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Design of a Production Planning System in a Pharmaceutical Factory: Spreadsheet Model and Case Study

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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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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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Correspondence to Paveena Chaovalitwongse.

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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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