Otwarty dostęp

Analysis of the Impact of Effective Time Management on Workstation Efficiency Using a Multi-Criteria Optimization Approach

   | 01 sie 2023

Zacytuj

M. Krynke, “Management optimizing the costs and duration time of the process in the production system,” Production Engineering Archives, vol. 27, no. 3, pp. 163-170, 2021, doi: 10.30657/pea.2021.27.21. Search in Google Scholar

M. Krynke, “Personnel Management on the Production Line Using the FlexSim Simulation Environment,” Manufacturing Technology, vol. 21, no. 5, pp. 657-667, 2021, doi: 10.21062/mft.2021.073. Search in Google Scholar

S. Luscinski and V. Ivanov, “Management and Production Engineering Review,” 2020. Search in Google Scholar

M. Ingaldi and D. Klimecka-Tatar, “Digitization of the service provision process - requirements and readiness of the small and medium-sized enterprise sector,” Procedia Computer Science, vol. 200, pp. 237-246, 2022, doi: 10.1016/j.procs.2022.01.222. Search in Google Scholar

R. Ulewicz and K. Mielczarek, “Machine operation efficiency in the production of car equipment,” in 13th International Scientific Conference 2022, p. 50070. Search in Google Scholar

M. Beaverstock, A. Greenwood, and W. Nordgren, Applied simulation: modeling and analysis using FlexSim, 5th ed.: Published by FlexSim Software Products, Inc., Canyon Park Technology Center, Building A Suite 2300, Orem, UT 84097 USA., 2017. Search in Google Scholar

M. Laguna, OptQuest, 2011. [Online]. Available: https://www.opttek.com/sites/default/files/pdfs/optquest-optimization%20of%20complex%20systems.pdf Search in Google Scholar

M. Frantzén, A. H. Ng, and P. Moore, “A simulation-based scheduling system for real-time optimization and decision making support,” Robotics and Computer-Integrated Manufacturing, vol. 27, no. 4, pp. 696-705, 2011, doi: 10.1016/j.rcim.2010.12.006. Search in Google Scholar

M. O. Mohammadi, T. Dede, and M. Grzywiński, “Solving a stochastic time-cost-quality trade-off problem by meta-heuristic optimization algorithms,” BoZPE, vol. 11, 2022.11, pp. 41–48, 2022, doi: 10.17512/bozpe.2022.11.05. Search in Google Scholar

Z. Čičková, M. Reiff, and P. Holzerová, “Applied multi-criteria model of game theory on spatial allocation problem with the influence of the regulator,” PJMS, vol. 26, no. 2, pp. 112-129, 2022, doi: 10.17512/pjms.2022.26.2.07. Search in Google Scholar

. N. Ivanova, W. Biały, A. I. Korshunov, J. Jura, K. Kaczmarczyk, and K. Turczyński, “Increasing Energy Efficiency in Well Drilling,” Energies, vol. 15, no. 5, p. 1865, 2022, doi: 10.3390/en15051865. Search in Google Scholar

D. Siwiec, A. Pacana, and R. Ulewicz, “Concept of a model to predict the qualitative-cost level considering customers’ expectations,” PJMS, vol. 26, no. 2, pp. 330-340, 2022, doi: 10.17512/pjms.2022.26.2.20. Search in Google Scholar

O. Shatalova, E. Kasatkina, and V. Larionov, “Multi-criteria Optimization in Solving the Problem of Expanding Production Capacity of an Enterprise as a Method of Modeling Strategic Directions for the Development of Production Systems,” MATEC Web Conf., vol. 346, p. 3105, 2021, doi: 10.1051/matecconf/202134603105. Search in Google Scholar

N. L. P. Hariastuti and Lukmandono, “A Review on Sustainable Value Creation Factors in Sustainable Manufacturing Systems,” Production Engineering Archives, vol. 28, no. 4, pp. 336-345, 2022, doi: 10.30657/pea.2022.28.42. Search in Google Scholar

M. Krynke and D. Klimecka-Tatar, “Production costs management in process supported by external entities – Process flow optimization,” in 13th International Scientific Conference 2022, p. 50068. Search in Google Scholar

