In this paper we present the case study for the optimization of the production line by using the balancing and discrete event simulation approach. First the basic theory and steps for the production line balancing are presented. For the real production process, consisting of two production lines and an assembly workplace the simulation model is built and the initial results obtained. After balancing of the production process and improvement of its performance some further steps of the process optimization by using the improved simulation model are performed. The results of the combination of the line balancing and further process optimization raise the production rate of the process enormously, which is obvious from the research results of this paper.

The proposed hybrid algorithm is a combination of heuristic algorithm extended with priority rules, discrete event simulation and genetics algorithm. It takes into account 11 different priority rules and scenarios, is based on the assumption that for a realistic workshop scheduling of orders, it is necessary to consider real throughput times of the operations, otherwise the obtained scheduling of orders is not suitable for the industrial environment. The simulation result for the proposed model is the optimal sequence of selected orders for the selected time interval while taking into account three criteria: the minimum flow time of all orders, the maximum average utilization of workplaces, and the minimum waiting time of the orders. Because the mentioned criteria are usually mutually exclusive the advantage of the proposed model is that we can find the optimum with respect to all three criteria. In the paper, an example of the application of the proposed model is shown.

An analysis of a product line of small and medium-sized enterprises (SME) shows that products (component parts or assemblies) are quite similar in terms of design and technology, thus clusters of products are formed. For each cluster a production cell can be organized. According to the product line of a company a certain number of individual production cells is organized, while workshop production is retained for the remaining product line.The paper shows how clusters of products are designed on the basis of a product line data and how an ideal layout optimization is determined on the basis of the intensity of material flow. Layout optimization of a production cell is based on a combination of Schmigalla modified triangular method and the Schwerdfeger circular process. The method was applied on a cluster of 20 orders similar in design and technology that are processed at 10 workplaces. At the end of the article a transition from a theoretical O-cell to a real U-cell is suggested.

This paper presents a novel approach to implement manufacturing nodes using the combined strength of digital twins, holons, and digital agents. Manufacturing nodes are based on holon theory and present a universal manufacturing platform that consists of cyber-physical systems (CPS) with an integrated digital twin, digital agent, databases and various communication protocols. The manufacturing node network is controlled globally using the global digital twin of logistics process and locally using the local nodes and local digital agents, digital twins and information shared by the node network. The main objective of this research was to develop and test a new concept of distributed system modelling and distributed system control for easy implementation of distributed manufacturing nodes in a smart factory concept.

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