Developing a Predictive Model to Forecast Optimal Production Quantity Under Uncertainty: A Systematic Literature Review

Production planning is essential for a manufacturing firm to work smarter by efficiently utilizing its internal resources to meet customer orders or demands. Furthermore, it typically involves scheduling, sequencing, selecting the production mix, deciding the optimal production quantities, and spotlighting the most flavored product categories based on the forecasted demands. Moreover, this production planning is a crucial step in a manufacturing industry, predominantly when the system operates in a stochastic uncertain environment. In the actual scenario, planning the optimal production quantity is often conducted under a variety of uncertainties together, such as demand, funds availability, machine availability, worker efficiency, material availability, etc. As a result, it is significant to consider all these production constraints while making production decisions within the manufacturing firm. The determination of this study is to give a comprehensive overview of the current production planning-related literature, including mathematical models to predict optimal production quantity subjected to various kinds of production limitations, with the objective of identifying beneficial study gaps for the future to improve production planning in uncertain situations. The study’s findings have demonstrated the constraints and limitations of production planning and method that optimize the utilization of resources with multiple objectives and better demand forecasting methods under the influence of external factors that are desirable with current manufacturing operations. Finally, it has summarized results and future research opportunities to increase the convenience of making production decisions in critical situations.