PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2021 | 12 | nr 2 | 17--26
Tytuł artykułu

Design of Supply Chain Network to Reduce Impacts of Damages during Shipping

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Recently, the expand of industrial market has led to have long supply chain network. During the long shipment, the probability of having damaged products is likely to occur. The probability of having damaged products is different between stages and that could lead to higher percentage of damaged products when arrived at retailers. Many companies have rejected the entire shipment because the damaged product percentage was higher than that agreed on. Decision-makers have tried to reduce the percentage of damaged products that happened because the transit, loading unloading the shipment, and natural disasters. Companies started to implement recovery centers in the supply chain network in order to return their system steady statues. Recovery models have been developed in this paper to reduce the damaged percentage at minimum costs to do so. Results show that the possibility of implementing an inspection unit and a recovery centers in the system before sending the entire shipment to the retailer based on examining a sample size that has been selected randomly from the shipment and the minimum cost of committing type I and type II errors. Designing a methodology to minimize the total cost associated with the supply chain system when there is a possibility of damage occurring during shipping is the objective of this research. (original abstract)
Słowa kluczowe
Rocznik
Tom
12
Numer
Strony
17--26
Opis fizyczny
Twórcy
  • Jazan University, Kingdom of Saudi Arabia
  • Wichita State University, United States of America
  • University of Sussex, United Kingdom
  • Wichita State University, United States of America
  • Jazan University, Kingdom of Saudi Arabia
Bibliografia
  • Alsobhi, S.A., Krishnan, K.K., Dhuttargaon, M., and Gupta, D. (2017). Design of Supply Chain Damage Recovery Systems. Journal of Supply Chain and Operations Management, 15, 1, 79-100.
  • Altner, D.S., Ergun, Ö., and Uhan, N.A. (2010). The maximum flow network interdiction problem: Valid inequalities, integrality gaps, and approximability. Operations Research Letters, 38, 1, 33-38, doi: 10.1016/j.orl.2009.09.013.
  • Aryanezhad, M.B., Naini, S.G.J., and Jabbarzadeh, A. (2012). An integrated model for designing supply chain network under demand and supply uncertainty, African Journal of Business Mmanagement, 6, 7, 2678.
  • Azad, N., and Davoudpour, H. (2010). A two-echelon location-routing model with considering value-at-risk measure. International Journal of Management Science and Engineering Management, 5, 3, 235-240.
  • Berman, O., Krass, D., and Menezes, M.B.C. (2007). Operations research: INFORMS. Operations Research, doi: 10.1287/opre.1060.0348.
  • Christopher, M., and Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15, 2, 1-14, doi: 10.1108/09574090410700275.
  • Church, R.L. and Scaparra, M.P. (2007). Protecting critical assets: The r-interdiction median problem with Fortification. Geographical Analysis, 39, 2, 129-146, doi: 10.1111/j.1538-4632.2007.00698.x.
  • Church, R.L., Scaparra, M.P., and Middleton, R.S. (2004). Identifying critical infrastructure: The median and covering facility interdiction problems. Annals of the Association of American Geographers, 94, 3, 491-502, doi: 10.1111/j.1467-8306.2004.00410.x.
  • Colbourn, C. (1987). The combinatorics of network reliability. New York: Oxford University Press.
  • Craighead, C.W., Blackhurst, J., Rungtusanatham, M.J., and Handfield, R.B. (2007). The severity of supply chain disruptions: Design characteristics and mitigation capabilities. Decision Sciences, 38, 1, 131-156. doi: 10.1111/j.1540-5915.2007.00151.x.
  • Cui, T., Ouyang, Y., and Shen, Z.-J.M. (2010). Reliable facility location design under the risk of disruptions. Operations Research, 58 (4-part-1), 998-1011. doi: 10.1287/opre.1090.0801.