S. M. Kalinović, D. I. Tanikić, J. M. Djoković, R. R. Nikolić, B. Hadzima, and R. Ulewicz, “Optimal Solution for an Energy Efficient Construction of a Ventilated Façade Obtained by a Genetic Algorithm,” Energies, vol. 14, no. 11, p. 3293, 2021, doi: 10.3390/en14113293. Search in Google Scholar

V. V. Borisova, O. V. Demkina, A. V. Mikhailova, and R. Zieliński, “The enterprise management system: evaluating the use of information technology and information systems,” PJMS, vol. 20, no. 1, pp. 103-118, 2019, doi: 10.17512/pjms.2019.20.1.09. Search in Google Scholar

J. April, F. Glover, J. P. Kelly, and M. Laguna, “Practical introduction to simulation optimization,” in Proceedings of the 2003 Winter Simulation Conference: Fairmont Hotel, New Orleans, LA, U.S.A., December 7-10, 2003, New Orleans, LA, USA, 2004, 2003, pp. 71–78. Search in Google Scholar

C. Kardos, C. Laflamme, V. Gallina, and W. Sihn, “Dynamic scheduling in a job-shop production system with reinforcement learning,” Procedia CIRP, vol. 97, pp. 104–109, 2021, doi: 10.1016/j.procir.2020.05.210. Search in Google Scholar

J. April, M. Better, F. Glover, J. Kelly, and M. Laguna, “Enhancing Business Process Management with Simulation Optimization,” in Proceedings of the 38th conference on Winter simulation, Monterey, CA, USA, Dec. 2006 - Dec. 2006, pp. 642-649. Search in Google Scholar

F. P. Santos, Â. P. Teixeira and C. G. Soares., “Modeling, simulation and optimization of maintenance cost aspects on multi-unit systems by stochastic Petri nets with predicates,” SIMULATION, vol. 95, no. 5, pp. 461-478, 2018, doi: 10.1177/0037549718782655. Search in Google Scholar

M. W. Sari, Herianto, I. B. Dharma, and A. E. Tontowi, “Integrated Production System on Social Manufacturing: A Simulation Study,” Management Systems in Production Engineering, vol. 30, no. 3, pp. 230-237, 2022, doi: 10.2478/mspe-2022-0029. Search in Google Scholar

M. Krynke, K. Mielczarek, and O. Kiriliuk, “Cost Optimization and Risk Minimization During Teamwork Organization,” Management Systems in Production Engineering, vol. 29, no. 2, pp. 145-150, 2021, doi: 10.2478/mspe-2021-0019. Search in Google Scholar

V. A. Zherebko, O. A. Pisarenko, and V. P. Drabynko, “Simulation and genetic optimization of control systems by lab-view programming” Problems in programming, no. 2-3, pp. 288-295, 2018, doi: /10.15407/pp2018.02.288. Search in Google Scholar

J. Tabor, “Ranking of management factors for safe maintenance system based on Grey Systems Theory,” Production Engineering Archives, vol. 27, no. 3, pp. 196-202, 2021, doi: 10.30657/pea.2021.27.26. Search in Google Scholar

M. Daroń, “Simulations in planning logistics processes as a tool of decision-making in manufacturing companies,” Production Engineering Archives, vol. 28, no. 4, pp. 300-308, 2022, doi: 10.30657/pea.2022.28.38. Search in Google Scholar

M. Rostek, “Productivity and improvement of logistics processes in the company manufacturing vehicle semi-trailers – Case study,” Production Engineering Archives, vol. 28, no. 4, pp. 309-318, 2022, doi: 10.30657/pea.2022.28.39. Search in Google Scholar

T. Pukkala and J. Kangas, “A heuristic optimization method for forest planning and decision making,” Scandinavian Journal of Forest Research, vol. 8, 1-4, pp. 560–570, 1993, doi: 10.1080/02827589309382802. Search in Google Scholar

A. Jerbi, A. Ammar, M. Krid, and B. Salah, “Performance optimization of a flexible manufacturing system using simulation: the Taguchi method versus OptQuest,” Simulation, 2019, doi: 10.1177/0037549718819804. Search in Google Scholar

FlexSim, User manual, 2017. Search in Google Scholar