Author:
Wa-Muzemba Tshibangu
Affiliation:
Department of Industrial and Systems Engineering, Morgan State University, 1700 E. Cold Spring Lane, Baltimore, Maryland 21251, U.S.A.
Keyword(s):
Flexible Manufacturing System (FMS), Discrete-Event Simulation, Taguchi, Design of Experiments (DOE), Robust Design, Single-Objective Optimization, ANOVA, T-Test, Normal Probability Plot.
Abstract:
During the lockdowns following the Covid-19 pandemic many companies have become flexible by implementing new manufacturing technologies, such as group technology (GT), just-in-time (JIT) production systems, and flexible manufacturing systems (FMSs) that, hence, become among the solutions of the future. This paper uses the emergence of these systems to present an alternative robust design formulation to Taguchi methodology before proposing a single-objective optimization scheme to find the optimal operational settings of primary individual key performance indicators (KPIs). The study uses the Throughput Rate (TR) and the Mean Flow Time (MFT) as illustrative examples of KPIs, tracked over a range of AGV fleet sizes. Additional KPIs, e.g., Work-in-process (WIP), Machine utilization, and AGV utilization are also analyzed as secondary measures to validate and fine-tune the results of the procedure. The study deploys and uses in association multiple statistical tools for a proper analysis
and validation of the technique. The effectiveness of the proposed model is validated by comparing the results to some other similar approaches. Although derived from simulation of manufacturing operations, the framework presented in this paper can be applied to various industries including food production, financial institutions, warehouse industry, and healthcare.
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