The Use of Computer Simulation in the Management of Subcontractors and Outsourced Services
KRYNKE Marek
download PDFAbstract. The paper examines cooperation among production companies to fulfill orders beyond plant capacity by selecting subcontractors. The developed model focuses on planning the production process to minimize total production costs by deciding where to produce goods before they are actually produced. The concept utilized a 3D FlexSim simulation environment, specifically the built-in optimization module OptQuest, to address the problem. The paper covers the key steps in creating the simulation model and presents the simulation results.
Keywords
Simulation, Flexsim, Optimization, Production Management
Published online 9/1/2023, 10 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: KRYNKE Marek, The Use of Computer Simulation in the Management of Subcontractors and Outsourced Services, Materials Research Proceedings, Vol. 34, pp 334-343, 2023
DOI: https://doi.org/10.21741/9781644902691-39
The article was published as article 39 of the book Quality Production Improvement and System Safety
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
References
[1] D. Klimecka-Tatar et al. Sustainable Developement in Logistic – A Strategy for Management in Terms of Green Transport. Manag. Sys. Prod. Eng. 29 (2021) 91-96. https://doi.org/10.2478/mspe-2021-0012
[2] J. Karcz, B. Ślusarczyk. Criteria of quality requirements deciding on choice of the logistic operator from a perspective of his customer and the end recipient of goods, Prod. Eng. Arch. 27 (2021) 58-68. https://doi.org/10.30657/pea.2021.27.8
[3] M. Ingaldi et al. Analysis of problems during implementation of Lean Manufacturing elements, MATEC Web Conf. 183 (2018) art.01004. https://doi.org/10.1051/matecconf/201818301004
[4] R. Ulewicz, R. Kucęba. Identification of problems of implementation of Lean concept in the SME sector, Eng. Manag. Prod. Serv. 8 (2016) 19-25. https://doi.org/10.1515/emj-2016-0002
[5] D. Klimecka-Tatar. Context of production engineering in management model of Value Stream Flow according to manufacturing industry, Prod. Eng. Arch. 21 (2018) 32-35. https://doi.org/10.30657/pea.2018.21.07
[6] K. Knop. Indicating and analysis the interrelation between terms – visual: management, control, inspection and testing, Prod. Eng. Arch. 26 (2020) 110-120. https://doi.org/10.30657/pea.2020.26.22
[7] E. Staniszewska et al. Eco-design processes in the automotive industry, Prod. Eng. Arch. 26 (2020) 131-137. https://doi.org/10.30657/pea.2020.26.25
[8] R. Ulewicz et al. Implementation of Logic Flow in Planning and Production Control, Manag. Prod. Eng. Rev. 7 (2016) 89-94. https://doi.org/10.1515/mper-2016-0010
[9] M. Mazur, H. Momeni. LEAN Production issues in the organization of the company – results, Prod. Eng. Arch. 22(2019) 50-53. https://doi.org/10.30657/pea.2019.22.10
[10] M. Niciejewska et al. Impact of Technical, Organizational and Human Factors on Accident Rate of Small-Sized Enterprises, Manag. Sys. Prod. Eng. 29 (2021) 139-144. https://doi.org/10.2478/mspe-2021-0018
[11] M. Krynke et al. Cost Optimization and Risk Minimization During Teamwork Organization, Manag. Sys. Prod. Eng. 29 (2021) 145-150. https://doi.org/10.2478/mspe-2021-0019
[12] K. Knop. Evaluation of quality of services provided by transport & logistics operator from pharmaceutical industry for improvement purposes, Trans. Res. Procedia 40 (2019) 1080-1087. https://doi.org/10.1016/j.trpro.2019.07.151
[13] M. Ingaldi. A new approach to quality management: conceptual matrix of service attributes, Pol. J. Manag. Stud. 22 (2020) 187-200. https://doi.org/10.17512/pjms.2020.22.2.13
[14] N. Baryshnikova et al. Management approach on food export expansion in the conditions of limited internal demand, Pol. J. Manag. Stud. 21, 2 (2020) 101-114. https://doi.org/10.17512/pjms.2020.21.2.08
[15] K. Knop. Importance of visual management in metal and automotive branch and its influence in building a competitive advantage, Pol. J. Manag. Stud. 22 (2020) 263-278. https://doi.org/10.17512/pjms.2020.22.1.17
