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Purpose: The paper presents the basic assumptions and the plan of the research work, which is directed at implementing a CMMS class system in a selected manufacturing enterprise to support selected maintenance tasks. Design/methodology/approach: The research conducted at the company was based on participant observation, using social research techniques and a tool from the Root Cause Analysis group. Findings: The analysis and diagnosis results were used to develop proposals for implementing a system to support maintenance and repair tasks in selected segments of the production system. These proposals included tool and organizational solutions to increase the efficiency and effectiveness of maintenance activities. Research limitations/implications: While the issue of maintenance is a key component of manufacturing engineering, the article does not address other equally important areas, such as process design, optimization or quality control, which, with an integrated approach to manufacturing engineering, could lead to synergistic results. Practical implications: The introduction of solutions based on the TPM paradigm will make it possible to systematically increase the stability of the production process by improving maintenance processes and reducing the risk and severity of the consequences of downtime and failures. Originality/value: The paper's novelty is its systematic approach, which provides a practical framework for implementing a CMMS in a manufacturing environment. The diagnostic process and the resulting proposals for using the system to support maintenance and repair tasks in selected segments of the production system represent a form of process innovation. The paper is aimed at manufacturing companies seeking to improve maintenance operations and increase productivity by implementing modern management systems. [ABSTRACT FROM AUTHOR]

The research aims to characterise the optimisation of a technological process depending on the main time parameters for production. The optimisation does not require to correct technical parameters of a system, but rather the organisational and managerial factors of the technological process. The workload is taken as an evaluation criterion, which factors in the probability distribution of time characteristics of computer process operations. Time characteristics that represent the performance of an operation influence the workloads of an operator and equipment, determining the productivity of the technological process. Analytical models were developed for the operational control of a production line efficiency considering the probability–statistical parameters pertaining to the performance of operations and technological equipment peculiarities. The article presents research results, which characterise the dependence of a production line efficiency on the type of equipment, and the duration of preparatory and final operations considering their probability. Under an optimal workload of the operator, the duration of the complete program changes linearly, regardless of the time required for the performance of operations by a computer without the involvement of the operator, and depending on the type of equipment. A managerial decision can be optimal under the condition that the factor of technological process efficiency (K_TP) tends to max. The developed method of analytical determination can be used to calculate the workload of both an operator and technological equipment. The calculations of the duration of a production line operation resulted in the methodology for the consideration of probability characteristics pertaining to the time distribution of the period required to perform operations, which influences the unequal efficiency of the production line. The probabilistic character of time distribution related to intervals of performed operations serves as a parameter in the management of technological process optimisation, which can be achieved using simulators of technological processes optimised in terms of their efficiency.

Almost every branch of industry, at a certain point, utilizes omnifarous materials in their granular form. A key constituent in many bulk material logistic systems is the hopper, which usually acts as a buffering component. In order to achieve the desired throughput, the geometry of the particular hopper must be carefully determined. Considering the geometric properties of the given hopper, the inclination of the walls and the outlet orifice characteristics are the pivotal determinants of hopper functionality. In this paper, the authors have developed an analytical model of the conical hopper's mass efficiency and compared the model with the experimental results for two distinctive granular materials. The model inputs were: the density of the bulk material, critical angle of material repose, generatrix inclination angle of the cone, and diameter of the circular outlet. The experiment was conducted according to a 32 full factorial design. The repeatability of the results was examined according to Cochran's theorem and the adequacy of the data was evaluated via Fisher's criterion, which confirmed the quality of the mathematical model. The error of the developed model does not exceed 4.5%. [ABSTRACT FROM AUTHOR]

The research is aimed at creating a methodology for increasing the positioning accuracy of an industrial robot and minimizing the vibration of the robot gripper by applying machine learning based on the developed mathematical model for estimating the positioning error. Two components of positioning accuracy are considered: geometric and kinematic errors and elastic static deformations. The dynamic error in the partial system of motion of the robot manipulator links is analyzed. The equation of partial motions is obtained from Lagrange's differential equation of motion of the II kind. The system of differential equations for the positioning error was solved analytically by Euler's method. An example of modeling the position and orientation error of the gripper due to temperature deformations of the third link for the manipulator scheme is given. An example of the modeling of static deformations and errors of the manipulator with elastic pliability of the robot links is given. An example of dynamic error modeling in a partial system of motion of the robot links is given. The proposed method of modeling robot gripper positioning errors makes it possible to increase the positioning accuracy of the industrial robot and minimize the vibration of the gripper. Having a mathematical model of positioning errors, it is possible to compensate for the positioning error by changing the speed of movement of the gripper reference point before determining the direct kinematic task. [ABSTRACT FROM AUTHOR]

Two systems of milking machines were considered - biotechnical and vacuum. Methodology for estimation of efficiency of the "machine-animal" biotechnical system was worked out. The dependences of the efficiency parameters of the technical system operation were analyzed. The KMMO operator load factor of the milking machine was proposed. The factor characterizes the technological process of the machine milking. The analytical dependences were worked out for the simulation of the productivity of milking machines and oscillation of the vacuum-gage pressure. As to the simulation results, when the vacuum pipeline diameter was increased the oscillation of the vacuum-gage pressure decreased. The results of analysis and theoretical researches on technological process of the cow machine milking gave a possibility to define the requirements to the improvement of technological process and technical equipment, which will provide the increase of efficiency of the milking systems. Usage of the developed cyber-physical system of the machine milking of cows will increase the productivity of the milking machine in 1.26…1.85 times. At the vacuum gage pressure oscillation of ΔPvp = 2500 Pa the suction ability of milking machine will be E=4.093 m/s accordingly. The defined index of efficiency of the adapted systems functioning of the milking machine is KBTS2 = 55.3.