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A design expert system for guidance and assessment of the design evolution of motion control systems

University of British Columbia

The automation of engineering design is of great significance in the development of machinery and products in competitive industries. Using an automated and “optimal” design process to redesign the faulty components and poorly performing regions of an existing engineering system will facilitate the realization of realistic design alternatives, with benefits such as improved quality, reliability, and cost effectiveness. Motivated by such needs, this thesis develops a Design Expert System (DES) for motion control (MC) applications. The developed DES is expected to be integrated into a multi-system Evolutionary Design Framework (EDF) which is being developed in our laboratory. The EDF integrates techniques of condition monitoring, modeling, and evolutionary optimization for autonomous identification, diagnosis, and redesign of poorly performing aspects of an existing machine. Through integration with optimization routines and the use of a comprehensive knowledge base (KB) in the MC domain, the DES developed in this work is able to guide the evolution of optimal design alternatives and assess their feasibility and effectiveness. Due to the prevalence of electric motors as actuators in many industrial applications, MC design and actuator (motor) selection represent the application domain of the DES developed in the present research. The KB of the DES includes knowledge of typical mechanical structures used in industrial MC systems, common profiles of load speed or position (duty cycles), and the effect of practical issues such as s-curve profiling, geometric trajectory blending, intermittent duty cycles, rms torque, and the thermal response of motors. A systematic methodology for detailed design analysis and subsequent selection of commercially available motors, their drive systems, and transmission devices (e.g., gears) from an external database is developed. Selections by the DES are compared to those by a human designer for both hypothetical and actual designs, thereby verifying the DES procedure. To facilitate the interaction between different systems in the EDF, a graphical user interface (GUI) is created for the DES in Excel®. The DES is synchronized with Matlab® to guide optimization routines based on its built-in human expertise and heuristic design knowledge. A guided optimization case study is presented and benefits of the guidance process are discussed.

Text

2012-03-30

Attribution 3.0 Unported

http://hdl.handle.net/2429/41894

Mechanical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by/3.0/