### Existing Work Discussion  
Scheduling of production and related processes was researched in many works. The authors analyze the processes of scheduling, dividing the problems occurring in it into: types of production systems [14], the occurrence of the phenomenon of randomness [15], the dynamics of processes and changes in time [11], or their relation to practice [1]. Task scheduling problems are considered in various production environments. The flow-shop [16], job-shop [17] and open-shop environments [18] are the most frequently analyzed in the literature. Due to the fact that the robotization of various production processes often involves several of these areas simultaneously--in the literature, one can clearly distinguish the area of task scheduling in which industrial robots are used. Then, the implementation of robots is analyzed in terms of their impact on the overall processes [9; 10; 19], serialization of robot tasks for specific jobs [20; 21], or precise determination of robot paths [5; 22]. Upon analyzing the literature in the above-mentioned areas, it can be observed that the number of publications in recent years increased significantly. This proves the relevance of the issues raised, as well as the timeliness of research in this area. In the area of works on production scheduling, the authors try to supply the classical problems with issues related to the use of robots. In the research related to the field of production scheduling, attention is paid to the use of robots in processes of the handling type [23], and well-known scheduling methods, such as the Branch and Bound method, are used to solve such problems. For example, in [10], a robot is used for transporting elements between two production stations, and the authors analyze its impact on the schedule, with the target criterion being the execution time of all orders. In turn, the work [24] considers a flexible flow-shop class system, in which the robot has the task of handling three technological machines moving along a running track. Many papers in this area also emphasize that robotic environments are highly dynamic, and thus the formulated problems are characterized by considerable computational complexity [9; 23]. Sometimesthe problem of scheduling with several robots is discussed [25; 26], but this issue more often concerns cooperation between robots or a detailed analysis of robot paths. In the case of work serialization in specific production processes, the authors usually place focus on thorough analyses of robot paths while omitting the important aspect of robot task serialization. Various processes are described using the classical Travelling-Salesman Problem (TSP) [19; 20], and numerous algorithms are used to solve the problem. Gene-type algorithms are most often applied [9; 20]. The authors propose solutions with detailed process parameters considered [27]. For example, in [20] the authors address the issue of shortening the transition paths by analyzing the coordinates of the trajectories. In turn [5], they present a solution aiming at appropriate path planning with simultaneous force control in the process of robotic grinding. The works very often deal with the aspect of the occurrence of collisions between the elements of the infrastructure of robotic workstations [9], with the target criterion usually being the execution time of the robot tasks [10]. Approaches based on artificial intelligence are increasingly proposed in the literature also [28; 29]. The utilization of AI techniques provides control process automation and simplification [30; 31]. Moreover, the mentioned solutions are applicable in the whole production systems analysis [32]. The problems of planning robot paths are subjected to multi-criteria analysis. The relations between shortening paths, minimizing costs, excluding collisions and reducing the failure rate of robots are sought as solutions [17; 33; 34].