  • Daehy, Y., Krishnan, K., Alsaadi, A., and Alghamdi, S. (2019). Effective cost minimization strategy and an optimization model of a reliable global supply chain system. Uncertain Supply Chain Management, 7, 3, 381-398.
  • Darwish, M.A., Odah, O.M., and Goyal, S.K. (2014). Vendor managed inventory models for single-vendor multi-retailer supply chains with quality consideration. International Journal of Industrial and Systems Engineering, 18, 4, 499-528.
  • Ellis, S.C., Henry, R.M., and Shockley, J. (2010). Buyer perceptions of supply disruption risk: A behavioral view and empirical assessment. Journal of Operations Management, 28, 1, 34-46, doi: 10.1016/j.jom.2009.07.002.
  • Guide, V.D.R., Jayaraman, V., Srivastava, R., and Benton, W.C. (2000). Supply-chain management for recoverable manufacturing systems. Interfaces, 30, 3, 125-142, doi: 10.1287/inte.30.3.125.11656.
  • Jüttner, U., Peck, H., and Christopher, M. (2003). Supply chain risk management: outlining an agenda for future research. International Journal Of Logistics: Research and Applications, 6, 4, 197.
  • Kovács, G. and Tatham, P. (2009). Responding to disruptions in the supply network-from dormant to action. Journal of Business Logistics, 30, 2, 215-229, doi: 10.1002/j.2158-1592.2009.tb00121.x.
  • Liberatore, F., Scaparra, M.P., and Daskin, M.S. (2012). Hedging against disruptions with ripple effects in location analysis. Omega, 40, 1, 21-30.
  • Melnyk, S.A., Narasimhan, R., and DeCampos, H.A. (2013). Supply chain design: Issues, challenges, frameworks and solutions. International Journal of Production Research, 52, 7, 1887-1896, doi: 10.1080/00207543.2013.787175.
  • Melnyk, S.A., Lummus, R.R., Vokurka, R.J., Burns, L.J., and Sandor, J. (2009). Mapping the future of supply chain management: A Delphi study. International Journal of Production Research, 47, 16, 4629-4653, doi: 10.1080/00207540802014700.
  • Nganje, W.E. and Skilton, P. (2011). Food risks and type I & II errors. International Food and Agribusiness Management Review, 14, 5, 109-124, https://wwwifama.org.proxy.wichita.edu/publications/journal/IFAMRArchive.aspx.
  • Qi, L., Shen, Z.-J., and Snyder, L.V. (2010). The effect of supply disruptions on supply chain design decisions. Transportation Science, 44, 2, 274-289, doi: 10.1287/trsc.1100.0320.
  • Shear, H., Speh, T., and Stock, J. (2002). Many happy (product) returns. Harvard Business Review, 80, 7, 16-17.
  • Shier, D.R. (1991). Network reliability and algebraic structures. Clarendon Press.
  • Shooman, M.L. (2002). Reliability of computer systems and networks: fault tolerance, analysis, and design. John Wiley & Sons.
  • Singh, S. and Xu, M. (1993). Bruising in apples as a function of truck vibration and packaging. Applied Engineering in Agriculture, 9, 5, 455-460.
  • Snyder, L.V. and Daskin, M.S. (2005). Reliability models for facility location: the expected failure cost case. Transportation Science, 39, 3, 400-416.
  • Snyder, L.V., and Daskin, M.S. (2006). Stochastic probust location problems. Iie Transactions, 38, 11, 971-985.
  • Tang, C.S. (2006). Perspectives in supply chain risk management. International Journal of Production Economics, 103, 2, 451-488.
  • Thierry, M., Salomon, M., Van Nunen, J., and Van Wassenhove, L. (1995). Strategie issues in product recovery management. California Management Review, 37, 2, 114-135.
  • Toledo, T., Koutsopoulos, H.N., Davol, A., Ben-Akiva, M.E., Burghout, W., Andréasson, I., ... and Lundin, C. (2003). Calibration and validation of microscopic traffic simulation tools: Stockholm case study. Transportation Research Record, 1831, 1, 65-75.
  • Wagner, S.M. and Neshat, N. (2010). Assessing the vulnerability of supply chains using graph theory. International Journal of Production Economics, 126, 1, 121-129, doi: 10.1016/j.ijpe.2009.10.007.
  • Zhao, K., Kumar, A., Harrison, T.P., and Yen, J. (2011). Analyzing the resilience of complex supply network Topologies against random and targeted disruptions. IEEE Systems Journal, 5, 1, 28-39, doi: 10.1109/jsyst.2010.2100192.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171623104

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.