Six Sigma Performance Assessment of Coal Truck Payload Based on Non-Normal Capability and Sigma Level Analysis

Selamat Hia

doi:10.31181/sa202584

Authors

Selamat Hia Universitas Logistik dan Bisnis Internasional Author

DOI:

https://doi.org/10.31181/sa202584

Abstract

Coal hauling performance is strongly influenced by truck payload consistency, which affects transportation efficiency and compliance with operational specifications. This study assesses coal truck payload performance using a Six Sigma approach supported by non-normal capability analysis and Minitab. A total of 513 payload observations from Hino 260 JD trucks were evaluated against a lower specification limit (LSL) of 25 tons and an upper specification limit (USL) of 27 tons. The analysis included process stability assessment, normality testing, distribution identification, non-normal capability analysis, PPM estimation, process yield, and Sigma Level calculation. The results showed that the payload data were non-normal, with an Anderson–Darling statistic of 8.024 and p-value <0.005. The Largest Extreme Value distribution provided the best fit. Based on the observed performance, total nonconformance was estimated at 633,528 PPM, corresponding to an observed process yield of 36.65%, a Zbench of approximately −0.34, and a Sigma Level of 1.16σ using the conventional 1.5-sigma shift. The fitted distribution also estimated an expected overall nonconformance of 686,594 PPM, equivalent to an expected yield of approximately 31.34%. The I-MR chart indicated special-cause variation and limited process stability. These findings provide a quantitative baseline for reducing payload variation, improving process centering, and strengthening operational control.

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