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Smart Factory is a complex system that integrates the main elements of the Industry 4.0 concept (e.g., autonomous robots, Internet of Things, and Big data). In Smart Factories intelligent robots, tools, and smart workpieces communicate and collaborate with each other continuously, which results in self-organizing and self-optimizing production. The significance of Smart Factories is to make production more competitive, efficient, flexible and sustainable. The purpose of the study is not only the introduction of the concept and operation of the Smart Factories, but at the same time to show the application of Simulation and Artificial Intelligence (AI) methods in practice. The significance of the study is that the economic and social operational requirements and impacts of Smart Factories are summarized and the characteristics of the traditional factory and the Smart Factory are compared. The most significant added value of the research is that a real case study is introduced for Simulation of the operation of two collaborating robots applying AI. Quantitative research methods are used, such as numerical and graphical modeling and Simulation, 3D design, furthermore executing Tabu Search in the space of trajectories, but in some aspects the work included fundamental methods, like suggesting an original whip-lashing analog for designing robot trajectories. The conclusion of the case study is that—due to using Simulation and AI methods—the motion path of the robot arm is improved, resulting in more than five percent time-savings, which leads to a significant improvement in productivity. It can be concluded that the establishment of Smart Factories will be essential in the future and the application of Simulation and AI methods for collaborating robots are needed for efficient and optimal operation of production processes.

Abstract. In a competitive market the manufacturing companies have to produce cost effective products which can be realized by minimized production cost and higher effectiveness. The effective facility planning can significantly reduce the operational costs of companies. An adequate facility layout can result in the improvement of the performance of the production line. The Facility Layout Problem (FLP) is relating to location of objects (departments, workstations, machines, etc.) on a given site and the material flow between these objects. The goal of this study is to show the reasons, objectives and steps of a layout redesign process. The minimization of the workflow realized on the shop floor is an often applied an objective function during the layout redesign. Material flow efficiency is a commonly used term for the determination of the amount of workflow, which is the multiplication of material flow data and distance data. In this study, this mathematical method for workflow calculation is introduced. The described case study shows how the efficiency and reduced manufacturing cost of a real manufacturing system can be improved by re-layout design, while smaller floor space is needed for the production.

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The application of the Industry 4.0′s elements—e.g., industrial robots—has a key role in the efficiency improvement of manufacturing companies. In order to reduce cycle times and increase productivity, the trajectory optimization of robot arms is essential. The purpose of the study is the elaboration of a new “whip-lashing” method, which, based on the motion of a robot arm, is similar to the motion of a whip. It results in achieving the optimized trajectory of the robot arms in order to increase velocity of the robot arm’s parts, thereby minimizing motion cycle times and to utilize the torque of the joints more effectively. The efficiency of the method was confirmed by a case study, which is relating to the trajectory planning of a five-degree-of-freedom RV-2AJ manipulator arm using SolidWorks and MATLAB software applications. The robot was modelled and two trajectories were created: the original path and path investigate the effects of using the whip-lashing induced robot motion. The application of the method’s algorithm resulted in a cycle time saving of 33% compared to the original path of RV-2AJ robot arm. The main added value of the study is the elaboration and implementation of the newly elaborated “whip-lashing” method which results in minimization of torque consumed; furthermore, there was a reduction of cycle times of manipulator arms’ motion, thus increasing the productivity significantly. The efficiency of the new “whip-lashing” method was confirmed by a simulation case study.