Stochastic assessment of the material haulage efficiency in the earthmoving industry

Ozdemir, B and Kumral, M (2017) Stochastic assessment of the material haulage efficiency in the earthmoving industry. Journal of Construction Engineering and Management, 143(8): 05017013, ISSN 0733-9364

Abstract

The match factor is a criterion that measures efficiency of truck and loader compatibility used in the construction industry. This factor is a function of number of trucks and loaders, truck cycle time, and loader loading time. However, these parameters are uncertain in nature because of equipment failures, climate, road conditions, and operator habits. Fluctuations in the match factor result in truck queues or idle loaders waiting, which lead to production losses or opportunity costs. In this paper, a stochastic approach is proposed to assess the risks associated with uncertain parameters in the match-factor equation. The approach is based on coupling of Markov-chain Monte Carlo simulations for a number of available equipment and Ordinary Monte Carlo simulations for loader loading and truck cycle times. Thus, the variations in the match factor over a time series are quantified in such a way as to determine equipment capacity utilization and maintenance management strategy. A case study has been carried out and the results show that the proposed approach can be used as a tool to assist production planning of material handling in the construction industry.

Item Type: Article
Uncontrolled Keywords: fleet efficiency; Markov chains; Markov-chain Monte Carlo simulation; match factor; ordinary Monte Carlo simulation; quantitative methods
Index terms: quantitative method, variation, habit, material handling, time series, production planning, strategy, loading, earthmoving, construction industry, Markov chain, case study, maintenance management, efficiency, coupling, Monte Carlo simulation
Subjects: modelling and simulation, project delivery, data analysis and analytics, construction operations, data science, product delivery, mathematical modelling, data collection methods, health behaviours and lifestyles, systems engineering, industry analysis, performance management, maintenance engineering, management, contractual condition
Topics: Engineering Principles, Research Practice, Project Management, Business Strategy, Supply Chain Management, Quality Management, Contract Administration, Site Management
Descriptive scope: 5 PCTEA

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