Design of robust layout for Dynamic Plant Layout Problems

Abstract

In this paper, a design for robust facility layout is proposed under the dynamic demand environment. The general strategy for a multi period layout planning problem is adaptive approach. This approach for Dynamic Plant Layout Problem (DPLP) assumes that a layout will accommodate changes from time to time with low rearrangement and production interruption costs, and that the machines can be easily relocated. On the other hand the robust layout approach, assumes that rearrangement and production interruption costs are too high and hence, tries to minimize the total material handling costs in all periods using a single layout. Robust approach suggests a single layout for multiple scenarios as well as for multiple periods. As a solution procedure for the proposed model, a Simulated Annealing (SA) algorithm is suggested, which perform well for the problems from literature and QAPLIB website. The application of suggested model for robust layout to cellular layouts has given better results compared to the robust cellular layout model of literature. For the standard DPLP of the literature, the solution values of the suggested model are very near to the results of adaptive approach. The Total Penalty Cost (TPC) is used to test the suitability of the suggested layout to be a robust layout for the given data set. TPC values indicate that the suggested layout is suitable as robust layout for the given data sets.

Introduction

To operate production and service systems efficiently, systems should not only have to be operated with optimal planning and operational policies, but also have a facility layout that is well designed. Optimal design of physical layout is an important issue in the early stage of system design and has a big influence on the long-term viability of the manufacturing system. A poorly designed layout will results in reduced productivity, increased work-in-process, increased manufacturing lead time, disordered material handling and so on. In general, the objective function for the facility layout problem is focused on reducing the Material Handling Cost (MHC). According to Chan, Chan, and Kwong (2004) the MHC assumes about 20–50% of the total operating cost of the facility layout. MHC is a non-value added cost. Efficient facilities planning can reduce these costs by at least 10–30% and thus increase the productivity. The facility layout problem is a long term, costly proposition, and any modifications or rearrangements of the existing layout represent a large expense and cannot be easily accomplished. Hence, an efficiently planned facility can reduce these costs, and thus increase productivity.

A facility layout is concerned with the location and arrangement of departments, cells or machines within the cells. The facility layout problem is often formulated as a Quadratic Assignment Problem (QAP), which assigns m departments to m locations while minimizing the MHC. However, QAP is known to be NP-complete, and optimization methods are not capable of solving problems with 15 or more facilities in a reasonable amount of time. Therefore, there is a need for heuristic methods that provide good sub-optimal solutions.

In a competitive environment, markets are heterogeneous and volatile in nature. In order for a manufacturing firm to sustain its productivity under volatile demand conditions, its production process has to be configured suitably. The ability to design and operate manufacturing facilities that can quickly and effectively adapt to changing technological and marketing requirements is becoming increasingly important to the success of any manufacturing organization. Hence, manufacturing facilities must be able to exhibit high levels of flexibility and robustness in order to deal with significant changes in their operating requirement.

When the demand is more or less constant with time, Static Plant Layout Problem (SPLP) approach is a suitable method for obtaining a good facility layout. But when demand is varying frequently with time, static layout generation approaches may not be efficient in various periods of the planning horizon. Fluctuations in product demand, changes in product mix, introduction of new products, and discontinuation of existing products are all factors that render the current facility layout inefficient and can increase MHC, which might necessitate a change in the layout (Afentakis, Millen, & Solomon, 1990). Maintaining a good facility layout requires a continuous assessment of the variations in product demands and flow between departments, and the need for Dynamic Plant Layout Problems (DPLP) approaches for the development of layouts.

The approaches that have been followed to solve the dynamic facility layout fall into two major categories.

• Adaptive or flexible or agile approach.

• Robust approach.

The first approach assumes that layout will accommodate changes from time to time with low rearrangement costs and that the machines can be easily relocated. On the other hand, a robust layout approach assumes that rearrangement costs are too high and hence tries to minimize the total material handling costs in all periods using a single layout. Robust layout approach is one of the methods used for developing layouts for multiple production scenarios of a single period problem and for multi-period problems. Robust approach suggests a single layout for multiple scenarios as well as for multiple periods. Rosenblatt (1986) made the first attempt to model the DPLP. A dynamic programming approach was used for solving the model for multiple periods. At each phase, the designer solves a static layout design problem for a specific number of alternatives. Lacksonen (1997) proposed a model to handle both rearrangement and unequal area constraints for the DPLP. This model employed a pre-processing strategy that generated solutions for large-sized problems and uses an improved branch-and-bound algorithm to yield feasible layouts. Yang and Peters (1998) proposed a flexible machine layout model which includes both material handling and machine rearrangement costs. This layout design uses a rolling horizon planning time window.

The present paper suggests a robust model for DPLP. Simulated Annealing (SA) method of layout formation is used as a solution procedure for the suggested robust model. The proposed SA method is tested for problems in literature and it is performing well in all cases of problems except in one case where the result is inferior by 0.07%. The robust model is applied to the problems of literature. Then, robust layout solution is compared with the adaptive layout solution of the problems tested. Robust layout strategy provides solution quality almost equal to the solution quality of adaptive layout strategy without production interruption and relocation. We define robust layouts as those that can effectively cope with product demand variability, over various periods of planning horizon.