Facility layout design in a changing environment

Abstract

Increasing global competition, rapid changes in technology and the necessity to respond quickly to a cost and quality conscious customer have changed the dynamics of facilities planning. Today's manufacturing facility needs to be responsive to the frequent changes in product mix and demand while minimizing material handling and machine relocation costs. In this paper, we present a framework for the design of a dynamic facility which can respond e ectively to the changes in product design, mix and volume in a continuously evolving work environment. A genetic algorithm-based heuristic is used for solving the design problem and two test cases are presented to illustrate the use of the methodology. IntroductionIn a typical manufacturing plant, a manufacturing engineer decides on the sequence of operations that are necessary to transform the raw materials into ® nished products. This set of operations, along with previously established cost and quality criteria help determine suitable manufacturing equipment. Based on this selection and knowledge of the interaction between various machining centres or departments, the facility designer attempts either to maximize an adjacency measure, minimize the total cost of material handling or optimize some combination of the two. A heuristic or an optimal algorithm (depending on the formulation and size of the problem) is used to obtain a block layout. The solution is then modi® ed to include qualitative or non-quanti® able criteria. Such models often assume that:

Next Generation Factory Layouts: Research Challenges and Recent Progress

“…Improvements to the branch and bound procedure in [63] are provided in a number of other papers including [5], [8] and [76]. Heuristic procedure for the dynamic layout problem can be found in a number of papers including [15], [42], [50] and [75], among others. Variations of the basic dynamic layout problem are studied in [7], [57] and [75].…”

“…While grouping resources based on their functionality allows for some economies of scale and simplicity in workload allocation, it makes the layout vulnerable to changes in the product mix and/or routings. When they occur, these changes often result in a costly relayout of the plant and/or an expensive redesign of the material handling system [42,49,74,82].…”

“…Heragu and Kochhar [31] discuss this idea and argue that advances taking place in materials and mechanical process engineering, for example, lighter composite materials, nano-technology and laser cutting, will allow companies to reconfigure machines rather easily on a frequent basis. Kochhar and Heragu [42] present a genetic algorithm to solve the associated dynamic layout problem.…”

“…There is an emerging consensus that existing layout configurations do not meet the needs of the multi-product enterprise [4,13,37,42,58,59,61,79,82] and that there is a need for a new generation of factory layouts that are more flexible, modular, and more easily reconfigurable. Flexibility, modularity, and reconfigurability could save factories the need to redesign their layouts each time their production requirements change.…”

Agent-based hierarchical production planning and scheduling in make-to-order manufacturing system

“…Moreover, other changes in the business environment like change in demand pattern cannot be handled simultaneously by the use of these two concepts. In terms of changes in demand pattern, two approaches related to layout design have been developed, including the dynamic layout (Rosenblatt and HAU, 1987;Balakrishnan et al, 1992;Balakrishnan and Cheng, 1998;Kochhar and Heragu, 1999) and robust layout (Rosenblatt and Kropp, 1992;Benjaafar et al, 2002). These approaches aim to add built-in flexibility or robustness to system layout in response to forecasted changes in demand pattern.…”