Quantitative-Based Inventory Control Methods for Personal Protective Equipment in Support of Sustainable Development Goals

Purpose – This study aims to evaluate the application of quantitative-based inventory control methods for Personal Protective Equipment (PPE) at PT XYZ, a mechanical-electrical contracting company, to support Sustainable Development Goals (SDGs) 3, 8, and 12. Methodology/approach – Using a descriptive quantitative case study, secondary data from 2024 were analyzed with Economic Order Quantity (EOQ), Periodic Order Quantity (POQ), Min-Max, and Lot-for-Lot (LFL) methods, supported by Reorder Point (ROP) and Safety Stock calculations. Class A PPE items identified through ABC analysis were selected as the research sample. Findings – EOQ consistently yielded the lowest total inventory cost compared to other methods, reducing costs significantly versus current practices. ROP and Safety Stock planning effectively mitigated demand fluctuations and supplier lead-time risks, ensuring continuous PPE availability. Novelty/value – The research integrates multiple quantitative inventory control models in a PPE management context, linking operational efficiency to sustainability outcomes. Findings provide practical recommendations for construction project logistics while aligning with SDG targets.