Citation :

Jhonatan David Malpartida Hermitaño, Jezzy James Huaman Rojas, "Reducing Truck Dwell Time in an Andean Wholesale Market through Lean-Green Six Sigma, Discrete-Event Simulation, and Energy-Environmental Assessment," International Journal of Engineering Trends and Technology (IJETT), vol. 74, no. 8, pp. 294-308, 2026. Crossref, https://doi.org/10.14445/22315381/IJETT-V74I8P120

Abstract

Congestion in Andean wholesale food markets is primarily due to a concentration of truck arrivals in specific time periods, combined with inadequate unloading infrastructure and a lack of control during peak periods. This study analyzes the impact of unloading capacity on truck dwell time in an Andean wholesale market, bringing together Lean-Green Six Sigma, DMAIC, and discrete-event simulation coupled with an energy-environmental assessment. The receiving and unloading process was modeled as a discrete-event system characterized by stochastic truck arrivals, FIFO service, and three unloading capacity scenarios with 10, 15, and 20 unloading bays. The primary measure of truck dwell time was supported in the analysis by the indicators of maximum truck dwell time, process variability, and energy consumption. From the results, the baseline scenario with 10 unloading bays presented an average truck dwell time of 101.342 minutes. With the unloading capacity expanded to the 15 and 20-bay scenarios, average truck dwell time was reduced to 70.007 minutes (30.9% improvement) and 54.644 minutes (46.1% improvement). The concurrent reduction of both maximum truck dwell time and its variability confirmed that the lack of unloading capacity was the primary operational bottleneck. The integration of LGSS with discrete-event simulation provides, integrates a rigorous methodology for diagnosing congestion in Andean wholesale markets. The methodology was also useful for evaluating unloading capacity and operational improvements.

Keywords

Lean-Green Six Sigma, Energy-environmental, Discrete-event, Truck dwell time, Wholesale food market.

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