Abstract
Purpose
This work focuses on developing a production planning tool for small- and medium-sized enterprises (SMEs) in pharmaceutical manufacturing to achieve service levels that can meet their needs under highly competitive market conditions and fluctuating demand with efficiently and reasonable production costs. And, the tool is developed with the requirements of the general characteristics and constraints of industries.
Methods
The proposed tool is developed on a spreadsheet-based model that includes decisions to determine production and sequence orders to manage inventory levels. The production plans are simulated with actual data for 9 months. The results are then compared with the as-is method in terms of the service level and inventory level.
Results
The computational experiment shows that the service level has improved to 100% as targeted without additional inventory cost and capacity. In addition, it can improve the efficiency of planners with an easy-to-implement automation tool yielding less planning time and more agility to unexpected changes.
Conclusions
The model aims to improve the service level and operational efficiency of the case study. And, it is a practical approach for production planning in SMEs with limited on investment and expertise. It also has potential to be extended to high efficiency production planning systems.
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References
Heck M, Vettiger H. Production planning and scheduling and SME. Intern J Ind Manuf Eng. 2014;8(7):2276–88.
Stefansson H, Shah N, Jensson P. Multiscale planning and scheduling in the secondary pharmaceutical industry. AIChE J. 2006;52(12):4133–49.
Chaoleam S, Somboonwiwat T, Prombanpong S. The production planning of pharmaceutical production under Multi variables. 2013 IEEM. 2013.
Mukhopadhyay SK, Dwivedy J, Kumar A. Design and implementation of an integrated production planning system for a pharmaceutical manufacturing concern in India. Production Planning and Control. 1998;9(4):391–402.
Piller C, Wölfel DIW. Production planning for SMEs–Implementation of production planning with subject-oriented business process management (S-BPM). Comm Comp Inform Sci. 2014;422:164–73.
Filho OSS, Cezarino W, Ratto J. Aggregate production planning: modeling and solution via Excel spreadsheet and solver. IFAC Proceedings Volumes. 2010;43(17):89–94.
Vieira J, Deschamps F, Valle PD. Advanced planning and scheduling (APS) systems: a systematic literature review. Adv Transdis Eng. 2021.
Guzman E, Andres B, Poler R. Models and algorithms for production planning, scheduling and sequencing problems: a holistic framework and a systematic review. J Ind Inf Integr. 2022;27: 100287.
Friemann F, Schönsleben P. Reducing global supply chain risk exposure of pharmaceutical companies by further incorporating warehouse capacity planning into the strategic supply chain planning process. J Pharm Innov. 2016;11(2):162–76.
Martínez KYP, Toso EAV, Morabito R. Production planning in the molded pulp packaging industry. Comput Ind Eng. 2016;98:554–66.
Chen WL, Huang CY, Lai YC. Multi-tier and multi-site collaborative production: illustrated by a case example of TFT LCD manufacturing. Comp Ind Eng. 2009;57(1):61–72 (Collaborative e-Work Networks in Industrial Engineering).
Mula J, Poler R, García-Sabater JP, Lario FC. Models for production planning under uncertainty: a review. Int J Prod Econ. 2006;103(1):271–85.
Steger-Jensen K, Hvolby H-H, Nielsen P, Nielsen I. Advanced planning and scheduling technology. Prod Plan Control. 2011;22(8):800–8.
Alharkan IM. Algorithms for sequencing and scheduling. Riyadh: Saudi Arabia. Industrial Engineering Department, King Saud University. 2005.
Takahashi K, Nakamura N. Production planning and inventory control in a company manufacturing PC parts: a case study. Production Planning and Control. 2001;12(3):296–308.
Hervert-Escobar L, López-Pérez JF. Production planning and scheduling optimization model: a case of study for a glass container company. Ann Oper Res. 2020;286(1–2):529–43.
De Armas J, Laguna M. Parallel machine, capacitated lot-sizing and scheduling for the pipe-insulation industry. Int J Prod Res. 2020;58(3):800–17.
Asgeirsson El, Axelsdottir GS. and Stefansson, H. Automating a manual production scheduling process at a pharmaceutical company. 2011 IEEE Workshop On Computational Intelligence In Production And Logistics Systems (CIPLS).
Wang X, Li D, O’Brien C, Li Y. A production planning model to reduce risk and improve operations management. Int J Prod Econ. 2010;124(2):463–74.
Ashayeri J, Selen W. A production planning model and a case study for the pharmaceutical industry in the Netherlands. Int J Log Res Appl. 2003;6(1–2):37–49.
Sezen B, KitapÇi H. Spreadsheet simulation for the supply chain inventory problem. Prod Plan Control. 2007;18(1):9–15.
Wattitham S, Somboonwiwat T, Prombanpong S. Master production scheduling for the production planning in the pharmaceutical industry. Lect Note Elect Eng. 2015;267–276.
Walton S, Metters R. Production planning by spreadsheet for a start-up firm. Prod Plan Control. 2008;19(6):556–66.
Chien YI, Cunningham WHJ. Incorporating production planning in business planning: a linked spreadsheet approach. Prod Plan Control. 2000;11(3):299–307.
Olhager J, Wikner J. Production planning and control tools. Production Planning and Control. 2000;11(3):210–22.
Penlesky R, Srivastava R. Aggregate production planning using spreadsheet software. Prod Plan Control. 1994;5(6):524–32.
Techawiboonwong A, Yenradee P. Aggregate production planning using spreadsheet solver: model and case study. ScienceAsia. 2002;28(3):291–300.
Kempf K, Keskinocak P, Uzsoy R. Planning production and inventories in the extended enterprise. 1. New York, USA: Springer. 2011.
Land MJ, Gaalman GJC. Production planning and control in smes: time for change. Prod Plan Control. 2009;20(7):548–58.
Hopp WJ, Spearman ML. Factory Physics. 3rd ed. Singapore: McGrawHill. 2008.
Schneider U, Friedli T, Basu P, Werani J. Operational excellence in practice–the application of a Takt-time analysis in pharmaceutical manufacturing. J Pharm Innov. 2015;10(2):99–108.
Lee SL, O’Connor TF, Yang X, Cruz CN, Chatterjee S, Madurawe RD, et al. Modernizing pharmaceutical manufacturing: from batch to Continuous Production. J Pharm Innov. 2015;10(3):191–9.
Matt D, Modrak V, Zsifkovits H. Industry 4.0 for SMEs: challenges, opportunities and requirements. S.l., Switzerland: Springer Nature. 2021.
Acknowledgements
The authors would like to thank Advance Pharmaceutical manufacturing (APm), the pharmaceutical manufacturing company, for their inputs and support throughout this research.
Funding
This study was funded by The Scholarship from the Graduate School, Chulalongkorn University to commemorate the 72th anniversary of his Majesty King Bhumibol Aduladej.
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Niamchuen, P., Chaovalitwongse, P. & Sachakamol, P. Design of a Production Planning System in a Pharmaceutical Factory: Spreadsheet Model and Case Study. J Pharm Innov 18, 1371–1380 (2023). https://doi.org/10.1007/s12247-023-09736-3
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DOI: https://doi.org/10.1007/s12247-023-09736-3