مدل برنامه ریزی خطی مخلوط عدد صحیح برای مخلوط بخشی، تخصیص ابزار و فرآیند انتخاب طرح در مراکز پردازش CNC

A mixed-integer linear programming model is developed for the simultaneous determination of part mix, tool allocation and process plan selection in CNC machining centres. Illustration of the use of the model in a hypothetical example and its application to a real problem arising in deep seabed operations demonstrate the utility of the model as one more step towards the integration of computer-aided process planning (CAPP) tasks in CNC machining enviroments.

In automated manufacturing systems, such as CNC machining centres, a number of process plans are generated for each part type. In each process plan, requirements are specified for operations, tools, fixtures, etc. The selection of the best process plan depends on cost factors as well as characteristics of the manufacturing environment under consideration. Kusiak and Finke [1] developed a mixed-integer linear programming (MILP) model in which the sum of process plan dissimilarity and cost functions is minimised. Bhaskaran [2] proposed a multi-stage procedure in which initial process plans are gradually consolidated with a view to cost minimisation. Chang [3] included sequencing of part type machining in the process plan selection problem, employing the same objective function as Kusiak and Finke [1]. None of the aforementioned works take into account operational aspects such as part selection and tool allocation when selecting process plans. On the other hand, Iakocou et al. [4] developed an MILP model for determining the optimal part–tool combination with a view to maximizing total revenue; however, it was assumed that each part can be machined by one and only one out of several tools. This is a severe restricting assumption in practice, as a part is machined by one out of several process plans, each of which requires one or more tools. It is the objective of this paper to address this gap in developing an MILP model for the integration of determining optimal part mix, tool allocation, and process plan selection. The structure of the rest of the paper is as follows. A concise problem statement is first presented. This is followed by the development of the MILP model. Next, the procedure employed in generating machining process plans is presented. The use of the model is then illustrated via the machining of three hypothetical parts. The model is then applied to a real case involving the machining of a 3-part assembly employed in deep seabed oil drilling operations.

The MILP model developed in this paper for simultaneous part mix, tool allocation, and process plan selection problem in CNC machining centres has been ilustrated by application to a hypothetical example and to the fabrication of a deep seabed operations assembly. In this way, one more step is taken towards the integration of tasks in computer-aided process planning (CAPP) in CNC machining enviroments.