بهینه سازی تعمیر و نگهداری ابزار برای سیستم های ماشینکاری چند ایستگاهی با توجه به اقتصادی منسوخ شده و از دست دادن کیفیت

Tools used in a machining process are vulnerable to frequent wear-outs and failures during their useful life. Maintenance is thus considered essential under such conditions. Additionally, it is widely recognized that the maintenance of manufacturing equipments and the quality of manufactured product are highly interrelated. However, few detailed study has been found in the literature dealing with the effects of maintenance policies on the operational performance of such a system, especially the long-term average cost. The need for a method to determine the optimal tool maintenance policy has become increasingly important. Since the multiple tools in a multi-station machining system generally have significant interactive impacts on the product quality loss, the optimal multi-component maintenance models for several policies are investigated to address the interdependence among these tools. Three distinctive multi-component maintenance policies, i.e., age replacement, block replacement, and block replacement with minimal repair, are identified and analyzed. The proposed approach focuses on these maintenance policies with consideration of both component catastrophic failures, and the interdependence of component degradations on the product quality loss as well as the obsolescence cost. The effects of various maintenance policies on the system performance are simulated, and they are used to determine the best policy for a given system. An illustrative example is used to demonstrate effectiveness and applicability of the proposed approach. The results presented a comparative analysis of specified maintenance policies with respect to the total maintenance cost with consideration of the product quality loss and the obsolescence cost.

In most industrial processes, the machine tool reliability plays a major role in manufacturing product with a high quality. Tool related costs contribute to a significant portion of the expense of producing parts. Furthermore, increased worldwide competitions, continuous advancement in the manufacturing technologies have all amplified the importance of tool management. Typically, a plenty of tool components are involved in the manufacturing process. Therefore, a proper tool management policy is highly demanded to improve the product quality and reduce overall production costs. One imperative aspect of the tool management is the tool maintenance or tool replacement policy. Multi-component maintenance is intensively studied in recent literature, various maintenance policies and related models have been investigated [1], [2], [3] and [4]. The use of mathematical modeling for the purpose of maintenance planning and optimization has also received growing attention. Many of these models have considered the economic dependency among the components, and have further pointed out that an opportunity existed for group replacement on several components, provided that a joint replacement cost of several components is less than that of the separate replacements of individual ones. Group maintenance policies based on the number of failed components were rigorously studied [5], [6] and [7]. Lam and Yeh [8] investigated the optimal maintenance policies for a deteriorating system. However, few of these models have captured cost related to the joint tool degradation and the quality loss. The degradation costs of the tools are either ignored, or separately assigned to each component. This makes the tool maintenance policy intricate and hard to be implemented in industry. The research on preventive maintenance (PM) and minimal repair for machines or tools to maintain system reliability has also been prevalent [9] and [10]. Often used to improve the system condition before it fails, conventional PM policy assumes that the system after each intervention is restored to be ‘as-good-as-new’. The best policy has to be selected for a given system with respect to its failure, repair, and maintenance characteristics. Mathematical sophistication of maintenance models has increased with the growth in the system complexity. Extensive research has been published in the areas of maintenance modeling, optimization, and management, while less can be found on maintenance related issues of multi-station machining systems. Alternatively, a minimal repair restores the function of the system in such a way that its failure rate remains as it was just before the failure occurrence, as is often called ‘as-bad-as-old’. This seems plausible for the failure behavior of the system when one of its many non-dominating tools is replaced by a new one. The tool maintenance studies should be coupled with economic analysis aiming at reducing the associated costs of downtime, replacement and repair. This entails evaluating and trading off conflicting objectives of operational performance and cost. In this way, a new methodology is developed with consideration of the following characteristics: (1) two different types of failures, namely the degradation due to drifts, and the catastrophic failures due to random shocks; (2) joint and interactive effects of multiple tools on the product quality loss; (3) easy-to-implement maintenance/replacement polices; and (4) obsolescence cost due to technologic innovation. To the best of the authors’ knowledge, no existing maintenance model concurrently captures these characteristics, which has not yet been sufficiently explored and exploited. In this research, a systematical methodology is proposed for the multi-station discrete manufacturing process to minimize the overall production costs, including the maintenance costs, the product quality loss, and the obsolescence cost. The remainder of the paper is organized as follows: the related cost due to the product quality loss and the obsolescence are presented in Section 2. Various multi-component maintenance policies incorporating the relevant cost issues are investigated in Section 3. An example is provided in Section 4 and is used to demonstrate the developed methodology. Finally in Section 5, some concluding remarks and future directions are offered.

Different maintenance policies have been modeled and analyzed by incorporating the economical effects of maintenance activities, product deviation related quality loss, and obsolescence at the time of disposal. A quadratic loss function is employed to characterize the costs resulting from the deviation of part dimension from its target value. The models also make contribution towards effective economic evaluation of maintenance policy decision when the system follows a given obsolescence function. A case study for a box-type workpiece manufacturing in the four-station machining process is used to demonstrate the optimal tool replacement policies determination process. A comparative analysis of some specified maintenance policies with respect to the long-term expected cost with consideration of the product quality loss and the obsolescence cost are provided. Future studies can be carried out on the cost aspects of various policies. Some other possible maintenance policies should be studied and compared to those presented in this study. Combinations of several policies are also possible within the same manufacturing system. For example, while a set of tools is maintained by one policy, another set can be maintained by a different policy. While maintenance actions can reduce the effects of breakdowns due to wear-outs, random failures are still unavoidable. Another very important area of future investigation is to understand the implication of a given maintenance policy on a multi-station manufacturing system before its implementation.