Lead times - their behavior and the impact on planning and control in supply chains

• Autorzy: Nielsen P. , Michna Z. , Sørensen B. B. , Dung N. D. A.

Identyfikatory

DOI

10.1515/mper-2017-0015

• Języki publikacji: EN

Abstrakty

EN

Lead times and their nature have received limited interest in literature despite their large impact on the performance and the management of supply chains. This paper presents a method and a case implementation of the same, to establish the behavior of real lead times in supply chains. The paper explores the behavior of lead times and illustrates how in one particular case they can and should be considered to be independent and identically distributed (i.i.d.). The conclusion is also that the stochastic nature of the lead times contributes more to lead time demand variance than demand variance.

Słowa kluczowe

EN

supply chain management; stochastic lead time; simulation; inventory management

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2017
• Tom: Vol. 8, No. 2
• Strony: 30--40
• Opis fizyczny: Bibliogr. 29 poz., rys., tab., wykr.

Twórcy

autor

Nielsen P.

• Aalborg University, Department of Materials and Production, Aalborg 9220, Denmark

autor

Michna Z.

• Department of Mathematics and Cybernetics, Wroclaw University of Economics, Wroclaw, Poland

autor

Sørensen B. B.

• SCM Consultant, Copenhagen, Denmark

autor

Dung N. D. A.

• Department of Materials and Production, Aalborg University, Denmark

Bibliografia

• [1] Otto A., Kotzab H., Does supply chain management really pay? Six perspectives to measure the performance of managing a supply chain, European Journal of Operational Research, 144, 2, 306–320, 2003.
• [2] Singh R.K., Sharma M.K., Prioritising the alternatives for flexibility in supply chains, Production Planning & Control, 25, 2, 176–192, 2014.
• [3] Chen F., Drezner Z., Ryan J.K., Simchi-Levi D., Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information, Management Science, 46, 3, 436–443, 2000.
• [4] Mascle C., Gosse J., Inventory management maximization based on sales forecast: case study, Production Planning & Control, 25, 12, 1039–1057, 2014.
• [5] Silver E.A., Pyke D.F., Peterson R., Inventory management and production planning and scheduling, Wiley New York, Vol. 3, 1998.
• [6] Nielsen P., Michna Z., Do N.A.D., An empirical investigation of lead time distributions, IFIP International Conference on Advances in Production Management Systems, Springer 2014.
• [7] Chatfield D.C., Kim J.G., Harrison T.P., Hayya J.C., The bullwhip effect – impact of stochastic lead time, information quality, and information sharing: a simulation study, Production and Operations Management, 13, 4, 340–353, 2004.
• [8] Kim J.G., Chatfield D., Harrison T.P., Hayya J.C., Quantifying the bullwhip effect in a supply chain with stochastic lead time, European Journal of Operational Research, 173, 2, 617–636, 2006.
• [9] Bagchi U., Hayya J.C., Chu C.-H., The effect of lead-time variability: the case of independent demand, Journal of Operations Management, 6, 2, 159–177, 1986.
• [10] Chaharsooghi S.K., Heydari J., LT variance or LT mean reduction in supply chain management: which one has a higher impact on SC performance?, International Journal of Production Economics, 124, 2, 475–481, 2010.
• [11] Wikner J., Towill D.R., Naim M., Smoothing supply chain dynamics, International Journal of Production Economics, 22, 3, 231–248, 1991.
• [12] Metters R., Quantifying the bullwhip effect in supply chains, Journal of Operations Management, 15, 2, 89–100, 1997.
• [13] Lee H.L., Padmanabhan V., Whang S., The bullwhip effect in supply chains, MIT Sloan Management Review, 38, 3, 93, 1997.
• [14] Lee H.L., Padmanabhan V., Whang S., Information distortion in a supply chain: the bullwhip effect, Management Science, 43, 4, 546–558, 1997.
• [15] McCullen P., Towill D., Diagnosis and reduction of bullwhip in supply chains, Supply Chain Management: An International Journal, 7, 3, 164–179, 2002.
• [16] Michna Z., Nielsen I.E., Nielsen P., The bullwhip effect in supply chains with stochastic lead times, Mathematical Economics, 9, 16, 71–88, 2013.
• [17] Song J.-S., The effect of leadtime uncertainty in a simple stochastic inventory model, Management Science, 40, 5, 603–613, 1994.
• [18] Buchmeister B., Pavlinjek J., Palcic I., Polajnar A., Bullwhip effect problem in supply chains, Advances in Production Engineering & Management, 3, 1, 45– 55, 2008.
• [19] Ghaffari M., Javadian N., Analysis of the bullwhip effect with multi-echelon, multi-product supply chains, International Journal of Industrial Engineering Computations, 4, 4, 579–586, 2013.
• [20] Wang X., Disney S.M., Mitigating variance amplification under stochastic lead-time: the proportional control approach, European Journal of Operational Research, 256, 1, 151–162, 2017.
• [21] Disney S.M., Maltz A., Wang X., Warburton R.D.H., Inventory management for stochastic lead times with order crossovers, European Journal of Operational Research, 248, 2, 473–486, 2016.
• [22] Gross D., Soriano A., The effect of reducing leadtime on inventory levels-simulation analysis, Management Science, 16, 2, B-61–B-76, 1969.
• [23] Eppen G.D., Martin R.K., Determining safety stock in the presence of stochastic lead time and demand, Management Science, 34, 11, 1380–1390, 1988.
• [24] So K.C., Zheng X., Impact of supplier’s lead time and forecast demand updating on retailer’s order quantity variability in a two-level supply chain, International Journal of Production Economics, 86, 2, 169–179, 2003.
• [25] Sitek P., Wikarek J., A hybrid framework for the modelling and optimisation of decision problems in sustainable supply chain management, International Journal of Production Research, 53, 21, 6611–6628, 2015.
• [26] Sitek P., Nielsen I.E., Wikarek J., A hybrid multiagent approach to the solving supply chain problems, Procedia Computer Science, 35, C, 1557–1566, 2014.
• [27] Bocewicz G., Banaszak Z.A., Declarative approach to cyclic steady state space refinement: periodic process scheduling, The International Journal of Advanced Manufacturing Technology, 67, 1–4, 137– 155, 2013.
• [28] Eriksen P.S., Nielsen P., Order quantity distributions: estimating an adequate aggregation horizon, Management and Production Engineering Review, 7, 3, 39–48, 2016.
• [29] Nielsen I., Lim M., Nielsen P., Optimizing supply chain waste management through the use of RFID technology, Proceedings of 2010 IEEE International Conference on RFID-Technology and Applications, RFID-TA, pp. 296–301, 2010.

Uwagi

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