A Generic Materials and Operations Planning Approach for Inventory Turnover Optimization in the Chemical Industry

  • Jairo R. Coronado-HernándezEmail author
  • Alfonso R. Romero-Conrado
  • Olmedo Ochoa-González
  • Humberto Quintero-Arango
  • Ximena Vargas
  • Gustavo Gatica
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12133)


Chemical industries usually involve continuous and large-scale production processes that require demanding inventory control systems. This paper aims to show the results of the implementation of a mixed-integer programming model (MIP) based on the Generic Materials and Operations Planning Problem (GMOP) for optimizing the inventory turnover in a fertilizer company. Results showed significant improvements for Inventory Turnover Ratios and overall costs when compared with an empirical production planning method.


Inventory turnover Production planning GMOP Fertilizers Chemical industry Optimization 


  1. 1.
    Calcium Nitrate - an overview|ScienceDirect Topics.
  2. 2.
  3. 3.
    Allman, A., Palys, M.J., Daoutidis, P.: Scheduling-informed optimal design of systems with time-varying operation: a wind-powered ammonia case study. AIChE J. 65(7) (2019).
  4. 4.
    Amaran, S., et al.: Long-term turnaround planning for integrated chemical sites. Comput. Chem. Eng. 72, 145–158 (2015). Scholar
  5. 5.
    Burawat, P.: Guidelines for improving productivity, inventory, turnover rate, and level of defects in manufacturing industry. Int. J. Econ. Perspect. 10(4), 88–95 (2016)Google Scholar
  6. 6.
    Castillo, P.C., Castro, P.M., Mahalec, V.: Multiperiod inventory pinch algorithm for integrated planning and scheduling of oil refineries. In: Computing and Systems Technology Division 2016 - Core Programming Area at the 2016 AIChE Annual Meeting, pp. 402–404 (2016)Google Scholar
  7. 7.
    Cunha, A.L., Santos, M.O.: Mathematical modelling and solution approaches for production planning in a chemical industry. Pesquisa Operacional 37(2), 311–331 (2017). Scholar
  8. 8.
    Dziurzanski, P., Zhao, S., Swan, J., Indrusiak, L.S., Scholze, S., Krone, K.: Solving the multi-objective flexible job-shop scheduling problem with alternative recipes for a chemical production process. In: Kaufmann, P., Castillo, P.A. (eds.) EvoApplications 2019. LNCS, vol. 11454, pp. 33–48. Springer, Cham (2019). Scholar
  9. 9.
    Garcia-Sabater, J.P., Maheut, J., Marin-Garcia, J.A.: A new formulation technique to model materials and operations planning: the generic materials and operations planning (GMOP) problem. Eur. J. Ind. Eng. 7(2), 119–147 (2013). Scholar
  10. 10.
    Kwak, J.K.: Analysis of inventory turnover as a performance measure in manufacturing industry. Processes 7(10) (2019).
  11. 11.
    Li, D., Zhang, X.: How time horizons and arbitrage cost influence the turnover premium? Appl. Econ. 51(44), 4833–4848 (2019). Scholar
  12. 12.
    Maheut, J., Garcia-Sabater, J.P.: Algorithm for complete enumeration based on a stroke graph to solve the supply network configuration and operations scheduling problem. J. Ind. Eng. Manage. 6(3 SPL.ISS), 779–795 (2013). Scholar
  13. 13.
    Maheut, J., Garcia-Sabater, J.P., Mula, J.: The generic materials and operations planning (GMOP) problem solved iteratively: a case study in multi-site context. In: Frick, J., Laugen, B.T. (eds.) APMS 2011. IAICT, vol. 384, pp. 66–73. Springer, Heidelberg (2012). Scholar
  14. 14.
    Maheut, J., Garcia-Sabater, J.P.: A parallelizable heuristic for solving the generic materials and operations planning in a supply chain network: a case study from the automotive industry. IFIP Adv. Inf. Commun. Technol. 397, 151–157 (2013). Scholar
  15. 15.
    Mostafaei, H., Harjunkoski, I.: Continuous-time scheduling formulation for multipurpose batch plants. AIChE J. 66(2) (2020).
  16. 16.
    Nugroho, Y.K., Zhu, L.: An integration of algal biofuel production planning, scheduling, and order-based inventory distribution control systems. Biofuels, Bioprod. Biorefin. 13(4), 920–935 (2019). Scholar
  17. 17.
    Odongo, I., Nag, B.: Achieving quality by rapid inventory turnover in the supply chain. Int. J. Prod. Qual. Manage. 19(2), 209–241 (2016). Scholar
  18. 18.
    Otashu, J.I., Baldea, M.: Scheduling chemical processes for frequency regulation. Appl. Energy 260 (2020).
  19. 19.
    Pacheco Velásquez, E.A.: Un modelo para la optimización de políticas de inventario conjuntas en cadenas de suministro. INGE CUC 9(1), 11–23 (2013).
  20. 20.
    Reetz, H.F.: Fertilizantes e seu Uso Eficiente, vol. 2 (2016).
  21. 21.
    Romero-Conrado, A.R., Coronado-Hernandez, J.R., Rius-Sorolla, G., García-Sabater, J.P.: A Tabu list-based algorithm for capacitated multilevel IoT-sizing with alternate bills of materials and co-production environments. Appl. Sci. (Switz.) 9(7), 1464 (2019). Scholar
  22. 22.
    Sabah, B., Nikolay, T., Sylverin, K.T.: Production planning under demand uncertainty using Monte Carlo simulation approach: a case study in fertilizer industry. In: Proceedings of the 2019 International Conference on Industrial Engineering and Systems Management, IESM 2019, pp. 1–6. Institute of Electrical and Electronics Engineers (IEEE), January 2019).
  23. 23.
    Talay, I., Özdemir-Akyıldırım, Ö.: Optimal procurement and production planning for multi-product multi-stage production under yield uncertainty. Eur. J. Oper. Res. 275(2), 536–551 (2019). Scholar
  24. 24.
    Wiemer, P.: Production planning and scheduling in chemical and pharmaceutical industry. In: European Control Conference, ECC 1999 - Conference Proceedings, pp. 4836–4841 (2015).
  25. 25.
    Yang, L.: Design of production management system in ERP of coal chemical industry. Chem. Eng. Trans. 65, 475–480 (2018). Scholar
  26. 26.
    Zheng, H.: Chemical enterprise production management system based on ERP. Chem. Eng. Trans. 62, 763–768 (2017). Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Universidad de la CostaBarranquillaColombia
  2. 2.Universidad Tecnológica de BolívarCartagenaColombia
  3. 3.Universidad Andrés BelloSantiagoChile

Personalised recommendations