Comparison of optimal buffer allocation in flow lines under installation buffer, echelon buffer, and CONWIP policies

Abstract

We compare the optimal buffer allocation of a manufacturing flow line operating under three different production control policies: installation buffer (IB), echelon buffer (EB), and CONWIP (CW). IB is the conventional policy where each machine may store the parts that it produces only in its immediate downstream buffer if the next machine is occupied. EB is a more flexible policy where each machine may store the parts that it produces in any of its downstream buffers. CW is a special case of EB where the capacities of all buffers, except the last one, are zero. The optimization problem that we consider is to maximize the average gross profit (AGP) minus the average cost (AC), subject to a minimum average throughput constraint. AGP is defined as the average throughput of the line weighted by the gross marginal profit (selling price minus production cost per part), and AC is the sum of the average WIP plus total buffer capacity plus transfer rate of parts to remote buffers, weighted by the inventory holding cost rate, the cost of storage space, and the marginal cost of transferring parts to remote buffers, respectively. Numerical results show that the optimal EB policy generally outperforms the optimal IB and CW policies. They also show that as the production rates of the machines decrease, the relative advantage in performance of the EB policy over the other two policies increases. When the cost of transferring parts to remote buffers increases, the dominance of the EB policy over the IB policy decreases while the dominance of the EB policy over CW increases.

Joint Machine Selection and Buffer Allocation in Large Split and Merge Manufacturing Systems

“…Romero-Silva and Shaaban [44] used simulation and statistical techniques to analyze the influence of buffer allocation patterns and the mean operation time configuration on the merging assembly lines' efficiency. Liberopoulos [45] proposed a two-phase optimization algorithm for solving and comparing the buffer allocation of a flow line operating under the installation buffer, echelon buffer, and CONWIP control policies. Motlagh et al [46] developed an expert system to address the processing time and BAP for production lines with time-based parameters.…”

A novel algorithm for optimal buffer allocation in automated asynchronous unreliable lines

“…It is worth mentioning that BAP is part of a larger manufacturing problem, dealing with the selection of optimal configurations for manufacturing systems. Hence, works in this field include also extended optimization problems with respect to decision variables and objective function, such as joint selection of machine and buffers with productivity performance [22], energy-efficient performance [23], transfer line [24,25] and assembly line [26] balancing, CONWIP policies [27], and time buffers [28] for cost optimization. Since the proposed work deals with BAP in serial lines, a set of relevant works is classified in Table 1.…”

Automotive Body Shop Design Problems Using Meta-Models Considering Product-Mix Change and Reconfiguration Strategy

“…Finally, as mentioned in Section 2.2, the fourth classification is the approaches used for performance evaluation such as stochastic models, simulations, and meta-models. Since there have been many survey papers related to BAP [42][43][44][45][46][47], we will not discuss BAP anymore.…”