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Abstract

This study examines the production capacity challenges faced by PT RAS following the launch of RAS Gleam in November 2023. The significant increase in demand has put pressure on the production, filling, and packing workstations, leading to potential bottlenecks in fulfilling orders. To address this issue, time-series forecasting was applied to project demand for the next year for three products: RAS Self-Cleaning, RAS Instant Antifog, and RAS Gleam. These forecasts guided the development of a Master Production Schedule (MPS) to align production with projected demand and informed Rough-Cut Capacity Planning (RCCP) to identify capacity constraints. The analysis revealed gaps between available and required work hours, particularly during peak periods. To bridge these gaps, the study proposed workforce management solutions, including a controlled overtime system and the strategic use of freelance workers for filling and packing workstations. These measures enabled PT RAS to meet demand while complying with Indonesian labour regulations. The findings demonstrate how accurate forecasting, workforce optimization, and flexible labour management enhance production efficiency and operational flexibility at PT RAS. By forecasting demand, PT RAS can prepare for future conditions, ensuring it has the capacity to meet demand.

Keywords

Demand Forecasting MPS RCCP Workforce Management

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Azzahra, N., & Mulyono, N. B. (2025). Demand Forecasting and Capacity Planning for Eyewear Cleaner Products at PT RAS. Ilomata International Journal of Management, 6(3), 824-847. https://doi.org/10.61194/ijjm.v6i3.1469

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