Modelling Decision-Making Processes in the Management Support of the Manufacturing Element in the Logistic Supply Chain

Robert Bucki,Petr Suchánek

doi:10.1155/2017/5286135

Robert Bucki, Petr Suchánek

Open Access

https://doi.org/10.1155/2017/5286135

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Abstract

This paper highlights the problems of mathematical modelling for a specific element of the logistic supply chain, that is, the manufacturing system. The complex manufacturing system consisting of a determined number of parallel subsystems is modelled. The fact that the same manufacturing procedure can be carried out in various locations is emphasised. Control algorithms as well as manufacturing strategies are explained. The equations of state are introduced. The two-stage criterion lets us use the result data generated by the simulator of the production system as the initial data for further processing; however, the main goal remains to minimise the time of the course of production. The precisely elaborated case study implements initial data obtained by preceding simulation procedures carried out in manufacturing systems consisting of three, four, and five subsystems.

Highlights

Nowadays, design and optimisation of logistic and production systems is a demanding and important area
To survive in the highly competitive global economy, manufacturing systems must be able to adapt to new circumstances [1]
Production systems may vary in terms of their complexity

Summary

Introduction

Design and optimisation of logistic and production systems is a demanding and important area. The main goal of this article is to define and simulate the mathematical model for the evaluation of the distribution of production in several plants within one complex company to achieve maximum production in the shortest possible time and minimise costs of manufacturing. The proposed model represents one of the possible solutions for optimising production in case of dislocated companies which are at disposal It is significant as it is possible to use it for a particular realistic case described by the defined structure and, it can be treated as one of the scientific bases for solving similar examples (e.g., adaptation of the model for other structures, implementation of other decision-making algorithms, and expansion of other evaluation parameters, for example, from the set of key performance indicators (KPI) of the company)

Mathematical Model

Case Study

Conclusions