[16] R. Ulewicz, M. Blaskova, Sustainable development and knowledge management from the stakeholders’ point of view, Pol. J. Manag. Stud. 18 (2018) 363-374. https://doi.org/10.17512/pjms.2018.18.2.29
[17] D. Klimecka-Tatar, M. Ingaldi. Assessment of the Technological Position of a Selected Enterprise in the Metallurgical Industry, Mater. Res. Proc. 17 (2020) 72-78. https://doi.org/10.21741/9781644901038-11
[18] R. Ulewicz. Practical Application of Quality Tools in the Cast Iron Foundry, Manuf. Technol. 14 (2014) 104-111. https://doi.org/10.21062/ujep/x.2014/a/1213-2489/MT/14/1/104
[19] J.M. Garrido. Introduction to Flexsim. In: Object Oriented Simulation: A Modeling and Programming Perspective, J.M. Garrido (Ed.), 31-42, Springer US, 2009. https://doi.org/10.1007/978-1-4419-0516-1
[20] J. Kyncl. Digital Factory Simulation Tools, Manuf. Technol. 16 (2016) 371-375. https://doi.org/10.21062/ujep/x.2016/a/1213-2489/MT/16/2/371
[21] E. Sujová et al. Simulation Models of Production Plants as a Tool for Implementation of the Digital Twin Concept into Production, Manuf. Technol. 20 (2020) 527-533. https://doi.org/10.21062/mft.2020.064
[22] C. Zhuang et al. Digital twin-based smart production management and control framework for the complex product assembly shop-floor, J. Adv. Manuf. Technol. 96 (2018) 1149-1163. https://doi.org/10.1007/s00170-018-1617-6
[23] M. Krynke. Risk Management in the Process of Personnel Allocation to Jobs, System Safety: Human – Technical Facility – Environment 2 (2020) 82-90. https://doi.org/10.2478/czoto-2020-0011
[24] M. Krynke, K. Mielczarek. Applications of linear programming to optimize the cost-benefit criterion in production processes, MATEC Web Conf. 183 (2018) art.04004. https://doi.org/10.1051/matecconf/201818304004
[25] I. Kaczmar. The use of simulation and optimization in managing the manufacturing process – case study, Gospodarka Materiałowa i Logistyka 2016 (4) (2016) 21-28.
[26] [26] S. Borkowski et al. The use of 3×3 matrix to evaluation of ribbed wire manufacturing technology, METAL 2012 – 21st Int. Conf. Metall. Mater. (2012), Ostrava, Tanger 1722-1728.
[27] K. Czerwinska et al. Improving quality control of siluminial castings used in the automotive industry, METAL 2020 – 29th Int. Conf. Metall. Mater. (2020) 1382-1387. https://doi.org/10.37904/metal.2020.3661
[28] A. Pacana et al. Analysis of quality control efficiency in the automotive industry, Transp. Res. Procedia 55 (2021) 691-698. https://doi.org/10.1016/j.trpro.2021.07.037
[29] M. Zenkiewicz et al. Electrostatic separation of binary mixtures of some biodegradable polymers and poly(vinyl chloride) or poly(ethylene terephthalate), Polimery/Polymers 61 (2016) 835-843. https://doi.org/10.14314/polimery.2016.835
[30] D. Siwiec et al. Improving the process of achieving required microstructure and mechanical properties of 38mnvs6 steel, METAL 2020 29th Int. Conf. Metall. Mater. (2020) 591-596. https://doi.org/10.37904/metal.2020.3525
[31] P. Jonšta et al. The effect of rare earth metals alloying on the internal quality of industrially produced heavy steel forgings, Materials 14 (2021) art.5160. https://doi.org/10.3390/ma14185160
[32] T. Lipinski et al. Influence of oxygen content in medium carbon steel on bending fatigue strength, Eng. Rural Develop. 21 (2022) 351-356. https://doi.org/10.22616/ERDev.2022.21.TF116
[33] N. Radek et al. The influence of plasma cutting parameters on the geometric structure of cut surfaces, Mater. Res. Proc. 17 (2020) 132-137. https://doi.org/10.21741/9781644901038-20
[34] N. Radek et al. Microstructure and tribological properties of DLC coatings, Mater. Res. Proc. 17 (2020) 171-176. https://doi.org/10.21741/9781644901038-26
[35] N. Radek et al. Influence of laser texturing on tribological properties of DLC coatings, Prod. Eng. Arch. 27 (2021) 119-123. https://doi.org/10.30657/pea.2021.27.15
[36] N. Radek et al. Operational properties of DLC coatings and their potential application, METAL 2022 – 31st Int. Conf. Metall. Mater. (2022) 531-536. https://doi.org/10.37904/metal.2022.4491
[37] G. Barucca et al. The potential of Λ and Ξ- studies with PANDA at FAIR, Europ. Phys. J. A 57 (2021) art.154 https://doi.org/10.1140/epja/s10050-021-00386-y
