طرح تسهیلات با استفاده از ارتباط الگوریتم های داده کاوی مبتنی بر قواعد وزن دار: ارزیابی با شبیه سازی

Facility layout has considerable effects on the operational productivity and efficiency of a facility because of its direct effect on material handling costs. The objective of this study is to propose new weighted association rule-based data mining approaches for facility layout problem. Classic association rule-based approaches assume that each item has the same level of significance. On the other hand, in weighted association rule-based approaches, each item is assigned a weight according to its significance with respect to some user defined criteria. In this study, different weighted association rule-based data mining approaches, namely MINWAL(O), MINWAL(W), WARM and BWARM, are applied to facility layout problem. To confirm the viability of the proposed approaches, two case studies are presented. The approaches are compared in terms of general performance criteria for the facility layout problems using simulation. This is the first study that applies weighted association rule-based data mining approaches to facility layout problem. To address the needs in practice, “demand”, “part handling factor” and “efficiency of material handling equipment” are used as the weighting criteria. Then, this study differs from the previous works in that it considers the three key location factors together.

Machines are important resources for manufacturing systems, and their locations have direct effects on efficiency, productivity and ergonomic conditions of these systems. The location and arrangement of machines can be considered as a typical facility layout problem. From this perspective, facility layout problem deals with the question of where m numbers of machines (each with area ai) are arranged within a given location. The significant problem of facility layout is about the decision on which pairs of facilities should be located next to each other ( Wäscher & Merker, 1997). The most related machines are located adjacent to each other as possible to minimize transfer time, waiting time in queue, product cycle time, and maximize total production and machine utilization. Hassan (1994) indicates that machine layout affects the material handling cost and time, throughput and productivity of the facility and some factors, namely material handling system used, available space, the similarity of the sequences of operations of the parts, the capability of meeting system’s requirements. Minimization of the total material handling costs is the most frequently considered objective in facility layout problems. Tompkins et al. (1996) indicate that 20–50% of the total operating expenses are composed of material handling cost, and an effective facility layout can reduce these costs by 10–30%. To date, many numbers of efforts have been done to address facility layout problem. Data mining based algorithms have often been applied to manufacturing systems in the last decade. One of the main data mining methods is association rule, the aim of which is to find the correlation between items. Hipp et al., 2000, Zhao and Bhowmick, 2003, Kotsiantis and Kanellopoulos, 2006 and Forsati and Meybodi, 2010 can be referred for more details on association rules. Association rule-based algorithms assume that each item has the same level of significance. But in practice, some items may be more important than others. Therefore, decision makers have to reflect this importance level to the items. That is, each item in weighted association rule is assigned a weight by considering the significance of the criteria defined by the decision makers. Factors that affect real-life problems can easily be considered in the model by finding the association between items by using weighted association rules. No previous work applies weighted association rules to manufacturing systems although there are several studies that apply classic association rules. To fill this gap, we propose five weighted association rule-based data mining algorithms for facility layout problem. This is the first study that applies weighted association rule-based data mining approaches to facility layout problem. The remainder of this study is organized as follows. Section 2 gives a general overview of the related literature. In Section 3, the proposed weighted association rule-based approaches are introduced. Section 4 is devoted to the presentation of the computational experiments aiming the illustration of the viability of the proposed approaches. To this aim, two case studies with different size are handled. Finally, Section 5 presents the conclusions and future research directions.

This study proposes five different weighted association rule-based data mining approaches for facility layout problem. To our knowledge, this is the first study that applies weighted association rule-based data mining approaches to facility layout problem. Three location factors, namely demand, part handling factor and efficiency of material handling equipment that are most pertinent to facility layout problems are selected as the weighting criteria. This study differs from the previous works in two ways. First, it considers these three key location factors together. Therefore, there are no other study results to compare against. Second, in addition to the quantitative factor, qualitative factors, part-handling factor and efficiency of material handling equipment, are considered in algorithmic approaches. The proposed approaches are based on MINWAL(O), MINWAL(W), WARM and BWARM approaches. Facility layouts obtained by the proposed approaches are compared in terms of five performance measures, namely machine utilization, total amount of products produced, cycle time, transfer time and waiting time in queue, using simulation. The results indicate that the proposed WARM-based approach provides better results in terms of total amount of products produced, cycle time, waiting time in queue and transfer time for case study-I. However, the proposed approaches provide similar results for case study-II. The proposed MINWAL(O)-based and MINWAL(W)-based approaches can give same or different layout configuration according to the weighted minimum support value (wminsup) used. The proposed two MINWAL(W)-based approaches can also give different layout configurations even using the same wminsup value. By means of the approaches proposed in this study, quantitative and qualitative factors that affect facility layout can be taken into account. In this concern, the following works can be regarded as future research directions. – The proposed approaches can be applied to multi objective facility layout problems. – Other weighting methods such as SAW and ANP can be used for weighting the facilities, and the results can be compared. – Other production factors such as batch sizes, processing time learning rate, operation costs, inventory costs and machine breakdowns can be considered. – Facility layout problem can be treated by considering the ergonomic factors.