Decision Support Simulation Method for Process Improvement of Intermittent Production Systems

Abstract

Nowadays production system processes are undergoing sweeping changes. The trends include an increase in the number of product variants to be produced, as well as the reduction of the production's lead time. These trends were induced by new devices of the industry's 4.0, namely the Internet of Things and cyber physical systems. The companies have been applying intermittent production systems (job production, batch production) because of the increase in the number of product variants. Consequently, increasing the efficiency of these systems has become especially important. The aim of development in the long term-not achievable in many cases-is the realization of unique production, with mass production's productivity and lower cost. The improvement of complex production systems can be realized efficiently only through simulation modeling. A standardized simulation method for intermittent production systems has not been elaborated so far. In this paper, I introduce a simulation method for system improvement and present its application possibilities and a practical example.

Two - Echelon Vehicle Routing Problem with Recharge Stations

“…Each customers can belong to only one satellite: (19) The satellite-customer routes, which belong to the . satellite, can be taken after the service of the depot-satellite level.…”

“…In the age of the fourth industrial revolution, versatile solutions for manufacturing and logistics systems are required to increase the utilization, reliability, flexibility and cost efficiency. The diversified customers' demands present manufacturing systems with new challenges (Tamás, 2017). Matrix production may become a suitable solution through configurable production cells, the transfer of parts and tools using automated guided vehicles (AGVs) and the separation of logistics from production.…”

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Special Issue on Modeling, Simulation, Operation and Control of Discrete Event Systems

“…Three strategies, based on exhaustive search, genetic algorithms and a greedy heuristic, respectively, are formulated, which have been implemented and tested. The eighth paper [14], contributed by Tamás, dwells upon decision support simulation for intermittent production systems that represent an important class of industrial processes. As claimed by the author, the proposed simulation method takes less time than the earlier methods (the modeling steps are clear and simple to implement) and it can also examine every complex intermittent production system by using the elaborated investigational method.…”