برنامه ریزی دوره ای جرثقیل واحد با مخازن متعدد: راه حل جابجایی مواد

A hoist controlled by a computer is widely used for moving electroplates which is chemically treated in a sequence of tanks. The hoist scheduling directly affects the throughput of a production system. The objective of the hoist scheduling problem is to schedule the moves to maximize the throughput. This paper investigates the hoist scheduling problem, a specific material handling issue, in a manufacturing environment. The scope of the study is in the area of single hoist cyclic scheduling with multiple tanks. The purpose of the study is to develop a mixed integer linear programming model that can be used to schedule multiple tanks and improve throughput in a process industry. Specifically, a method has been proposed to estimate the processing time in a bottleneck stage with multiple tanks.

This paper investigates the hoist scheduling problem, a specific material handling issue, in a manufacturing environment. The scope of the study is in the area of single hoist cyclic scheduling with multiple tanks. The purpose of the study is to develop a mixed integer linear programming model that can be used to schedule hoist moves and multiple tanks and improve throughput in a production system. In this research, a multi-tank sequencing procedure is proposed for the single hoist scheduling problem (HSP). Specifically, a solution procedure has been suggested to estimate the processing time in a bottleneck stage with multiple tanks. Material handling includes packaging, moving, and storing materials and it consumes labor, space, and facilities. Material handling during a production process adds very little value to the product. Although, the choice of how the material is moved and when the material is moved is an important technological decision, this decision can affect a manufacturing company's overall performance such as profitability and customer service level. Therefore, both researchers and practitioners have been searching for solutions and new ways to reduce material handling costs. The scheduling of material handling devices such as hoist directly affects the throughput of a production system. In the printed circuit boards industry, electroplating is an important material handling process. Scheduling the movement of material handling hoist for electroplating processes is generally known as the HSP problem and has been proven to be an NP-complete problem [1]. The objective of hoist scheduling problem is to find a cyclic sequence of hoist moves that minimizes the cycle time or maximize the throughput of a production system. In this study, a mixed integer model is proposed to solve single hoist scheduling problem with multiple tanks at a bottleneck stage. The paper is organized as follows. Section 2 provides the background information for the single hoist scheduling problem. Section 3 models the single hoist cyclic scheduling problem with multiple tanks. An illustrative example is presented in Section 4. Conclusions are given in Section 5.

In this paper, the single hoist cyclic scheduling with multi-tank problem has been studied and a mixed integer linear programming model based on Phillip's model of the single hoist scheduling with single tank problem has been proposed and tested. Specifically, a solution procedure is proposed to estimate the processing time in a bottleneck stage with multiple tanks. The example case gives the shortest cycle time of the production system using the mixed integer model suggested in this research. This model provides some valuable insights for tackling the bottleneck problem in the manufacturing industry and shows how to use material handling technique to improve production performance. Future research may consider the multi-hoist and multi-tank material handling problem. As manufacturing process technology evolves, the processing time is significantly reduced. This puts the pressure on reducing material handling time. Without adequate material handling control, machines will be idle and jobs will be waiting. This will waste a lot of resources. Future research may consider set up time, processing time, and material handling together to provide a holistic model for manufacturing firms [11], [12], [13], [14], [15] and [16].