INTEGRATED MISSION SOLUTIONS DD(X ... - Raytheon

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“At it’s heart R6σ is about seeking perfection, looking current reality in the eye and then using appropriate tools to close the gap. R6σ in engineering is no different except perfection is defined by customer value, in terms of ever aggressive performance of our products and services. Taking a facts and data approach, using predictive tools, to quantifying current performance levels and then using these predictive techniques as a part of the engineering processes, as we strive to deliver solutions, is R6σ in engineering.” Jon W. McKenzie, Director Six Sigma Institute Design for Six Sigma Continued from page 21 Here’s an example of applying statistical design methods to a “problem” that was identified using a traditional design approach. Boresight Example: A traditional worse-case tolerance analysis indicated that all of the MK-47 sensors would require a mechanical alignment. Jeff Gilstrap, a senior system engineer from NCS, was brought in to do a boresight analysis. Jeff had recently attended the first session of the R6σ for Design Practitioner Track and saw an opportunity to use the Statistical Design Methods he learned in class to accomplish the following design objectives: • Determine if boresight requirements could be achieved with hard-mounted cameras and Laser Rangefinder (LRF) • Establish the optical and mechanical parts tolerances required to achieve boresight requirements. Jeff constructed a detailed model of the complete optical system and performed a Monte Carlo simulation with Six Sigma manufacturing tolerance distributions (vari- 22 summer 2003 DFSS (continued) ability) for all of the optical elements and mechanical part features. Fabrication process capabilities were obtained from PCAT. This model can now be reused or modified for similar applications. Using the model and the statistical methods from DFSS, Jeff was able to verify that: • Both cameras must be aligned at assembly due to wide tolerance ranges • The LRF could be hard-mounted, avoiding a costly alignment mechanism and procedure What if we had used statistical design methods from the beginning? Do we have the time NOT to use DFSS? Again, NO! Another DFSS technique that can be used to generate preliminary System and Product Design concepts is TRIZ. TRIZ, a Russian acronym for Theory of Inventive Problem Solving, is a philosophy and methodology for solving technical problems using inventiveness and creativity. TRIZ was developed by Genrich Altshuller and his colleagues in the former USSR starting in 1946, and is now being developed and practiced throughout the world. Stages 4 & 5: Detailed Design and System Integration, Test, Verification and Validation The body of DFSS resides in Stages 4 & 5. The design concepts are defined, requirements are clearly understood and have been allocated and the preliminary designs are complete. Now it is time for the detailed design work, with a strong focus on Producibility and Affordability. We continue to use the DFSS concepts and tools that we used in Stages 1 & 3, as appropriate. Other DFSS tools we might consider are Design For Manufacture and Assembly (DFMA), Design Of Experiments (DOE), Process Capability Analysis Tool (PCAT), Design To Cost (DTC) and Cost As an Independent Variable (CAIV), Capability Analysis, Test Optimization, Test Error Allocation, Combinatorial Design Methodology, Markov Chains, etc. It is in Detailed Design and System ITV&V that we achieve the balance between Product Performance, Affordability and Producibility that provides Customer Value and maximizes our profitability. I know what you’re thinking, “How on earth can you possibly expect me to use all of those tools and design a system in a reasonable amount of time?!” A common R6σ in Product Development is defined as our ability to predict and perform to our customer requirements, quantify variation and understand the source of that variation. There are four areas of interest to our customers and programs. Program Managers and Engineers must constantly evaluate these areas and balance with customer value to assure a successful execution of a program. Product Development Schedule – Our ability to plan and execute that plan in the development of products and services. Product Development Cost – Our ability to predict the cost of the development of the products or services and then perform to those predictions. Product Performance – Our ability to predict how our products will perform when fielded. The prediction is done on key technical parameters, often driven by identified risk on the program. Many times these predictions are done with Modeling and Simulation. Product Cost – Our ability to predict the cost of the production of a product or the operational and maintenance cost associated with the product. Design for Six Sigma specifically refers to the dimensions of Product Performance and Product Cost.
