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Model of the port performance metrics in ports by integration six sigma and system dynamics

Asep Ridwan (Transport Systems and Logistics, Universität Duisburg-Essen, Duisburg, Germany)
Bernd Noche (Institute of Transport Systems and Logistics, Universität Duisburg-Essen, Duisburg, Germany)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 2 January 2018

857

Abstract

Purpose

The purpose of this paper is to design a model of the port performance metrics for improving the quality in ports by integration of six sigma and system dynamics (SD) approach.

Design/methodology/approach

The port performance is measured by the sigma value (SV), the process capability indices (PCIs), and the cost of poor quality (COPQ) as the performance metrics. A port is a complex system that requires SD as an appropriate tool to simulate the model dynamically. The performance metrics focus on measuring the port performance in the entire flow of material in the cargo handling process.

Findings

With this model, the changing of the SV, the PCIs, and the COPQ can be identified and analyzed the results to improve the performance in ports. These metrics are utilized to eliminate “waste” in the cargo handling process at ports. This waste consists of lost and damaged cargo, equipment and transporter breakdown, and equipment and transporter delay time. The port performance metrics model can assess the causal relationships in ports as a complex system.

Originality/value

Studies on integration between the six sigma model and SD in ports are few and relatively limited. The port’s performance can be measured directly using the SV, the PCIs, and the COPQ in the simulation. The port performance metrics model will give the decision makers to make some scenarios to contribute for the optimization of performance in ports.

Keywords

Citation

Ridwan, A. and Noche, B. (2018), "Model of the port performance metrics in ports by integration six sigma and system dynamics", International Journal of Quality & Reliability Management, Vol. 35 No. 1, pp. 82-108. https://doi.org/10.1108/IJQRM-03-2016-0041

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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