رویکرد بهینه سازی کلونی مورچه ها به یک مدل برنامه ریزی آرمانی فازی برای انتخاب ماشین ابزار و تخصیص عملیات مشکل یابی در FMS
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|16045||2006||10 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Robotics and Computer-Integrated Manufacturing, Volume 22, Issue 4, August 2006, Pages 353–362
Due to the global competition in manufacturing environment, firms are forced to consider increasing the quality and responsiveness to customization, while decreasing costs. The evolution of flexible manufacturing systems (FMSs) offers great potential for increasing flexibility and changing the basis of competition by ensuring both cost effective and customized manufacturing at the same time. Some of the important planning problems that need realistic modelling and quicker solution especially in automated manufacturing systems have assumed greater significance in the recent past. The language used by the industrial workers is fuzzy in nature, which results in failure of the models considering deterministic situations. The situation in the real life shop floor demands to adopt fuzzy-based multi-objective goals to express the target set by the management. This paper presents a fuzzy goal programming approach to model the machine tool selection and operation allocation problem of FMS. An ant colony optimization (ACO)-based approach is applied to optimize the model and the results of the computational experiments are reported.
The manufacturing industry is presently being affected by the structural changes caused the internal and external factors for an enterprise. The market conditions are becoming more dynamic, more global, and more customer driven. The manufacturing performance is no longer driven by the product price; instead other competitive factors such as flexibility, quality, delivery, and customer service have become equally important. The demand of the customer for tailored product has resulted in a shorter product life, reduced batch quantities and increased product varieties. Manufacturing firms need to give prominence to issues such as reduction of manufacturing lead time and flexibility to adapt to changes in the market. The improvement in productivity and reduction of costs of goods and services has become the key for maintaining the market share. Over the past few years, the concept of flexible manufacturing system (FMS) has emerged as a viable answer to the problems of flexibility and efficiency. Operations management in a FMS is more complex than that of the conventional manufacturing systems. Managing an FMS demands for more decisions for its effective performance compared to a transfer line or job shop production system. The optimal selection of machines and tools and the assignment of part operations to the selected machines turn out to be difficult tasks for the production planner. This is due to the versatile machine tools capable of performing many different operations resulting in many alternative routes for a part type, and due to system capability for processing of the parts concurrently .
نتیجه گیری انگلیسی
This paper considers the machine–tool selection and operation allocation problem and exhibits the effectiveness of the fuzzy goal programming-based approach to address the same. The objective taken into account are to determine the optimal combinations for the machine and tool for operations keeping in mind the minimization of various costs; namely, machining cost, set-up cost and material handling cost. The constraint posed by the system are pertaining to tool life, tool magazine capacity and machining time. The proposed model is optimized by ant colony algorithm. Some of the salient features of this work can be enlisted as follows: