PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

The use of a supply chain configuration model to assess the reliability of Logistics processes

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Zastosowanie modelu konfiguracji łańcucha dostaw do oceny niezawodności Realizacji procesów logistycznych
Języki publikacji
EN PL
Abstrakty
EN
The article presents an approach to assessing the reliability of logistics processes implemented in supply chains in terms of time losses resulting from the selection of a variant of material flows in the supply chain. In order to define this indicator, a mathematical model of the supply chain has been developed, i.e. the parameters of the research problem, the decision variables, the constraints and the evaluation criteria. The method of evaluating the reliability of the system is presented in diagram form. The algorithm was verified based on experimental data. In order to evaluate the reliability of the logistic processes for the sample supply chain, a simulation model was developed that determines the time losses in the points and linear elements of the examined chain. Time losses are dictated by traffic delays resulting from traffic congestion on particular sections of the route and road junctions and delays in point elements in the supply chain.
PL
W artykule przedstawiono podejście do oceny niezawodności procesów logistycznych realizowanych w łańcuchach dostaw w aspekcie strat czasu wynikających z wyboru wariantu realizacji przepływów materiałowych w łańcuchu dostaw. Na potrzeby tych badań opracowano model matematyczny łańcucha dostaw, tj. określono parametry problemu badawczego, zmienne decyzyjne, ograniczenia oraz kryteria oceny. Sposób oceny niezawodności systemu został przedstawiony w postaci schematu. Algorytm został zweryfikowany na podstawie danych eksperymentalnych. W celu oceny niezawodności procesów logistycznych dla przykładowego łańcucha dostaw opracowano model symulacyjny wyznaczający straty czasu w elementach punktowych i liniowych badanego łańcucha. Straty czasu podyktowane są opóźnieniami w ruchu drogowym wynikającymi z kongestii ruchu na poszczególnych odcinkach trasy i węzłach drogowych oraz opóźnieniami w elementach punktowych łańcucha dostaw.
Rocznik
Strony
367--374
Opis fizyczny
Bibliogr. 46 poz., rys., tab.
Twórcy
  • Faculty of Transport Warsaw University of Technology ul. Koszykowa 75, 00-662 Warsaw, Poland
  • Faculty of Production Engineering Warsaw University of Technology ul. Narbutta 86, 02-524 Warsaw, Polan
  • i.jacyna-golda@wip.pw.edu.pl
  • Faculty of Transport Silesian University of Technology ul. Krasińskiego 8, 40-019 Katowice, Poland
  • Faculty of Transport Warsaw University of Technology ul. Koszykowa, 00-662 Warsaw, Poland
  • Faculty of Transport Warsaw University of Technology ul. Koszykowa, 00-662 Warsaw, Poland
  • Faculty of Transport Warsaw University of Technology ul. Koszykowa, 00-662 Warsaw, Poland
Bibliografia
  • 1. Ambroziak T, Jachimowski R, Pyza D, Szczepański E. Analysis of the traffic stream distribution in terms of identification of areas with the highest exhaust pollution. Archives of Transport 2015: 32(4): 7–16, https://doi.org/10.5604/08669546.1146993.
  • 2. Ambroziak T, Jacyna M. Queueing theory approach to transport process dynamics Part 1. Dynamics of transport network connections. Archives of Transport 2002; 14(4): 5–20.
  • 3. Ambroziak T, Jacyna M. Queueing theory approach to transport process dynamics part 2. Parameters of the transport process dynamics.Archives of Transport 2003; 15(1): 5–21.
  • 4. Ambroziak T, Jacyna M, Wasiak M. The Logistic Services in a hierarchical distribution System. Goulias K G (ed.) Transport Science and Technology 2006: 383–394, https://doi.org/10.1108/9780080467542-030.
  • 5. Barnes E, Dai J, Deng S, Down D, Goh M, Lau H C, Sharafali M. On the Strategy of Shupply Hubs for Cost Reduction and Responsiveness. White Paper. Singapore: The Logistics Institute – Asia Pacific, National University of Singapore, 2003.
  • 6. Bertsimas D, Simchi-Levi D. A new generation of vehicle routing research: Robust algorithm, addressing uncertainty. Operations Research 1996; 44: 286–304, https://doi.org/10.1287/opre.44.2.286.
  • 7. Bramel J, Simchi-Levi D. The Logic of Logistics: Theory, Algorithms and Applications for Logistics Management. New York: Springer-Verlag, 1997, https://doi.org/10.1007/978-1-4684-9309-2.
  • 8. Chen A, Yang H, Lo H, Tang W H. A Capacity Related Reliability for Transportation Networks. Journal of Advanced Transportation 1999; 33(2): 183–200, https://doi.org/10.1002/atr.5670330207.
  • 9. Chopra S, Sodhi M S. Reducing the Risk of Supply Chain Disruptions. MIT Sloan Management Review 2014; 55(3): 73.
  • 10. Daganzo C F. Logistics Systems Analysis., New York: Springer Verlag, 1996, https://doi.org/10.1007/978-3-662-03196-4.
  • 11. Dandamudi S, Lu J-C. Competition Driving Logistics Design with Continuous Approximation Methods. Technical Report of the School of Industrial and Systems Engineering. Georgia Tech, 2004.
  • 12. Dugan J B, Bavuso B, Boyd M. Dynamic fault tree models for fault tolerant computer systems. IEEE Trans. Reliability 1992; 41: 363–377, https://doi.org/10.1109/24.159800.
  • 13. Dugan J B, Bavuso B, Boyd M. Fault trees and Markov models for reliability analysis of fault tolerant systems. Reliability Engineering and System Safety 1993; 39: 291–307, https://doi.org/10.1016/0951-8320(93)90005-J.
  • 14. Dukic G, Opetuk T. Warehouse layouts. Manzini R (ed.). Warehousing in the Global Supply Chain. Advanced Models, Tools and Applications for Storage Systems London: Springer, 2012, https://doi.org/10.1007/978-1-4471-2274-6_3.
  • 15. Ecker J G, Kupferschmid M. Introduction to Operations Research, Florida: Krieger Publishing Company, 1988.
  • 16. Fault Tree Analysis, International Technical Commission, IEC Standard, Publication 1025, 1990.
  • 17. Fechner I (red.). Zarządzanie łańcuchem dostaw. Poznań: Wyższa Szkoła Logistyki, 2007.
  • 18. Haj Shirmohammadi A. Programming maintenance and repair (Technical management in industry), 8th edn. Esfahan: Ghazal Publishers, 2002.
  • 19. Izdebski M. The use of heuristic algorithms to optimize the transport issues on the example of municipal services companies. Archives of Transport 2014; 29(1): 27-36, https://doi.org/10.5604/08669546.1146961.
  • 20. Izdebski M, Jacyna M. Wybrane aspekty zastosowania algorytmu genetycznego do rozwiązywania problemu przydziały zasobów do zadań w przedsiębiorstwie transportowym. Prace Naukowe Politechniki Warszawskiej 2013; 97: 183–194.
  • 21. Jacyna Marianna, Izdebski Mariusz, Szczepański Emilian [i in.] : The task assignment of vehicles for a production company. Symmetry-Basel 2018; 11(10): 1-19.
  • 22. Jacyna M, Wasiak M, Lewczuk K, Kłodawski M. Simulation model of transport system of Poland as a tool for developing sustainable transport. Archives of Transport 2015; 31(3): 23–35, https://doi.org/10.5604/08669546.1146982.
  • 23. Jacyna-Gołda I. Evaluation of operational reliability of the supply chain in terms of the control and management of logistics processes. Nowakowski T et. all (ed.) Safety and Reliability: Methodology and Applications. CRC Press Taylor & Francis Group, 2015, 549-558.
  • 24. Jacyna-Gołda I. Decision-making model for supporting supply chain efficiency evaluation. Archives of Transport 2015; 33(1): 17–31, https://doi.org/10.5604/08669546.1160923.
  • 25. Jacyna-Gołda I, Izdebski M, Podviezko A. Assessment of the efficiency of assignment of vehicles to tasks in supply chains: A case-study of a municipul company. Transport 2016; 31(4): 1–9.
  • 26. Lee H L. The triple-A supply chain. Harvard Business Review 2004; 82(10): 102.
  • 27. Magott J, Nowakowski T, Skrobanek P, Werbińska S. Analysis of possibilities of timing dependencies modelling – example of logistic support system. European Safety and Reliability Association Conference, ESREL, 2008. Valencia, Spain, Leiden: Taylor and Francis, 2008, 1055-10.
