Fibromyalgia Research

Topics: Downtime, Buffering agent, Machines Pages: 27 (9397 words) Published: March 18, 2011
An Evaluative Study of Operation Grouping
Policies in FMS


The increased use of flexible manufacturing systems to provide customers with diversified products efficiently has created a significant set of operational challenges for managers. This technology poses a number of decision problems that need to be solved by researchers and practitioners. In the literature, there have been a number of attempts to solve design and operational problems. Special attention has been given to machine loading problems, which involve the assignment of job operations and allocation of tools and resources to optimize specific measures of productivity. Most existing studies focus on modeling the problem and developing heuristics in order to optimize certain performance metrics rather than on understanding the problem and the interaction between the different factors in the system. The objective of this paper is to study the machine loading problem. More specifically, we compare operation aggregation and disaggregation policies in a random flexible manufacturing system (FMS) and analyze its interaction with other factors such as routing flexibility, sequencing flexibility, machine load, buffer capacity, and alternative processing-time ratio. For this purpose, a simulation study is conducted and the results are analyzed by statistical methods. The analysis of results highlights the important factors and their levels that could yield near-optimal system performance. Keywords: flexible manufacturing systems, operation grouping, aggregation and disaggregation policies, flexibility.

1 Introduction
A flexible manufacturing system (FMS) can be defined as a system composed of CNC machines, an automated material handling system, and a computer-controlled network that coordinates the activities of processing stations and the material-handling system. These systems are designed to process a variety of part types simultaneously. The flexibility of an FMS is primarily because of its capability of performing different operations at the same processing station combined with a material handling system, that is able to provide fast and flexible transfer of parts within the system. Since this technology entails high capital investment, an effective management-and-control system is necessary for a successful implementation.

FMS management requires the optimization of several components that can be classified into design and operational problems. Design problems deal with strategic decisions concerning the FMS hardware itself to meet the user goals and requirements. Operational problems deal with tactical and control decision problems such as process planning, machine grouping, part type selection, resource allocation, and loading [35]. The loading problem, which is of particular interest to our study, deals with the assignment of various resources (machines, tools, fixtures, and pallets) to the operations of different part types that are already planned for production in a given planning horizon. Obviously the machine loading related problems form an important link between both strategic and operational decisions.

A vast body of literature has been dedicated to modeling and solving loading problems, more specifically to the integration of process planning and scheduling sub-problems. In process planning, design specifications are transformed into manufacturing instructions by selecting the operation sequences and assigning the processes to the appropriate machine tool, etc., whereas in scheduling, the assignment of operations to machine tools over the planning horizon is done. For instance, some researchers develop integrated models to handle the feedback information efficiently between these two functions ([40],[30]).

Several studies consider a wide spectrum of single and multi-objective loading problems and formulate them as mathematical programs. For instance, in a seminal paper [35], Stecke describes six objectives of loading problems and...

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