A MATLAB platform for production planning in batch processing firms producing items that are jointly replenished

Ademola David Adeyeye * and Abimbola Ezekiel Bello

Department of Industrial and Production Engineering, University of Ibadan, Nigeria.
 
Research Article
Global Journal of Engineering and Technology Advances, 2024, 20(03), 065–073.
Article DOI: 10.30574/gjeta.2024.20.3.0162
Publication history: 
Received on 22 July 2024; revised on 06 September 2024; accepted on 09 September 2024
 
Abstract: 
Rising levels of poverty have prompted manufacturers of non-durable consumer goods to explore opportunities at the lower end of the wealth spectrum. To enhance affordability for low-income consumers, these goods are often packaged in various sizes, including single-serve sachets. While numerous models and algorithms have been developed to determine the optimal frequency of manufacturing runs and packaging setups for the simultaneous replenishment of different pack sizes, there is a notable lack of literature addressing their implementation by small and medium-sized enterprises (SMEs) in this sector. This gap may be attributed to the absence of accessible source codes, a shortage of model experts, and the complexity involved in manual calculations. To address this issue, we developed a user-friendly MATLAB software platform based on Goyal’s algorithm, tailored specifically for SMEs. The software prioritizes simplicity, interactivity, and flexible visual displays. It was validated against examples from existing literature and through randomly generated scenarios. Users can easily compute the optimal number of manufacturing setups, packaging frequencies for each pack size, and the associated costs by inputting relevant data such as manufacturing setup, inventory holding and packaging setup costs, and demand for each pack size. Importantly, users do not need expertise in modeling to operate the software. However, it is designed for single-product deterministic environments; future research should explore multi-product and stochastic modeling scenarios.
 
Keywords: 
Consumer goods; Economic order quantity; Decision support system; Inventory management; Software platform
 
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