Optimization of Truck Arrival Scheduling Using Truck Appointment Scheduling (TAS) Method to Minimize Waiting Time in FMCG Industry

Lifia Citra Ramadhanti; Jeni Marlina; Rakay Edhiargo Toyosito; Winarno

doi:10.35891/bjkprh88

Authors

Lifia Citra Ramadhanti University of Singaperbangsa Karawang , Department of Industrial Engineering, Universitas Singaperbangsa Karawang, Indonesia
Jeni Marlina
Rakay Edhiargo Toyosito
Winarno University of Singaperbangsa Karawang , Department of Industrial Engineering, Universitas Singaperbangsa Karawang, Indonesia

DOI:

https://doi.org/10.35891/bjkprh88

Keywords:

Truck, Waiting Time, Appointment System, Scheduling

Abstract

Distribution in the food manufacturing industry is essential to ensure supply chain effectiveness due to product time sensitivity. Fast moving consumer goods (FMCG) industryfaces high truck waiting times at its finished goods warehouse, causing delivery delays, increased operational costs, and reduced productivity. This study aims to analyze existing waiting time conditions, identify root causes, and evaluate application of Truck Appointment Scheduling (TAS). In contrast to previous studies on Truck Appointment Scheduling (TAS) in conventional warehouse settings, which primarily emphasize vehicle arrival scheduling, this study contributes a novel approach by integrating Truck Appointment Scheduling (TAS) with an Enterprise Resource Planning (ERP) system. The research methods include observation, questionnaires, Root Cause Analysis Diagram, and FMEA-based risk assessment approach. The results show that during May to September 2025, the average truck waiting time reached 691 minutes, exceeding the company standard of 240 minutes, with queue time accounting for 65%. The main causes were unscheduled truck arrivals and the absence of real-time queue monitoring. After implementing Truck Appointment Scheduling (TAS), waiting time decreased to 265 minutes and queue time to 29 minutes. These results indicate that the proposed approach effectively improves warehouse efficiency and reduces truck waiting time.

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References

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