LAPSE:2023.11404
Published Article

LAPSE:2023.11404
Optimization of the Automated Production Process Using Software Simulation Tools
February 27, 2023
Abstract
The purpose of this article is to point out the need to use software simulation tools in industrial practice to optimize the production process and assess the economic effectiveness of investment, including risk. The goal of the research is to find an optimal investment variant to ensure an increase in the production volume of at least 50% and to achieve the maximum economic efficiency of the investment, even considering the risk. The article presents a comprehensive approach that enables the achievement of the set research goal. The selection of the optimal version of the investment is carried out in three steps. Firstly, the versions of the investment variants are assessed from the production point of view using the program Tecnomatix Plant Simulation. Subsequently, the versions of the investment variants are assessed from an economic point of view and from a risk point of view. Economic efficiency is assessed using the financial criteria net present value (NPV), profitability index (PI), and discounted payback period (DPP), and risk analysis is carried out using Monte Carlo simulations. Finally, the accepted outputs are evaluated overall using a multi-criteria method, namely the method of partial order.
The purpose of this article is to point out the need to use software simulation tools in industrial practice to optimize the production process and assess the economic effectiveness of investment, including risk. The goal of the research is to find an optimal investment variant to ensure an increase in the production volume of at least 50% and to achieve the maximum economic efficiency of the investment, even considering the risk. The article presents a comprehensive approach that enables the achievement of the set research goal. The selection of the optimal version of the investment is carried out in three steps. Firstly, the versions of the investment variants are assessed from the production point of view using the program Tecnomatix Plant Simulation. Subsequently, the versions of the investment variants are assessed from an economic point of view and from a risk point of view. Economic efficiency is assessed using the financial criteria net present value (NPV), profitability index (PI), and discounted payback period (DPP), and risk analysis is carried out using Monte Carlo simulations. Finally, the accepted outputs are evaluated overall using a multi-criteria method, namely the method of partial order.
Record ID
Keywords
investment efficiency assessment, production process, risk assessment, simulations
Suggested Citation
Janeková J, Fabianová J, Kádárová J. Optimization of the Automated Production Process Using Software Simulation Tools. (2023). LAPSE:2023.11404
Author Affiliations
Janeková J: Institute of Industrial Engineering, Management, Environmental Engineering and Applied Mathematics, Faculty of Mechanical Engineering, Technical University of Kosice, Park Komenského 5, 04001 Košice, Slovakia
Fabianová J: Institute of logistics and Transport, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letná 9, 04200 Košice, Slovakia
Kádárová J: Institute of Industrial Engineering, Management, Environmental Engineering and Applied Mathematics, Faculty of Mechanical Engineering, Technical University of Kosice, Park Komenského 5, 04001 Košice, Slovakia
Fabianová J: Institute of logistics and Transport, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letná 9, 04200 Košice, Slovakia
Kádárová J: Institute of Industrial Engineering, Management, Environmental Engineering and Applied Mathematics, Faculty of Mechanical Engineering, Technical University of Kosice, Park Komenského 5, 04001 Košice, Slovakia
Journal Name
Processes
Volume
11
Issue
2
First Page
509
Year
2023
Publication Date
2023-02-08
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr11020509, Publication Type: Journal Article
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LAPSE:2023.11404
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https://doi.org/10.3390/pr11020509
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Feb 27, 2023
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