This paper reports the results of an analysis of indicators describing the effectiveness of actions taken and repairs made by the maintenance services in a food industry company which had implemented a new manufacturing execution system (MES) 10 months prior to the study. The application of the above effectiveness indicators plays a significant role in the rationalization of functioning of maintenance services. Therefore, it is vital that they are calculated correctly and interpreted in a way that has a positive effect on the organization of maintenance works. The paper investigates four effectiveness indicators employed by the maintenance services of the company in question, i.e., mean time to failure (MTTF), mean time between failures (MTBF), mean time to repair (MTTR) and overall equipment effectiveness (OEE). The objective of the analysis was to verify the correctness of determination of the above indicators in the analysed company. In addition, the study was to determine whether the use of correctly determined indicators and results interpretation could lead to a higher effectiveness of the actions taken by the maintenance services department. Moreover, the paper presents a diagnosis of problems connected with incorrect determination and visualization of the above-mentioned indicators in the analysed company.

The article deals with a widely used method of measuring the overall efficiency of equipment (OEE), which in combination with technologies and software tools is gaining in importance. The overall efficiency of OEE equipment is a key performance metric for machines and equipment to identify hidden capacities and increase production productivity. The intensification of Industry 4.0 in traditional manufacturing companies supports and creates the conditions for their transformation into a smart factory. The integration of intelligent machines and devices with complex human-machine communication network systems requires a new direction in measuring and increasing OEE. Mass customization, resp. personalization of production raises a high need to monitor, improve and further maintain productivity. The aim of the article is to create a simulation model of the production process and test the energy consumption of selected equipment using TX Plant Simulation software with a proposal of measures to increase the OEE of the company.

In the article problems related to human labor and factors affecting the increasing use of

industrial robots are discussed. Since human factors affect the production processes stability,

robots are preferred to apply. The application of robots is characterized by higher performance

and reliability comparing to human labor. The problem is how to determine the real

difference in work efficiency between human operator and robot. The aim of the study is to

develop a method that allows clearly definition of productivity growth associated with the

replacement of human labor by industrial robots. Another aim of the paper is how to model

robotized and manual operated workstation in a computer simulation software. Analysis of

the productivity and reliability of the hydraulic press workstation operated by the human

operator or an industrial robot, are presented. Simulation models have been developed taking

into account the availability and reliability of the machine, operator and robot. We apply

OEE (Overall Equipment Effectiveness) indicator to present how availability and reliability

parameters influence over performance of the workstation, in the longer time. Simplified

financial analysis is presented considering different labor costs in EU countries.

The problem of production flow in steel casting foundry is analysed in this paper. Because of increased demand and market competition, a reorganisation of the foundry process is required, including the elimination of manual labour and the implementation of automation and robotisation of certain processes. The problem is how to determine the real difference in work efficiency between human workers and robots. We show an analysis of the production efficiency of steel casting foundry operated by either human operators or industrial robots. This is a problem from the field of Operations Research for which the Discrete Event Simulation (DES) method is used. Three models are developed, including the foundry before and after automation when taking into consideration parameters of the availability of machines, operators and robots. We apply the OEE (Overall Equipment Effectiveness) indicator to present how the availability, performance and quality parameters influence the foundry’s productivity. In addition, stability of the simulation model was analysed. This approach allows for a better representation of real production processes and the obtained results can be used for further economic analysis.