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Paper lc3-2017-011:
Implementing a Data-Driven Simulation Method for Quantifying Pipe Welding Operator Quality Performance

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Wenying Ji and Simaan Abourizk

Implementing a Data-Driven Simulation Method for Quantifying Pipe Welding Operator Quality Performance

Abstract: This paper proposes a framework for implementing a Markov Chain Monte Carlo (MCMC)-based posterior distribution determination approach to quantify pipe welding operator quality performance for industrial construction projects. The existing quality management data and engineering design data from a pipe fabrication company are processed and analysed to demonstrate the feasibility and applicability of the proposed approach. Through the use of a specialised Metropolis-Hastings algorithm, operator welding performance is quantified and uncertainty is incorporated. Practitioners can utilize outputs of the proposed method to infer operator welding quality performance of a particular weld type and identify operators with exceptional quality performance. Potential applications of the research findings are discussed from the perspectives of production planning, employee training, and strategic recruiting.

Keywords: Industrial Construction, Pipe Fabrication, Quality Management, Fraction Nonconforming, Markov Chain Monte Carlo (MCMC)

DOI: https://doi.org/10.24928/JC3-2017/0011

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