  • 28. Mazuruk M, Rzepka M. Przegląd łańcucha dostaw według SCOR. Jak skutecznie kontrolować przepływ materiałów? EuroLogistics 2006; 3.
  • 29. Nowakowski T. Models of uncertainty of operation and maintenance information. Zagadnienia Eksploatacji Maszyn 2000; 35(2), 143–150.
  • 30. Nowakowski T. Reliability model of combined transportation system. [in:] Spitzer C, Schmocker U, Dang V N (ed.). Probabilistic Safety Assessment and Management. London: Springer, 2004, https://doi.org/10.1007/978-0-85729-410-4_323.
  • 31. Powell W. A comparative review of alternative algorithms for the dynamic vehicle allocation problem. [in.] Golen B, Assad A (ed.). Vehicle Routing: Methods and Studies. Amsterdam, Netherlands: Elsevier Science Publishers, 1988.
  • 32. Powell W, Jaollet P, Odoni A, Stochastic and dynamic networks and routing. [in.] Ball M, Magnanti T, Monma C, Nemhauser G (ed.). Network Routing; 8. Handbooks in Operations Research and Management Science. North-Holland, Amsterdam, Netherlands: 1995.
  • 33. Psaraftis H. Dynamic vehicle routing: Status and prospects. Annals of Operational Research 1995; 61(1): 143–164, https://doi.org/10.1007/BF02098286.
  • 34. Rodrigues V S, Stantchev D, Potter A, Naim M, Whiteing A. Establishing a transport operation focused uncertainty model for the supply chain. International Journal of Physical Distribution & Logistics Management 2008; 38(5-6): 388–411, https://doi.org/10.1108/09600030810882807.
  • 35. Sadgrove K. The Complete Guide to Business: Risk Management, 2nd ed. Aldershot: Gower Publishing Limited, 2005.
  • 36. Sawicki P, Kiciński M, Fierek S. Selection of the most adequate trip-modelling tool for integrated transport planning system. Archives of Transport 2016; 37(1): 55–66, https://doi.org/10.5604/08669546.1203203.
  • 37. Sohn S Y, Choi I S. Fuzzy QFD for supply chain management with reliability consideration. Reliability Engineering & System Safety 2001; 72(3): 327–334, https://doi.org/10.1016/S0951-8320(01)00022-9.
  • 38. Spitter J M, Hurkens C A J, de Kok A G, Lenstra J K, Negenman E G. Linear programming models with planned lead times for Supply Chain Operations Planning. European Journal of Operational Research 2005; 163(3): 706–720, https://doi.org/10.1016/j.ejor.2004.01.019.
  • 39. Stephens S. Supply Chain Council & Supply Chain Operations Reference (SCOR). Model Overview. Supply Chain Management an International Journal 2001.
  • 40. Szczepański E, Jacyna-Gołda I, Murawski J. Genetic algorithms based approach for transhipment HUB location in urban areas. Archives of Transport 2014; 31(3): 73–78, https://doi.org/10.5604/08669546.1146989.
  • 41. Twaróg J. Mierniki i wskaźniki logistyczne. Poznań: Biblioteka Logistyka, 2005.
  • 42. Wasiak M. A queuing theory approach to logistics systems modelling. Archives of Transport 2007; 19(1-2): 103–120.
  • 43. Yu M, De Koster R. The impact of order batching and picking area zoning on order picking system performance. European Journal of Operational Research 2009, https://doi.org/10.1016/j.ejor.2008.09.011.
  • 44. Zhang Q S, Wang H Y, Liu H. 4-stage distribution network optimization of supply chain with grey demands. Kybernetes 2012; 41(5-6):633–642, https://doi.org/10.1108/03684921211243293.
  • 45. Żak J, Jacyna-Gołda I. Using queue theory to analysis and evaluation of the logistics centre workload. Archives of Transport 2013; 25(1-2): 117–135.
  • 46. Żochowska R. Selected issues in modelling of traffic flows in congested urban networks. Archives of Transport 2015; 29(1): 77–89, https://doi.org/10.5604/08669546.1146971.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7dac35a3-5efe-438b-bd3f-381fd124abea
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.