Case study of an equivalent annual cost model for economic lifetime for construction vehicles under cost uncertainty

Abstract

Whereas the practical importance of the Economic Lifetime (EL) is well-known, selecting the proper process has always been a dilemma. In this respect, classical methods dating back to one century ago are generally favored, but using them in a data-driven approach still has particular shortcomings. This paper aims to present a Life Cycle Cost (LCC) model determining the EL of a truck while fluctuation in historical data deepens through its lifespan. The equivalent annual cost of LCC is developed based on Operating and Maintenance (O&M) costs along with the resale value. The O&M cost was estimated deterministically and stochastically using regression analysis and Brownian-Motion-based simulation. The resale value was modeled by employing a genetic algorithm. The model capability was evaluated using real data of a seven cubic-meters truck hauling rock-fill materials in a dam construction project. The optimal EL was estimated on average 105 months in deterministic condition, while it was 88-145 months at the 70% confidence level using non-deterministic approach.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request. (O&M Cost Data, MATLAB Codes).

Additional information

Notes on contributors

Mohamad Zarean

Mohammad Zarean completed his master's degree in mine economics and management at Tarbiat Modares University, Tehran, Iran. His main research interests are cost predictions and uncertainty analysis, applied in his master thesis. Besides the academic implementation of his research interest, he has delivered several cost-estimation projects, where he has worked as a construction management engineer. LinkedIn: https://www.linkedin.com/mwlite/in/mohamad-zarean-0396a0156

Ahmad Reza Sayadi

Dr. Ahmad Reza Sayadi is an associate professor in the Department of Mining Engineering at Tarbiat Modares University, Tehran, Iran. He is president of the Iranian Society of Mining Engineering (IRSME) since 2019. He has received his M.Sc. and Ph.D. degrees in mining economics from Mines Paris Tech, Paris, France. His research areas include economics, modeling and optimization, maintenance, supply chain, and productivity management. He has 18 years of teaching and research experience and eight years of activity in the mining industry. LinkedIn: https://www.linkedin.com/in/ahmad-reza-sayadi-20a28145

Amin Alah Mousavi

Dr. Amin Mousavi is an Assistant Professor within the Department of Mining Engineering at Tarbiat Modares University in Iran. Amin joined Tarbiat Modares University in 2017, after completing his Ph.D. at the Queensland University of Technology, Australia. In a joint research project with CRC ORE and BHP Billiton, Amin completed his Ph.D. and developed a mathematical-based optimization tool to solve open-pit mining short-term planning. LinkedIn: https://www.linkedin.com/in/amin-mousavi-29855452