A knowledge-based auto-reasoning methodology in hole-machining process planning

In process planning, how to obtain an optimal process planning is the essential of computer-aided process planning (CAPP) system. The main goal of CAPP system is to derive manufacturing features and machining operations from a design model and sequence the machining operations of the part in a feasible (by some technological constraints) and effective (by some economical standards) order. In this paper, we construct a process planning model (PP model) for the hole's machining, which consists of three parts: the features framework, the precedent relation net and the sequencing mathematical model. The features framework makes a mapping from manufacturing features of hole into its machining operations. A semantic net named the precedence-relations-net reflects the precedence relationships among hole's machining-operations. Some vectors and matrixes are employed to construct a mathematical sequencing model. Usually, a hole should be machined in several operation directions, nu(1), nu(2),(...), nu(M). In each operation direction, nu(i), there are M basic geometrical units to be operated, namely, U-1(l), U-2(l),..., U-N(l). For each operation direction, nu(i), a vector and a matrix are defined to memory the process planning and its operation objects. The mathematical sequencing model will generate an optimal process planning in each operation direction by minimizing the number of tool-changes and decreasing the number of operation steps. Therefore, it can shorten processing times and consume less energy. Finally, two hole-machining examples are employed to illustrate our methodology. (c) 2005 Elsevier B.V. All rights reserved.