This 2-day course covers the dramatic developments in Knowledge-Based Engineering (KBE) that have recently become possible through a marriage of traditional CAD/CAM techniques and those from the fields of Artificial Intelligence and Expert Systems. This marriage is producing the next generation of truly intelligent, or Knowledge-Based, CAD/CAM systems. This course surveys examples of these developments, including consideration of the concepts underlying such systems. We include a look at the expert system for transmission design recently developed by the instructor for Ford Motor Co., that has automatically produced thousands of patentable new designs.

BENEFITS of ATTENDING

• Examine case studies of successful Knowledge-Based Engineering systems
• Learn the Artificial Intelligence/Expert System concepts behind KBE
• Become familiar with the Theory of Inventive Problem Solving (TRIZ)
• Learn about the tools available for applying KBE techniques

WHO SHOULD ATTEND

This course is for design engineers, manufacturing engineers and engineering managers interested in understanding the principles, tools and opportunities of knowledge-based engineering. This is an introductory-level course requiring no background in computer programming or artificial intelligence. A general engineering background is assumed.

COURSE HIGHLIGHTS

EXPERT SYSTEMS

• Background
• Architecture
• Video of Expert System Success Stories
• Expert System Shells
• Prolog as an Expert System Shell

KNOWLEDGE

• Knowledge Acquisition
• Video of CHARLEY, an Expert System for vibration analysis at GM
• Machine Learning and Neural Nets
• Robot Navigation using Neural Nets
• Problem Formulation
• Knowledge Representation
• Demo of Associational Thinking with IdeaFisher software

SEARCH

• Path-Finding (State Space Search) Problems
• Search ordering techniques
• Divide and Conquer Methods
• Assembly Planning using Divide and Conquer

CONSTRAINT-BASED REASONING

• The Constraint Satisfaction Problem
• Constraint-Based Reasoning Methods
• Applications in Machine Vision
• The instructor's constraint-based expert system for transmission design at Ford Motor Co.

THE THEORY OF INVENTIVE PROBLEM SOLVING (TRIZ)

• TRIZ Background
• Patterns of Technological Evolution and Directed Evolution
• Ideality and the Ideal System
• Improving systems by exploiting resources and effects
• Problems of Mutual-Contradiction
• Altshuller's 39 key engineering parameters and 40 inventive principles
• The TRIZ contradiction matrix for solving problems of mutual-contradiction
• Demo of TRIZ software

DESIGN OPTIMIZATION

• Efficiency versus Psychology
• Optimization methods: breadth-first search, depth-first search, branch & bound search, hill climbing, best-first search, A* search, Genetic Algorithms, Virtual Reality
• Applications in engineering: truss design, airplane wing design, assembly planning, flow shop scheduling

HANDLING UNCERTAINTY

• Representing Uncertainty
• Fuzzy Logic and an application to vehicle control

INSTRUCTOR

Dr. Bernard Nadel, President, IntelliGineering Corp.

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