misconception is that we have to use all of the tools. Using all of the tools would take too long and cost too much. As a design engineer, you are expected to use the right tool at the right step of the process to provide the right amount of balance between Performance, Affordability and Producibility. This is a call that only you can make. So how do you make the right choices? When choosing the appropriate DFSS tools, your past experiences will play a huge role. But knowledge of the toolset that is available to you is also important. That is where learning new skills comes in. A Practitioner Track has been developed to help you integrate R6σ concepts and tools into the design process. The R6σ for Design Practitioner Track was developed for design engineers and R6σ Experts that are involved in the design process. In this session, the participant will learn about DFSS through discovery of new concepts, case studies and application through simulations and exercises. Our intent is to provide the skills and the con- View Point DFSS offers several key advantages to statistical analysis. • Better accuracy – use of simulation instead of estimation. Can specify inputs as distributions. Models more closely represent the real product. Worst case analysis typically results in over-design. • Greater insight – worst case and MRSS calculations yield no statistical data. • Greater analysis capability – improved sensitivity analysis, ability to easily change input parameters and obtain quick results for “what if “ scenarios. • Greater calculating power – spreadsheet-based analysis tools provide powerful and flexible calculation capability and more efficient management of large amounts of data and calculations. Jeff Gilstrap, senior principal systems engineer, NCS, Plano, Texas. text for engineering practitioners to recognize and apply appropriate R6σ tools in optimizing product design. This is a pull system, not a push. The R6σ for Design Practitioner Track is broken into two sessions. The first session (four days) focuses on Stages 1 & 3 and on the systems architects and systems engineers. The second session (four days) pertains to detailed design efforts. The first two days focus on detailed design of the hardware. The second two days focus on software design. Systems architects, engineers and R6σ Experts should plan to participate in all eight days. Detail designers should plan to participate in the first session and choose either the hardware or software piece of the second session for a total of seven days. For more information on the Design For Six Sigma Practitioner Track go to: http://homext.ray.com/sixsigma and click on the Six Sigma Practitioner Track Brochure icon. Our ultimate challenge as engineers is to “Predict and Perform”. R6σ, as deployed today, is very much a reactive improvement strategy. We find a problem and resolve it. We have to mature to a much more proactive approach by engaging early in the design. Our challenge is to prevent problems rather than fix them. Our ability to predict and then perform against those predictions forms the foundation of design excellence. Are you ready to accept this challenge? - Lynda Owens The More You Know About DFSS… References: “Engineering of Creativity: Introduction to TRIZ Methodology of Inventive Problem Solving”, Semyon Savransky, CRC Press LCC, 2002 “And Suddenly the Inventor Appeared”, Genrich Altshuller, Technical Innovation Center, 1996, 2nd ed. “Design For Six Sigma”, Creveling, C.M., J.L. Slutsky, and D. Antis, Jr., Prentice Hall PTR, 2003 To accept this challange, join the DFSS Community of Practice by contacting: Lynda Owens l-owens@raytheon.com Herrick Haenisch haenisch@raytheon.com DFSS General Information: R6σ Institute: Brian Morgan jbmorgan@raytheon.com IDS: Wayne Risas Wayne_E_Risas@raytheon.com IIS: Karl Arunski arunski@raytheon.com MS: Lou Vetoe lnveto@raytheon.com Debra Herrera Debra_S_Herrera@raytheon.com NCS: Lynda Owens l-owens@raytheon.com Richard Johnson r-johnson8@raytheon.com RAC: Otto Baierlein otto_baierlein@rac.ray.com RSL Derek Richardson Derek_R_Richardson@raytheon.com RTSC: Patty Smith smithp@indy.raytheon.com SAS: Nancy Fleischer nlfleischer@raytheon.com Tim Fitzgerald Tim_K_Fitzgerald@raytheon.com summer 2003 23
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INTEGRATED MISSION SOLUTIONS DD(X ... - Raytheon

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