Martin Marschall

The European vision of the Factory of the Future is based on increasing competition and sustainability by transformation from cost orientation to high-adding value with technical and organisational innovations. One of the expected outcomes is an increase in modularisation, i.e., the reconfigurability of the technical system in manufacturing conditions. Modular manufacturing systems (MMS), will consist of modular platforms (MP) that are capable of rapid rebuilding, and reconfiguration performed by adding or removing a module by Mobile Robotic Systems (MRS). In the conditions of MMS, to make the most efficient use of reconfiguration MRS capacities, it is necessary to know the optimal ratio of these MRS to the number of modular platforms (MP) used in MMS, which does not exist today. This ratio will help industrial companies that are deploying MMS-based solutions to plan the number of MRSs needed to reconfigure deployed systems. As a method of determining this optimal ratio, an experimental approach via simulation was chosen, using data from custom MRS and MP prototypes with testing different layouts of modular platforms with the view of warehouse layout, manufacturing island, manufacturing island power supply, and MRS. Based on the results, it can be determined that the MP-MRS limit ratio is 2:1, where the further increase in MRS has only a minimal impact on the reconfiguration period. With the reduction of MP transferred to one MRS, there is a gradual decrease in the time required for reconfiguration. When the ratio of 1:1 is attained, the time required for reconfiguration lowers, but not as dramatically as in bigger ratios.

Nowadays, many factories face changes on the global market and manufacturing is unpredictable. This fact creates a demand for developing new concepts of the factory which can represent a solution to these changes. This study presents a way for designing these new factory concepts, particularly a concept of the reconfigurable manufacturing lines. The methodology in this study uses characteristics of reconfigurable manufacturing systems for developing an algorithm for designing the basic factory layout. The methodology also combines classical math operations for designing the production layout with such approaches as simulation, cluster analysis, and LCS algorithm. This combination method with LCS algorithm and an entirely different approach to the design of the manufacturing line, has not yet been used. The accuracy of this methodology is then verified through the results of the complete algorithm containing these features. The main purpose of this study was to find new approaches to designing the reconfigurable factory layout. This article is presenting new ways that differ from the classical design method. The article suggests the new way is possible and the new systems also need new ways for designing and planning.

Current trends in manufacturing, which are based on customisation and gradually customised production, are becoming the main initiator for the development of new manufacturing approaches. New manufacturing approaches are counted as the application of new behavioural management patterns that calculate the retained competencies of decision-making by the individual members of the system agent; the production becomes decentralised. The interaction of the members of such a system creates emergent behaviour, where the result cannot be accurately determined by ordinary methods and simulation must be applied. Modelling and simulation will, therefore, be an integral part of the planning and control of the processes of factories of the future. The purpose of the article is to describe the use of modelling and simulation processes in factories of the future. The first part of the article describes new manufacturing concepts that will be used in factories of the future, with a description of modelling and simulation routing in the frame of Industry 4.0. The next section describes how simulation is used for the control of manufacturing processes in factories of the future. The included subsection describes the implementation of this suggested pattern in the laboratory of ZIMS (Zilina Intelligent Manufacturing System), with an example of a metamodeling application and the results obtained.

Route planning in a multi-agent system (MAS) is still a complex task, especially if there is need for a continuous, decentralized planner of the routes for physical agents in a dynamic environment. It is a planner of this kind that is required in the application the article considers: the transportation of parts at a modular manufacturing line. Such a planner has to meet several difficult requirements, regarding the physical, time-constrained dynamic environment, live-locks and deadlocks, delayed agents, and last needs to minimize the travel time and the total distance traveled. The article proposes an approach using a delegate multi-agent system (D-MAS) in order to meet these requirements. The approach was verified using virtual reality so as to provide a better understanding of the planner’s issues. Several coordination rules were proposed and implemented. As a further verification, the proof-of-concept solution was compared to a non-reservation planner. It was shown, that as the number of agents increases, the approach, including the reservations, outperformed its competitor. Various recommendations for the implementation of the planner were formulated. It was concluded that the performance of the planner is sufficient for its future use. The main objective of article was proof-of-concept and determining the functionality of a prototype based on MAS that was in compliance with a modular manufacturing line developed by us.