A nonlinear model for optimizing the performance of a multi-product production line

Abstract

This paper examines the measures of performance and in particular addresses the throughput of an automated production line processing multiple products. The line is composed of a sequence of workstations connected in series with finite buffers in between. We explore the effects of buffer size on attenuating the impact of line blocking and starvation that can cause a reduction in the output. Such effects are analyzed through a nonlinear mathematical programming model and the implications are examined. The aim of the model is to achieve the best performance subject to available workstation capacity without overexpenditure on buffer size. Single and multi‐objective optimizations are carried out in the paper. A numerical example of a production line with a given configuration of workstations; workstation capacity; and job mix is presented to demonstrate the model and its application. A discussion of the impact of buffer size on maximum throughput is also provided. The paper is concluded with a discussion on the decision‐making implications.

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“…This is because DES as an OR technique can be utilized to solve problems in any sector of the economy and to support decision‐making in any operations activities involving service or product. For example, a previous study identified 32 application domains where DES was utilized to solve operations and optimization problems (Abdul‐Kader et al., 2011; Akpan and Brooks, 2012; Akeb and Hifi, 2008; Akpan and Brooks, 2014). As COVID‐19 impacted nearly every sector of the global economy, scientists utilized the DES technique to address pandemic‐related issues in many operational areas and service sectors.…”

Optimal Buffer Allocation in Multi-Product Repairable Production Lines Based on Multi-State Reliability and Structural Complexity

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