[38] M. Domagala et al. The Influence of Oil Contamination on Flow Control Valve Operation, Mater. Res. Proc. 24 (2022) 1-8. https://doi.org/10.21741/9781644902059-1
[39] N. Radek et al. The impact of laser welding parameters on the mechanical properties of the weld, AIP Conf. Proc. 2017 (2018) art.20025. https://doi.org/10.1063/1.5056288
[40] N. Radek et al. Properties of Steel Welded with CO2 Laser, Lecture Notes in Mechanical Engineering (2020) 571-580. https://doi.org/10.1007/978-3-030-33146-7_65
[41] R. Ulewicz, M. Mazur. Economic aspects of robotization of production processes by example of a car semi-trailers manufacturer, Manufacturing Technology 19 (2019) 1054-1059. https://doi.org/10.21062/ujep/408.2019/a/1213-2489/MT/19/6/1054
[42] N. Radek, R. Dwornicka. Fire properties of intumescent coating systems for the rolling stock, Commun. – Sci. Lett. Univ. Zilina 22 (2020) 90-96. https://doi.org/10.26552/com.C.2020.4.90-96
[43] S. Marković et al. Exploitation characteristics of teeth flanks of gears regenerated by three hard-facing procedures, Materials 14 (20210 art. 4203. https://doi.org/10.3390/ma14154203
[44] J. Pietraszek, E. Skrzypczak-Pietraszek. The uncertainty and robustness of the principal component analysis as a tool for the dimensionality reduction. Solid State Phenom. 235 (2015) 1-8. https://doi.org/10.4028/www.scientific.net/SSP.235.1
[45] R. Dwornicka, J. Pietraszek. The outline of the expert system for the design of experiment, Prod. Eng. Arch. 20 (2018) 43-48. https://doi.org/10.30657/pea.2018.20.09
[46] J. Pietraszek et al. Challenges for the DOE methodology related to the introduction of Industry 4.0. Prod. Eng. Arch. 26 (2020) 190-194. https://doi.org/10.30657/pea.2020.26.33
[47] B. Jasiewicz et al. Inter-observer and intra-observer reliability in the radiographic measurements of paediatric forefoot alignment, Foot Ankle Surg. 27 (2021) 371-376. https://doi.org/10.1016/j.fas.2020.04.015
[48] J. Pietraszek. The modified sequential-binary approach for fuzzy operations on correlated assessments, LNAI 7894 (2013) 353-364. https://doi.org/10.1007/978-3-642-38658-9_32
[49] J. Pietraszek et al. Non-parametric assessment of the uncertainty in the analysis of the airfoil blade traces, METAL 2017 – 26th Int. Conf. Metall. Mater. (2017) 1412-1418. ISBN 978-8087294796
[50] J. Pietraszek et al. The non-parametric approach to the quantification of the uncertainty in the design of experiments modelling, UNCECOMP 2017 Proc. 2nd Int. Conf. Uncert. Quant. Comput. Sci. Eng. (2017) 598-604. https://doi.org/10.7712/120217.5395.17225
[51] M. Matuszny. Building decision trees based on production knowledge as support in decision-making process, Prod. Eng. Arch. 26 (2020) 36-40. https://doi.org/10.30657/pea.2020.26.08
[52] M. Beaverstock et al. Applied Simulation: Modeling and Analysis Using FlexSim. BookBaby, Pennsauken Township, 2018. ISBN 978 0983231974
[53] M. Drbúl et al. Simulation Possibilities of 3D Measuring in Progressive Control of Production, Manufacturing Technology 16 (2016) 53-58. https://doi.org/10.21062/ujep/x.2016/a/1213-2489/MT/16/1/53
[54] I. Kaczmar. Komputerowe modelowanie i symulacje procesów logistycznych w środowisku Flexsim. PWN, Warszawa, 2019. ISBN 978-8301205447
[55] S. Setamanit. Evaluation of outsourcing transportation contract using simulation and design of experiment, Pol. J. Manag. Stud. 18 (2018) 300-310. https://doi.org/10.17512/pjms.2018.18.2.24
[56] M. Krynke et al. Analysis of the Problem of Staff Allocation to Work Stations, QPI 2021 Qual. Prod. Improv. (2019) 545-550. https://doi.org/10.2478/cqpi-2019-0073
[57] T.D.C. Le et al. Optimal vehicle route schedules in picking up and delivering cargo containers considering time windows in logistics distribution networks: A case study, Prod. Eng. Arch. 26 (2020) 174-184. https://doi.org/10.30657/pea.2020.26.31
[58] J. Kyncl et al. Tricanter Production Process Optimization by Digital Factory Simulation Tools, Manuf. Technol. 17 (2017) 49-53. https://doi.org/10.21062/ujep/x.2017/a/1213-2489/MT/17/1/49
[59] FlexSim: User manual (2017).
