Modeling of production process by the method of works maximum approximation
DOI:
https://doi.org/10.26906/znp.2020.54.2279Keywords:
mathematical modeling of production, method of works maximum approximation, calculation schemes, calculation of time parameters of production processes execution, calendar scheduleAbstract
The work is devoted to mathematical modeling of production processes. Existing methods of production processes modeling are analyzed. Calculated workflow schemes are proposed when planning the manufacturing process by maximizing work approximation. The dependences of the time parameters calculation and the conditions of the proposed calculation schemes application are given. The method of the time parameters calculation of production processes execution by the method of works maximum approximation is offered. The procedure of calculation and construction of production processes calendar schedule is given. The advantages of the proposed methodology in comparison with existing modeling methods are analyzed
References
. Azab A. & Naderi B. (2015) Modelling the Problem of Production Scheduling for Reconfigurable Manufacturing Systems. Procedia CIRP, 33 (2015), 76-80 DOI: https://doi.org/10.1016/j.procir.2015.06.015
doi.org/10.1016/j.procir.2015.06.015 DOI: https://doi.org/10.1088/1475-7516/2015/06/015
. Bikas H., Stavropoulos P. & Chryssolouris G. (2016) Additive manufacturing methods and modeling approaches. International Journal of Advanced Manufacturing Technology, 83(1-4), 389-405
doi.org/10.1007/s00170-015-7576-2 DOI: https://doi.org/10.1007/s00170-015-7576-2
. Boualem M., Cherfaoui M., Bouchentouf A. & Aïssani, D. (2015). Modeling, simulation and performance analysis of a flexible production system. European Journal of Pure and Applied Mathematics, 8, 26-49
. Yudin A. (2002). Planning and management of production processes using mathematical modeling methods. Poltava, PoltNTU
. Faizrahnemoon M. (2012). Mathematical modelling of the scheduling of a production line at SKF (Thesis for the Degree of Master of Science). Gothenburg: Chalmers University of Technology and University of Gothenburg
. Dikman, L. (2006) Organization of construction productio. Moscow, Publishing House Association of Construction Universities
. Ilin I., Kalinina O., Levina A., Iliashenko O. (2016). Approach to Organizational Structure Modelling in Construction Companies MATEC Web of Conferences. 86:05028 DOI: https://doi.org/10.1051/matecconf/20168605028
doi.org/10.1051/matecconf/ 20168605028
. Meng X. (2010) Modeling of reconfigurable manufacturing systems based on colored timed object-oriented Petri nets Journal of Manufacturing Systems, 29, 81-90 DOI: https://doi.org/10.1016/j.jmsy.2010.11.002
doi.org/10.1016/j.jmsy.2010.11.002 DOI: https://doi.org/10.1088/1475-7516/2010/11/002
. OzgUven C., Ozbakir L. & Yavuz Y. (2010). Mathematical models for job-shop scheduling problems with routing and process plan flexibility. Applied Mathematical Modelling, 34, 1539-1548 DOI: https://doi.org/10.1016/j.apm.2009.09.002
https://doi.org/ 10.1016/j.apm.2009.09.002 DOI: https://doi.org/10.1055/s-0029-1217688
. Roslof J., Westerlund T. & Isaksson J. (2002). Solving a large-scale industrial scheduling problem using MILP combined with a heuristic procedure. European Journal of Operational Research, 138, 29-42.
doi.org/10.1016/S0377-2217(01)00140-0 DOI: https://doi.org/10.1016/S0377-2217(01)00140-0
. Müller S. & Westkämper E. (2018). Modelling of Production Processes: A Theoretical Approach to Additive Manufacturing. Procedia CIRP, 72, 1524-1529 DOI: https://doi.org/10.1016/j.procir.2018.03.010
doi.org/10.1016/j.procir.2018.03.010 DOI: https://doi.org/10.1088/1475-7516/2018/10/010
. Tseng F. & Gupta J. (2005) Comparative evaluation of MILP flowshop models. The Journal of the Operational Research Society, 56. 88-101
doi.org/10.1057/palgrave.jors.2601805 DOI: https://doi.org/10.1057/palgrave.jors.2601805
] DBN A.3.1-5-2016 (2016). Organization of construction production. Kyiv: Minrehbud Ukrainy
