Computer-aided fixture design an update


















A new design system is developed in the article for the special purpose jig and fixture by applying artificial intelligence AI technology into the CAFD system, using the theory of the expert system and technology of the 3D modelling.

It discusses the configuration, the general function modules, the knowledge representation, the reasoning mechanism and the standard component base of the jig and fixture. This paper explored the technology of intelligence and optimization in the process of the jig and fixture design. Finally, an example of virtual assembly is given designed by the CAFD system. Shin, H. Rule-based systems approach to fixture design.

PhD Dissertation, Dept. Chou, CY. Computerized fixture design from solid models of workpieces. Automated design of modular fixtures for flexible manufacturing systems. Journal of Manuf. Prombanpong, S. A computer aided fixture design system for two dimensional prismatic parts produced on machining centres. Masters Thesis, Dept. Holdex - Holding device expert system. Applications of artificial intelligence and the design of fixtures for automated manufacturing.

IEEE Int. An optimization approach to the integration of computer aided fixture design with macro process planning for three dimensional prismatic workpiece manufactured on CNC machining centres. FIXES, a system for automatic selection of set-ups and design of fixtures. Annals of the CIRP. Automated set-up and reconfiguration for modular fixturing. Proceedings of Manufacturing Int. Fixture design with FIXES: The automatic selection of positioning, clamping and supporting features for prismatic parts.

Computer aided assembly of modular fixturing systems. Autofix - An expert CAD system for jigs and fixtures. Tools Manufact. Knowledge representation database for the development of a fixture design expert system. Expert system for fixture design. A reconfigurable fixturing system for robotic assembly.

Robotised assembly of modular fixtures. Learning from observation: Conceptual clustering. Conceptual clustering: Inventing goal-oriented classification of structured objects. By utilizing a set of processes at each stage, an effective, efficient fixturing solution can be developed. Problem definition can be described as understanding the fixturing problem and enumerating the design variables, system constraints, and solution criteria.

Design variables typically include fixturing elements, fixture assembly options, equipment sizes, and the amount of force required to be applied to the product in order to achieve the desired result. Design constraints include the method of attaching the fixture to the product, accessibility of the fixture for the assembly worker, and the stress required to be supported by the fixture. Design criteria can be summarized as the total budget to the applied to the fixture, the skill required of the assembly worker to use the fixture, the production rate to be required on a per-fixture basis, and the overall quality required of the fixture.

As this step drives the remaining two steps, it can be the most important step. Fixture synthesis concerns itself with the design variables of a given fixture as required to meet design constraints. This requires selecting the subassemblies and parts that will make up the fixture. In addition, clamping positions and methods must be determined.



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