(untitled) (INTERNATIONAL JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING, 2024)
This work aimed at developing a web-based inventory management model for application in firms where data on inventory collection, storage, retrieval, analysis, and good management decisions are needed for well-informed management policy-making and for monitoring the overall performance of the establishment. This study applied an autoregressive moving average (ARMA) time series modelling approach to generate a model for forecasting monthly production quantity in Unizik Plastic Unit. A web-based inventory system for easy recording, visualization, and monitoring of inventory in the unit was developed using the My structured query language (MySQL) database. The generated ARMA model, economic order quantity model, suppliers, customers, and other useful information were built into an inventory management database system to enable continuous data collection, storage and quick access to inventory data on the target establishment. The results showed that out of the various ARMA models examined, ARMA (1,1) model, with the lowest Bayesian information criterion, mean absolute percentage error and root mean square error, was selected as the most suitable model for forecasting of monthly quantity of production in the unit. The autocorrelation and partial autocorrelation plots of the residuals of the model and the Ljung-Box statistic revealed that the model is free from serial correlation, hence, adequate and fits well for the production data in the unit. The developed inventory management database system showed a great improvement in the inventory control in the unit over the existing inventory management practice in the unit.