Equipment replacement policy for forest machines in Brazil

ABSTRACT

In this work, we present a model to assist in the equipment replacement decision process in the context of the Brazilian forestry sector using detailed equipment maintenance schedules. The approaches are based on the economic life (EL) method for three scenarios. In the first scenario, we considered buying a new machine during the first period. For the second scenario, we considered keeping the current machine for 24 months, and then buying a new one while for the third scenario, we considered selling the current machine, leasing a new one for 24 months and then buying a new machine. Our example draws from five tree harvesting machines that cut, delimb, and process the tree stem into logs in forest plantations of a large integrated Brazilian forestry company. The algorithms were coded in Visual Basic for Applications (VBA). The results show the new machine discounted cost (CNM) and rebuild machine discounted cost (CRM) scenarios presented higher values than the leased machine discounted cost (CRE) scenario, and those solutions should be rejected. The economic life policy proved optimum with 52 months for a new machine, while the best decision to make is sell the current machine, lease a new one for 24 months and then buy a new one. The solution and the algorithms used are described.

KEYWORDS:

• Infinite-horizon optimization
• harvesting
• economic life method
• logging

Acknowledgements

The authors thank two anonymous referees and the Editor-in-Chief Charlie Blinn for their valuable and helpful comments. Special thanks to the Brazilian forest company for their support during the data collection, special thanks to Mr. Eduardo Kremer, Mr. Reinaldo Correia, and Mr. Wanderlei Machado. The authors would also like to thank Mr. Jober Fonseca and Mr. Claumar Baldissera from Ponsse Brazil, and Mr. Wigando Netto from Ouro Verde. Finally, a special thanks to the College of Forestry at Oregon State University as this work was developed while visiting that institution.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.