| Research Abstract |
The aim of this research is to realize an advising system for product design enhancement by use of producibility evaluation based on product and manufacturing resource models. By using this system, product designers are able to predict the possible difficulty of production about his products, and ask for advises how to improve the manufacturability while keeping the functionality of products. It is fairly difficult to achieve the above-stated target, and here we restrict our research on machinability evaluation only, and do not consider the other manufacturing methods or processes. However, the underlying approach and methods would be equally effective for other types of production.
We first extend our previous work on product modelling in order to be able to present, in addition to product shape, tolerances, materials, surface roughness and property, machining form features, etc., and utilize those model attributes for dealing with products, their blank materials, and manufacturing res
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ources, such as machine tools. We combine these models with cutting process models to be able to predict cutting forces and torques very precisely. By this cutting process simulation, we can predict the stability boundary of chatter vibration correctly, and set up the appropriate cutting conditions automatically. We apply these results to the generation of numerically controlled cutter paths for complicated pocket mining. By this approach, the efficiency of NC pocket milling could be substantially enhanced.
We combine the above-stated results with our own process planning system to automatically generate pertinent process plans for products being designed. The generated process plans are evaluated by various rules extracted from past machining experiences and product property requirements. The result of the evaluation is a very useful advice for product designers to improve their design according to the manufacturability. The result of the research is summarized in a form of software tools which are useful for constructing advising systems for specific machining operations. Less
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