Time compression in supply chains is a crucial aspect involved in the integration of warehousing and
transport operations in the manufacturing industries. Supply chain flows could be interrupted due to many sources of delays that lead to additional time in dispatching process and reduction in customer service level. The problem considered in this paper consists of long waiting times of loading vehicles inside the plant. This work presents a simulation-based study to minimize vehicle dispatching time in a steel wire plant. Value stream map is developed to present a system perspective of processes involved in the overall supply chain. Process activity mapping is completed to provide a step by step analysis of activities involved in the vehicle dispatch process. A simulation model is developed for the system and a new model is proposed to improve the delivery performance by minimizing vehicles’ waiting time.
K. R. Zuting
,
P. Mohapatra
,
Y. Daultani
,
M. K. Tiwari
. A synchronized strategy to minimize vehicle dispatching time: a real example of steel industry[J]. Advances in Manufacturing, 2014
, 2(4)
: 333
-343
.
DOI: 10.1007/s40436-014-0082-1
1. Potter A, Yang B, Lalwani C (2007) A simulation study of dispatch bay performance in the steel processing industry. Eur J Oper Res 179(2):567–578
2. Womack J, Jones D (1996) Lean thinking. Simon and Schuster, New York
3. Manson SJ, Ribera PM, Farris JA et al (2003) Integrating the warehousing and transportation functions of the supply chain.Transp Res E 39(2):141–159
4. Potter A, Lalwani C (2007) Developing a methodology to analyse despatch bay performance. Int J Prod Econ 106(1):82–91
5. Juntunen J, Juga J (2009) Controlling the bullwhip with transport capacity constraints. Int J Serv Stand 5(2):160–171
6. Zhao QH, Chen S, Leung SCH et al (2010) Integration of inventory and transportation decisions in a logistics system.
Transp Res E 46(6):913–925
7. Yeh IC (1995) Construction-site layout using annealed neural network. J Comput Civil Eng 9(3):201–208
8. Malakooti B, Tsurushima A (1989) Expert system using priorities for solving multiple-criteria facility layout problems. Int J Prod Res 27(5):793–808
9. Rother M, Shook J (2003) Learning to see: value stream mapping to create value and eliminate muda, version 1.3. Lean Enterprise Institute, Brookline
10. Hines P, Rich N (1997) The seven value stream mapping tools. Int J Oper Prod Manage 17(1):46–64
11. Chang Y, Makatsoris H (2001) Supply chain modeling using simulation. Int J Simul 2(1):24–30
12. Kleijnen JPC (2003) Supply chain simulation: a survey. CentER Discussion, Tilburg University
13. Disney SM, Naim MM, Potter A (2004) Assessing the impact of e-business on supply chain dynamics. Int J Prod Econ 89(2):109–118
14. Sterman JD (2000) Business dynamics: systems thinking and modelling for a complex world. McGraw-Hill, Boston
15. Spedding TA, Sun GQ (1999) Application of discrete event simulation to the activity based costing of manufacturing systems. Int J Prod Econ 58(3):289–301
16. Persson F, Olhager J (2002) Performance simulation of supply chain design. Int J Prod Econ 77(3):231–245
17. Kelton WD, Sadowski RP, Sturrock DT (2004) Simulation with arena. McGraw-Hill, New York
18. Oral M, Kettani O (1993) The facets of the modeling and validation process in operations research. Eur J Oper Res 66(2): 216–234
