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.

中文翻译：

---

林业机械设备更换政策

摘要在这项工作中，我们提出了一个模型，以使用详细的设备维护计划在巴西林业部门的背景下协助设备更换决策过程。这些方法基于三种情景的经济寿命 (EL) 方法。在第一个场景中，我们考虑在第一阶段购买一台新机器。第二种情况，我们考虑保留现有机器24个月，然后购买一台新机器；第三种情况，我们考虑出售现有机器，租用新机器24个月，然后购买新机器。我们的示例来自巴西一家大型综合林业公司的森林种植园中的五台树木收割机，这些机器将树干切割、去枝并将其加工成原木。这些算法是用 Visual Basic for Applications (VBA) 编码的。结果表明，新机器贴现成本 (CNM) 和重建机器贴现成本 (CRM) 方案的价值高于租赁机器贴现成本 (CRE) 方案，这些解决方案应该被拒绝。新机器的经济寿命政策证明是最佳的 52 个月，而最好的决定是卖掉现有机器，租一台新机器 24 个月，然后再买一台新机器。描述了解决方案和使用的算法。租一个新的 24 个月，然后再买一个新的。描述了解决方案和使用的算法。租一个新的 24 个月，然后再买一个新的。描述了解决方案和使用的算法。