A process-planning model (PP model) is proposed to convert the geometric features into manufacture machining operations and sequence the machining operations of the part in a feasible and effective order. The process-planning model (PP model) construct a feature framework that makes a mapping from geometric features into machining operations. A semantic net named the Precedence-Relations-Net is established to reflect the precedence relationships among the machining operations. The vectors and the matrixes are employed to construct a mathematical sequencing model. A part is decomposed into several basic geometrical units, namely, U1, U2, … , UN. For each unit Ui, two vectors, named Fi and Pi, represent the features and machining operations of Ui. Finally, a matrix named PP is used to memorize the process plan, and a matrix – PO (performing objects) – represents the object of machining operations.
Manufacturing process planning is the method to get the necessary manufacturing process and their acceptable sequence in order to produce a given part in an economical and competitive way (a good way by some standards) [3], [4], [5], [6] and [7]. In order to obtain the process planning, the process planner derives some appropriate information from a design model such as the design profile, accuracy, surface roughness, material and so on. All of those information are defined as manufacturing features. Therefore, most of computer-aided process planning (CAPP) systems uses the concept of manufacturing features to describe a part [6], [8], [9] and [10]. In this regard, manufacturing features link the computer-aided design (CAD) and computer-aided manufacturing (CAM). But the problem is how to build the bridge that can translate the manufacturing features into the machining operations sequence.
For several years, this problem has received more and more attention from researchers because it is the essential for generating an optimal process planning. Many researchers construct a knowledge base [1], [2], [11] and [13]. Sang C. Park [1] constructs a knowledge base that consists of three sub-models: the object model, the function model, and the dynamic model. Although he gives us a methodology on process planning, it is not a systematic model of process planning. In this paper, we will construct a process-planning model (PP model) that has three parts: the Features Framework, the Precedence-Relations-Net and the Sequencing Mathematical Model and can be illustrated by Fig. 1. First, a design model should be decomposed into several units in according with its geometrical profile. Each unit has its features. Then features of each unit were input a knowledge base, which was expressed by framework, and the output is the final operation of each unit. Second, a semantic net, namely PR-net, will be build to reflect the precedence relations among machining operations. The final operation of each unit is input PR-net, and then a vector, which consists of operations, is output. The counter-order of this vector is an acceptable sequence for each unit. All of those vectors are input a sequencing mathematical model to obtain an acceptable and competitive process plan.
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Fig. 1.
Expert system.
It is an important issue on feature-based process planning for the computer-aided process planning [1]. Although there have been many studies on feature-based process planning, researches that use framework, semantic net and mathematical model is rare.
To construct the process-planning model, firstly, we use framework to do a mapping from features into operations. Using this framework, we can obtain the final operation of a unit of a part. Then, we employ a semantic net to reflect the precedence relations among operations, namely, the Precedence-Relations-Net. If a single operation is input, it can generate a sequence of operations in a feasible order on technological constraints. Finally, and most importantly, we built a sequencing mathematical model to obtain the process plan. In a part, if some unit volumes share the same machining operation and the same cutting tool, they can be aggregated into one machining operation [1]. But aggregating must be limited by some rules, say, the feasibility of the cutting operation and cutting accessibility. It is obviously that if all of machining operations satisfying the relation and those rules can be aggregated, an efficient and competitive process plan will be obtained. The sequencing mathematical model can aggregated all of those machining operations and obtain an acceptable one.
