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ME 350 – Lecture 21 – Feature Based Costing (FBC)

ME 350 – Lecture 21 – Feature Based Costing (FBC). Instructor: Dr. Mike L. Philpott Associate Professor of Mechanical & Industrial Engineering. FBC/DFM Background. 1990s DFMA software – stand alone software based on MTM standard times and empirical models (e.g. Boothroyd and Dewhurst)

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ME 350 – Lecture 21 – Feature Based Costing (FBC)

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  1. ME 350 – Lecture 21 – Feature Based Costing (FBC) Instructor: Dr. Mike L. Philpott Associate Professor of Mechanical & Industrial Engineering

  2. FBC/DFM Background • 1990s DFMA software – stand alone software based on MTM standard times and empirical models (e.g. Boothroyd and Dewhurst) • Designers needed to know cost early in design to do what-if analysis and explore alternative designs before expensive hard tooling decisions finalized • Advent of solid modeling with access to full solid definition of the part and assembly • Design to Cost (DTC) strategies in place, due to high overseas competition, but no practical tools • Need to know early if cost targets are being met - redesign if necessary before its too late.

  3. Feature Based Costing (FBC)TM A DFM Cad-based tool • Estimating cost directly from a part models geometric features • In real-time during CAD modeling with little to no extra time and without expert manufacturing knowledge • In an integrated environment with direct access to enterprise cost data (e.g. updated material cost, machine parameters, labor rates, overhead rates etc.)

  4. Feature Based Costing (FBC) Research • CAD-integrated feature recognition and extraction methodology to provide engineers with accurate real-time cost feedback during design. • Industry/University Collaborative research project: • UIUC / John Deere – 6 year duration - technology now being commercialized * 1. Cost Scripting Language 2. Parameterized machine, material, tooling and labor Database Supplier In-House Virtual Production Environments feature extraction algorithms Physics Based Mechanistic Manufacturing Process Models (cycle times -> cost) CAD Solid Model Geometric Cost Drivers Routing Engine Times and Costs Non-Geometric Cost Drivers User Optimum manufacturing sequence automatically derived from CAD Solid Model based on deterministic routing logic and Genetic Algorithms real-time cost feedback loop * “Integrated Real-Time Feature Based Costing (FBC),” U.S. Patent No. 7,065,420, June 20, 2006

  5. Feature Based Costing (FBC) Implementation • Novel algorithms are used to search for the sequence of processes and routings that minimizes the cost of manufacture of individual parts or assemblies of parts. • Integration with commercial CAD systems incl ProE, Catia, Inventor, NX, & Solidworks. • Commercialization Startup (www.aPriori.com) with user base now including: Deere, CAT, JLG, Eaton, Dana, Excel, AGCO, Polaris, Volvo Trucks, NMHG, Rolls Royce, Exmark… Integration to CAD Results at John Deere on Sample of 71 parts 1. Subbarao, G., M. L. Philpott, R. S. Schrader, and D. E. Holmes, “Feature Based Costing (FBC) of Welded Assemblies: A Genetic Approach,” Proceedings of IMECE’02 2002 ASME Congress & Exposition, New Orleans, LA, No. 17-22, 2002, IMECE2002-39425. 2. Philpott, M. L., E. A. Hiller, and D. E. Holmes , “Enterprise Cost Management: An Integration Methodology For New Product Introduction” Submitted to ASME Transactions: Journal of Computing & info Science in Engineering, (JCISE), Jan. 2005

  6. Target Cost Constraint Function Finance Acceptable product solution Fit Target Cost Constraint Cost as a True Parameter of Design (the 4th F ?) High Value to Customer Form Low Low High Profit to Company

  7. Cost Accounting Taxonomy Non-Recurring Costs Total Fully Burdened Cost

  8. Mechanistic Cost ModelsEg. Laser Process Model

  9. Laser Cycle/Labor Time LaserCycleTime = Cutting Time + Piercing Time + Rapid Traverse Time + Scrap Cut Time LaserLaborTime = LaserCycleTime * LaborStandard

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