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Engineering Quality Into Designs Using Behavioral Modeling

Total Length: 2 Days

This two day course is targeted at intermediate and advanced Pro/Engineer users.  Discussion topics will focus on engineering quality into designs using Behavioral Modeling.   The course will include both lecture and laboratory exercises.  Strategies for working with analysis features, sensitivity, feasibility & optimization studies will be demonstrated with real world examples.

Module 1: Introduction to Robust Design

  • The status of the current design and simulation process
  • Overview of the tools and techniques for traditional and robust design
  • Introduction to Design of Experiments and Behavioral Modeling (BMX)

    Application activity:
    Identification of the most influential Pro/E parameters on response attributes

Module 2: Analysis Features & BMX Sensitivity Analysis

  • Overview of analysis features based on measurements
  • Creating parameters based on analyses of the model
  • Using BMX field points and persistent display
  • Performing sensitivity studies to find the effect of design variables on response attributes

    Application activities:
  • Cable length optimization
  • Identification of structural discontinuities
  • Inspection of thickness requirements in castings

Module 3: Design Synthesis & BMX Optimization Analysis

  • Automatically determining the design variable values that achieve a desired model behavior
  • Performing optimization studies to find the optimum set of design variables that maximize the response attributes
  • Creating optimization study feature parameters based on analyses of the model
  • Linking BMX and Excel for graphing and associative data exchange

    Application activities:
  • Minimum weight section that meets strength, stability and manufacturing requirements
  • Automatic design of minimum cost container of a given volume
  • Optimum location of steering column's universal joint

Module 4: Multi-objective Design Studies

  • Use simple graphical techniques to analyze multi-objective study data
  • Identifying optimum experiments using Constraints and Pareto methods
  • Using response surface techniques in multi-objective design studies

    Application activities:
  • Stress distribution with field points and deformed shapes with spinal bends
  • Packaging optimization of metal stamped parts to minimize scrap

Module 5: Engineering Quality into the Design and Knowledge Capture

  • Review of the cost of poor quality and how improved quality reduces total cost
  • Identifying noise and control parameters
  • Statistical performance - shift (mean) and squeeze (variability)
  • Reliability based design with BMX external analysis
  • Designing for Six-sigma quality levels with BMX

    Application activities:
  • Design criteria driven column design (a smart self designed part)
  • Reliability based design within Pro/Engineer

Module 6: Strategies for Best Practice BMX Implementation

  • Overview of BMX implementation challenges
  • Organizational and technical inhibitors to achieve best practice BMX implementation
  • Solution strategies to overcome organizational and technical inhibitors
  • Baldrige National Quality Program as a framework for organizational improvement

    Demonstration activities:
  • Optimum spaceship sizing to minimize frontal and surface area
  • Location of the metacenter of a ship's section
  • Computation of hydrostatic forces on submerged gates
  • Radiation vulnerability analysis of satellites
  • Equilibrium positions during submarine deployment 

Who Should Attend

Pro/Engineer users, design engineers, CAE analysts, consultants, R&D personnel, quality engineers, and process engineers.  Working knowledge with Pro/Engineer 2001 is required.  NO prior knowledge of DOE or statistical techniques is required.

Learning Outcomes

  • Understand the basics of designed experiments and robust design
  • Enable designs to be driven by their product specifications
  • Know how to use simple graphical techniques to analyze multi-objective study data
  • Perform automated design space exploration
  • Optimize automatically the design for a set of performance attributes
  • Deign for Six-sigma quality levels

The Instructor

Dr. Andreas Vlahinos is a principal of Advanced Engineering Solutions.  He has helped thousands of university students and engineers to become experienced, skilled practitioners in the areas of CAD, CAE and design optimization.

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