Novel supply chain concepts and optimization of virtual enterprises to reduce cost, increase productivity and boost competitiveness

• Autorzy: Kovács G.

Identyfikatory

DOI

10.24425/bpas.2018.125945

• Języki publikacji: EN

Abstrakty

EN

Global competition and increasingly complex networks of supply chains require new production philosophies, novel supply chain paradigms (Lean, Agile and Hybrid ones) and new organization and cooperation forms of companies in order to reduce cost, increase productivity and boost competitiveness. Therefore, members of an Agile supply chain form a virtual enterprise (VE) network, which stands for temporary cooperation of VE members (final assemblers, suppliers, service providers) in which the members share their skills, human and equipment resources as well as waste for more efficient operation. The goal of this study is VE optimization, which means forming optimum combinations of potential chain members. This innovative and original approach involves developing an optimization method and defining objective functions (total cost, total lead time) and design constraints (production and service capacities, inventories and members flexibility) for optimum formation of VEs. The focus of VE optimization is to manufacture and deliver final products to customers in the most time- and cost-effective manner, with the total cost and total lead time of the supply chain being minimized during the optimization. Unique optimization software has been developed based on this method. It can can be widely used for optimizing micro- and macro regional virtual networks.

Słowa kluczowe

EN

virtual enterprise; optimization; cost; lead time; software development

PL

wirtualne przedsiębiorstwo; optymalizacja; koszt; czas realizacji; rozwój oprogramowania

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2018
• Tom: Vol. 66, nr 6
• Strony: 973--980
• Opis fizyczny: Bibliogr. 30 poz., rys., tab.

Twórcy

autor

Kovács G.

• University of Miskolc, Faculty of Mechanical Engineering and Informatics, Institute of Logistics, 3515 Miskolc-Egyetemváros, Hungary

Bibliografia

• [1] G. Kovács and S. Kot, “New logistics and production trends as the effect of global economy changes”, Pol. J. Manag. Stud. 14 (2), 121‒134 (2016).
• [2] R. McLachlin, “Management in initiatives and just-in-time manufacturing”, J. Oper. Manag. 15 (4), 271‒292 (1997).
• [3] Z. Bokor, 2005. “Evaluation of intermodal logistics services, development possibilities“, BME OMIKK Log. 10 (3), 22‒65 (2005), [in Hungarian].
• [4] G.C. Stevens, “Integrating the Supply Chain”, Int. J. Phys. Distrib. 19 (8), 3‒8 (1989).
• [5] M.A. Vonderembse, “Designing supply chains: Towards theory development”, Int. J. Prod. Econ. 100, 223‒238. (2006).
• [6] M. Mageira, “A multi-level method of support for management of product flow through supply chains”, Bull. Pol. Ac.: Tech. 63 (4), 933‒946. (2015).
• [7] X. Wang, H. Guo, R. Yan, and X. Wang, “Achieving optimal performance of supply chain under cost information asymmetry”, Appl. Math. Model. 53, 523‒539 (2018).
• [8] G.M. Kopanos, L. Puigjaner, and M. C. Georgiadis, “Simultaneous production and logistic operations planning in semicontinuous food industries”, Omega-Int. J. Manage. S. 40, 634‒650 (2012).
• [9] M. Amini and H. Li, ”Supply chain configuration for diffusion of new products: an integrated optimisation approach”, Omega-Int. J. Manage. S. 39, 313‒322 (2011).
• [10] A. Chatzikontidou, P. Longinidis, P. Tsiakis, and M.C. Georgiadis, “Flexible supply chain network design underuncertainty”, Chem. Eng. Res. Des. 128, 290‒305 (2017).
• [11] R. Jamshidi, S.M.T. Fatemi Ghomi, and B. Karimi. “Flexible supply chain optimization with controllable lead time and shipping option”, Appl. Soft. Comput. 30, 26‒35 (2015).
• [12] Y. Wang, Leadtime, inventory, and service level in assemble-to-order systems. In Supply Chain Structures: Coordination, Information and Optimization, Kluwer Academic Publishers, Norwell, 2001.
• [13] P. Schönsleben, “With agility and adequate partnership strategies towards effective logistics networks”, Comput. Ind. 42 (1), 33‒42 (2000).
• [14] J.B. Naylor, M.M. Naim, and D. Berry, “Leagility: Integrating the lean and agile manufacturing paradigms in the total supply chain”, Int. J. Prod. Econ. 62, 107‒118. (1999).
• [15] J.P. Womack and D.T. Jones, Lean Thinking: Banish waste and create wealth in your corporation, Simon & Schuster, New York, 1996.
• [16] J.K. Liker and T. Lamb, Lean Manufacturing Principles Guide DRAFT, University of Michigan, 2000.
• [17] A. Agarwal, R. Shankar, and M.K. Tiwari, “Modelling the metrics of lean, agile and leagile supply chain: An ANP-based approach”, Eur. J. Oper. Res. 173, 211‒225. (2006).
• [18] S. Wadhwa, M. Mishra and F.T.S. Chan, “Organizing a virtual manufacturing enterprise: an analytic network process based approach for enterprise flexibility”, Int. J. Prod. Res. 47 (1), 163‒186 (2008).
• [19] K. Yu, J. Cadeaux, and H. Song, “Flexibility and quality in logistics and relationships”, Ind. Market. Manag. 62, 211‒225 (2017).
• [20] Y.H. Tseng and C.T. Lin, “Enhancing enterprise agility by deploying agile drivers, capabilities and providers”, Inform. Sciences. 181, 3693‒3708 (2011).
• [21] C.A. Yauch, “Measuring agility as a performance outcome”, J. Manuf. Techn. Manag. 22, 384‒404 (2011).
• [22] H. Winkler and G. Seebacher, “A capability approach to evaluate supply chain flexibility”, Int. J. Prod. Econ. 167, 177‒186 (2015).
• [23] A.T.L. Chan, E.W.T. Ngai, and K.K.L. Moon, “The effects of strategic and manufacturing flexibilities and supply chain agility on firm performance in the fashion industry”, Eur. J. Oper. Res. 259 (4), 86‒99 (2017).
• [24] L.M. Camarinha-Matos, “Execution system for distributed business processes in a virtual enterprise”, Future. Gener. Comp. Sy. 17, 1009‒1021 (2001).
• [25] A. Gunasekaran, K. Lai, and T. C. Edwin Cheng, “Responsive supply chain: A competitive strategy in a networked economy”, Omega-Int. J. Manage. S. 36 (4), 549‒564 (2008).
• [26] M. Gubán, “Non-linear programming model and solution method of ordering controlled virtual assembly plants”, Conf. Proc.: Logistics – The Eurasian Bridge: Materials of V. International scientifically-practical conference, Krasnoyarsk, March 02‒03. 2011.
• [27] E. Esposito and P. Evangelista, “Investigating virtual enterprise models: literature review and empirical findings”, Int. J. Prod. Econ. 148, 145‒157 (2014).
• [28] S. Nikghadam, A.M. Ozbayoglu, H.O. Unver, and S.E. Kilic, “Design of a Customer’s Type Based Algorithm for Partner Selection Problem of Virtual Enterprise”, Procedia. Comp. Sci. 95, 467- 474 (2016).
• [29] P. Simon and L. Dudás. “Exploration of a new crossover operator for genetic algorithms for order planning problems”, Conf. Proc.: International Conference on Innovative Technologies, Budapest, September 10‒12. 2013.
• [30] G. Kovács, “Productivity improvement by lean manufacturing philosophy”, Adv. Log. Sys. 6 (1), 9‒16 (2012).

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).