Fixturing analysis and re-design in a co-operative fixture design system

Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Mechanical and Aerospace Engineering


Utpal Roy


Fixture design, Artificial intelligence, Stability analysis, Cooperative fixture design

Subject Categories

Computer-Aided Engineering and Design | Industrial Engineering | Mechanical Engineering


Fixture design is a complicated, experience based process which needs a comprehensive qualitative knowledge about a number of design issues including workpiece configuration, manufacturing processes involved, machining environment etc. Due to the complexity of fixture design problems, a general and comprehensive automated fixture design (AFD) system has not been completely developed. This dissertation presents the development of a simultaneous engineering based methodology for integration and collaboration of diverse expertise in fixture design and analysis to build a co-operative fixture design system. The system's blackboard based architecture provides a co-operative environment in which simple and problem-oriented knowledge sources can be easily integrated in the system to solve complicated or generic fixture design problem.

A computational methodology has been developed for quantitatively analyzing fixturing stability in the AFD environment. In stability analysis, the virtual disturbance which is expressed as a wrench in the screw coordinates and has the same tendency as those fixturing and machining forces to destabilize the workpiece is adopted in the study, and the stability of the workpiece is characterized based on its capability to overcome the virtual disturbance. The stability characteristics for each fixturing configuration (i.e. positions for fixturing components of supporters, locators and clamps) are obtained from the stability analysis and used in re-design process to determine the "best" design of fixturing configuration.

An automated process to carry out the analysis of workpiece's deflection has been developed in order to achieve a complete automation of the AFD system. A neural network based selector is created and integrated in the automated process for predicting the machining parameters which are then used for determining the machining forces. The FEA tool as well as a commercial CAD package have also been integrated in the AFD system to automate the deflection analysis. A rule based reasoning process has then been created to help guide the re-design of fixturing configurations in order to decrease the workpiece's deflection, if it is necessary.


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