Various problems occurred in encapsulation of plastic IC packages are the results of improperly handling of the many process parameters, lack of understanding of material properties, and immature mold design. The traditional way to get rid of these problems is to adjust the process parameters of the transfer molding machine. However, the optimization of these parameters is usually based on past experiences or obtained by trial and error. This approach is time consuming and less accurate. A program is developed to help users to choose an appropriate initial machine setting based on the machine, material and mold design information. The detail of its application to IC encapsulation process is described in the paper.
Determination of injection molding machine setting is usually carried out by an experienced machine operator. By considering the mold geometry, polymer type and machine model, the operator decides an initial setting based on his own knowledge. This knowledge could include material and machine data, empirical rules and simple formulae. A computer system based on this knowledge is developed for computing an initial setting for an injection molding machine. The system first determines the possible processing conditions by considering only the material type and machine model. Then an initial processing condition is determined from these possible conditions by reasoning using the empirical rules. This reasoning is formalized by fuzzy logic. Finally, the machine setting corresponds to the determined initial processing condition is calculated by simple formulae. The performance of the system has been verified by experiments. Results show that the computed setting is acceptable for simple geometry.
This paper reports on the development of a concurrent engineering system which covers four application domains in production of mechanical parts, namely design, manufacturing, assembly and inspection. Two approaches are introduced: (1) semantic feature which describes information within each domain separately, and (2) feature transformation which manipulates and derives information across different application domains. Their applications in generative process planning are illustrated in a case study.
The shape of non-uniform rational B-spline (NURBS) based free-form surface is determined by its control polygon. Shape modification is usually achieved by either individually changing the position or adjusting the weights at each of the control points. This paper proposed a unified method for shape modification of NURBS surface. The method provides a mathematical relationship between changes in the weight and location of control points to positional adjustment of surface points.
A feature-based concurrent engineering system covering most application domains in production, i.e., design domain, manufacturing domain, assembly domain, and inspection domain, is to be developed. Efficient information representation and manipulation are the basic criteria. In this paper, a hierarchical structure with generalized feature definition is proposed as the solution. It contains the vocabulary of the semantic feature-based language for information description and introduces the concept of feature transformation which forms the grammar of the language for information deriving and exchange. Its applications in generative process planning are demonstrated.
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