (Design of Experiments)Systems engineeringAnalysis toolsOptimize Phase
The Optimize phase requires use of process capability information and a statistical approach to tolerancing. Developing detailed design elements, predicting performance, and optimizing design, take place within this phase. Crucial Steps:
Assess process capabilities to achieve critical design parameters and meet CTQ limitsOptimize design to minimize sensitivity of CTQs to process parametersDesign for robust performance and reliabilityError proofingEstablish statistical tolerancingOptimize sigma and costCommission and startupKey Tools:
Manufacturing database and flowback toolsDesign for manufacturabilityProcess capability modelsRobust designMonte Carlo MethodsTolerancingSix Sigma toolsValidate Phase
The Validate phase consists of testing and validating the design. As increased testing using formal tools occurs, feedback of requirements should be shared with manufacturing and sourcing, and future manufacturing and design improvements should be noted. Crucial Steps:
Prototype test and validationAssess performance, failure modes, reliability, and risksDesign iterationFinal phase reviewKey Tools:
Accelerated testingReliability engineeringFMEADisciplined New Product Introduction (NPI)About The Author
David Woodford has a Ph.D. and a D.Sc from the University of Birmingham in England. He worked for GE in both the Turbine Technology Laboratory and in the Corporate R&D Center. From 1986 to 1994 he was Professor of Materials Engineering at Rensselaer Polytechnic Institute. He has published over one hundred and twenty papers in the general area of materials for energy conversion systems and has given numerous invited talks. Dr. Woodford is President, MPa, Inc. in Santa Barbara and Visiting Professor at the University of California at Santa Barbara.
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