Abstract
With the increasing demand for well-being and beauty, the dental industry has been strongly impacted in recent years. Consequently, companies in the dental implant production sector have needed to adjust their production volumes, sales, and product availability to meet market demand. Therefore, optimizing their product distribution network is essential to ensure timely delivery and customer satisfaction.
To achieve this performance, several aspects are taken into consideration, such as the strategic choice of the company’s distribution center locations, the quantity of these centers, and the target clientele for each. This study proposed a new strategic point for the distribution of Neodent’s products, based on the location of the company’s candidate stores to become distribution centers. To this end, data on the distance and location of the company’s stores, provided by Neodent, were compiled and implemented in the OpenSolver add-in for Excel, using the p-median mathematical model for facility location problems.
The results obtained through this tool proved to be valid, as they met both the overall and specific objectives of the study. They also demonstrated a significant cost-saving in the total road transport distance covered by the company’s logistics department.
The aforementioned challenges are particularly relevant to supply chain management. As the dental industry continues to face increased demand, optimizing distribution strategies has become a central concern for companies. It is crucial for them to ensure customer satisfaction and keep up with the growing demand for their products.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Schaefer, J.L., Baierle, I.C., Sellitto, M.A., Furtado, J.C., Nara, E.O.B.: Competitiveness scale as a basis for brazilian small and medium-sized enterprises. EMJ – Eng. Manage. J. 33(4), 255–271 (2021)
ABIMO. https://abimo.org.br/bid-brasil/. Accessed 18 July 2023
Nora, L.D.D., Siluk, J.C.M., Júnior, A.L.N., Nara, E.O.B., Furtado, J.C.: The performance measurement of innovation and competitiveness in the telecommunications services sector. Int. J. Bus. Excell. 9(2), 210–224 (2016)
Baierle, I.C., Schaefer, J.L., Sellitto, M.A., Furtado, J.C., Nara, E.O.B.: MOONA software for survey classification and evaluation of criteria to support decision-making for properties portfolio. Int. J. Strat. Prop. Manage. 24(2), 226–236 (2020)
Hamasaki, K., Gonçalves, M.C., Junior, O.C., Nara, E.O.B., Wollmann, R.R.G.: Robust linear programming application for the production planning problem. In: Deschamps, F., Pinheiro de Lima, E., Gouvêa da Costa, S.E., Trentin, M., (eds.) Proceedings of the 11th International Conference on Production Research – Americas, ICPR 2022, pp. 647–654. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-36121-0_82
Hansen, P., Brimberg, J., Urošević, D., Mladenović, N.: Solving large p-median clustering problems by primal-dual variable neighborhood search. Data Min. Knowl. Discov. 19(3), 351–375 (2009). https://doi.org/10.1007/s10618-009-0135-4
Aldrighetti, R., Battini, D., Ivanov, D., Zennaro, I.: Costs of resilience and disruptions in supply chain network design models: a review and future research directions. Int. J. Prod. Econ. 235, 108103 (2021). https://doi.org/10.1016/j.ijpe.2021.108103
Goncalves, M., Sampaio, R., Wollmann, R., Nara, E.Dias, I.: Using robust approach concept to solve the production planning problem in manufacturing systems. In: International Joint Conference on Industrial Engineering and Operations Management, IJCIEOM 2022. Springer Proceedings in Mathematics and Statistics (2023)
Dias, I., Sampaio, R., Wollmann, R., Goncalves, M., Nara, E.: A decomposition scheme in production planning based on linear programming that incorporates the concept of a dynamic planning environment. In: International Joint Conference on Industrial Engineering and Operations Management, IJCIEOM 2022. Springer Proceedings in Mathematics and Statistics (2023)
Gonçalves, M.C, Wollmann, R. R. G., Sampaio, R.J.B.: Proposal of a numerical approximation theory to solve the robust convex problem of production planning. Int. J. Oper. Res. (2023). https://doi.org/10.1504/IJOR.2022.10049618
Allaoui, H., Guo, Y., Choudhary, A., Bloemhof, J.: Sustainable agro-food supply chain design using two-stage hybrid multi-objective decision-making approach. Comput. Oper. Res. 89, 369–384 (2018). https://doi.org/10.1016/j.cor.2016.10.012
Masone, A., Sterle, C., Vasilyev, I., Ushakov, A.: A three-stage p-median based exact method for the optimal diversity management problem. Networks 74(2), 174–189 (2019). https://doi.org/10.1002/net.21821
Gonçalves, M.C., Canciglieri, A.B., Strobel, K.M., Antunes, M.F., Zanellato, R.R.: Application of operational research in process optimization in the cement industry. J. Eng. Technol. Ind. Appl. 6(24), 36–40 (2020). https://doi.org/10.5935/jetia.v6i24.677
De Faria, G.L., Gonçalves, M.C.: Proposition of a lean flow of processes based on the concept of process mapping for a bubalinocultura based dairy. J. Eng. Technol. Ind. Appl. 5(18), 23–28 (2019). https://doi.org/10.5935/2447-0228.20190022
Junior, O.J.T., Gonçalves, M.C.: Application of quality and productivity improvement tools in a potato chips production line. J. Eng. Technol. Ind. Appl. 5(18), 65–72 (2019). https://doi.org/10.5935/2447-0228.20190029
Acknowledgments
The authors would like to thank the Pontifical Catholic University of Paraná (PUCPR), PPGEPS-PUCPR and Neodent® Straumann Group.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 IFIP International Federation for Information Processing
About this paper
Cite this paper
Gonçalves, M.C., Pamplona, A.B., Nara, E.O.B., Dias, I.C.P. (2023). Optimizing Dental Implant Distribution: A Strategic Approach for Supply Chain Management in the Beauty and Well-Being Industry. In: Janssen, M., et al. New Sustainable Horizons in Artificial Intelligence and Digital Solutions. I3E 2023. Lecture Notes in Computer Science, vol 14316. Springer, Cham. https://doi.org/10.1007/978-3-031-50040-4_28
Download citation
DOI: https://doi.org/10.1007/978-3-031-50040-4_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-50039-8
Online ISBN: 978-3-031-50040-4
eBook Packages: Computer ScienceComputer Science (R0)
