Modelling & Simulation as a Strategic Tool for Decision-Making Process: A Dairy Case Study




Modelling and Simulation, Dairy Industry, decision-making process, optimisation, GAMS


The Dairy Industry faces many challenges compared to other sectors. On the supply side due to the nature of the raw material, large inventories are not applied; during the manufacturing process, the continuous production is highly sensitive to any sort of unplanned disruption; and on the demand side, the market dictates the commodity prices. In response to the growth in competition, dairy organizations’ strategy must incorporate technology into their daily processes in order to become more efficient, profitable and sustainable. To achieve desired levels of improvement, Modelling and Simulation has been increasing in popularity in the decision-making process. Using a Dairy company as a case study, this paper has highlighted the potential for Modelling and Simulation to be used as a powerful strategic tool for decision-making processes.

Author Biography

Cristiani Eccher, Dublin City University

Manufacturing Engineering


ABED, S. Y. (2008) ‘Improving Productivity in Food Processing Industries Using Simulation - A Case Study’, 12th WSEAS International Conference on SYSTEMS, pp. 596–602.

Alvfors, O. (2015) Optimization of Production Scheduling in the Dairy Industry. KTH Royal Institute of Technology, Stockholm, Schweden.

Amorim, P., Günther, H. O. and Almada-Lobo, B. (2012) ‘Multi-objective integrated production and distribution planning of perishable products’, International Journal of Production Economics, 138(1), pp. 89–101. doi: 10.1016/j.ijpe.2012.03.005.

An Introduction to GAMS (2017). Available at: (Accessed: 30 November 2017).

Bei, L. B., Jie, Y. C. and Jian, C. (2006) ‘A centralized optimization of dairy supply chain based on model predictive control strategy’, 2006 7th International Conference on Computer-Aided Industrial Design and Conceptual Design, pp. 1–6. doi: 10.1109/CAIDCD.2006.329449.

Doganis, P. and Sarimveis, H. (2007) ‘Optimal scheduling in a yogurt production line based on mixed integer linear programming’, Journal of Food Engineering, 80(2), pp. 445–453. doi: 10.1016/j.jfoodeng.2006.04.062.

Eccher, C. and Geraghty, J. (2017) ‘MODELLING & SIMULATION AS A STRATEGIC TOOL FOR DECISION-MAKING PROCESS IN THE DAIRY INDUSTRY’, in International Conference on Decision Making in Manufacturing and Services (DMMS 2017), pp. 97–107.

Farahani, R. Z. et al. (2014) ‘Competitive supply chain network design: An overview of classifications, models, solution techniques and applications’, Omega (United Kingdom). Elsevier, 45, pp. 92–118. doi: 10.1016/

Fuentes, E. et al. (2016) ‘Supporting small-scale dairy plants in selecting market opportunities and milk payment systems using a spreadsheet model’, Computers and Electronics in Agriculture. Elsevier B.V., 122, pp. 191–199. doi: 10.1016/j.compag.2015.12.025.

Guan, Z. and Philpott, A. B. Ã. (2011) ‘A multistage stochastic programming model for the New Zealand dairy industry’, Intern. Journal of Production Economics. Elsevier, 134(2), pp. 289–299. doi: 10.1016/j.ijpe.2009.11.003.

Gunasekaran, A., Patel, C. and McGaughey, R. E. (2004) ‘A framework for supply chain performance measurement’, in International Journal of Production Economics, pp. 333–347. doi: 10.1016/j.ijpe.2003.08.003.

Heinschink, K., Shalloo, L. and Wallace, M. (2016) ‘The costs of seasonality and expansion in Ireland’s milk production and processing’, Irish Journal of Agricultural and Food Research, 55(2), pp. 100–111. doi: 10.1515/ijafr-2016-0010.

Li, W., Zhang, F. and Jiang, M. (2008) ‘A simulation and optimisation-based decision support system for an uncertain supply chain in a dairy firm’, International Journal of Business Information Systems, 3(2), p. 183. doi: 10.1504/IJBIS.2008.016585.

Nutter, D. W. et al. (2013) ‘Greenhouse gas emission analysis for USA fl uid milk processing plants : Processing , packaging , and distribution’, International Dairy Journal. Elsevier Ltd, 31, pp. S57–S64. doi: 10.1016/j.idairyj.2012.09.011.

Özbayrak, M., Papadopoulou, T. C. and Akgun, M. (2007) ‘Systems dynamics modelling of a manufacturing supply chain system’, Simulation Modelling Practice and Theory, 15(10), pp. 1338–1355. doi: 10.1016/j.simpat.2007.09.007.

Prices of EU Dairy Commodities (2019). Available at: (Accessed: 7 December 2019).

Qiang, S., Yun-xian, H. O. U. and Xian-glin, L. U. (2010) ‘Study on the Quality-Control Mechanism of Dairy Supply Chain based on External Lose Sharing model’, International Conference on Future Information Technology and Management Engineering, pp. 247–251.

Reid, R. D. and Sanders, N. R. (2012) Operations Management. 5th edn.

Reiner, G., Gold, S. and Hahn, R. (2015) ‘Wealth and health at the Base of the Pyramid : Modelling trade-offs and complementarities for fast moving dairy product case’, Intern. Journal of Production Economics. Elsevier, 170, pp. 413–421. doi: 10.1016/j.ijpe.2015.08.002.

Scramim, F. C. and Batalha, M. O. (2003) ‘Assessment method for supply chain benefits’, Journal on Chain and Network Science, 3(2), pp. 95–107. doi: 10.3920/JCNS2003.x033.

Slack N., Brandon-Jones A., J. R. (2013) Operations Management. 7th edn. Edited by Pearson.

Sonesson, U. and Berlin, J. (2003) ‘Environmental impact of future milk supply chains in Sweden: a scenario study’, Journal of Cleaner Production, 11(3), pp. 253–266. doi: 10.1016/S0959-6526(02)00049-5.

Tan, K.C, Leong, G. . (2017) Principles of Supply Chain Management – A balance Approach. 5 ed. Edited by L. Cengage. Boston, MA.

Tonanont, Yimsir S., Jitpitaklert W., R. A. (2008) ‘Performance evaluation in reverse logistics with data envelopment analysis’, IIE Annual Conference. Proceedings, pp. 764–769.




How to Cite

Eccher, C., & Geraghty, J. (2020). Modelling & Simulation as a Strategic Tool for Decision-Making Process: A Dairy Case Study. Decision Making in Manufacturing and Services, 14(1).