Aplicação da análise do custo do ciclo de vida de ativos físicos suportada pela engenharia da confiabilidade

Abstract

In the current context, in which organizations face the growth of cost-based competition, the application of tools to control, minimize and predict the costs of their assets is little coverage in industries. Decision making regarding equipment replacement is still driven by technical aspects and, in many cases, it happens late, without a long-term view, because it does not consider the total costs of its assets. The objective of this study is to determine the optimum replacement time in the medium and long term and to analyze the economic viability of physical assets of a motorized tool industry based on life cycle cost analysis (LCCA). The working method is it consists parametric recurrent event data analysis (RDA) to identify which equipments that has a wearout behavior and predict the number of corrective failures expected over the next seven years. In addition, will be estimated the expected costs for corrective and preventive actions through life data analysis (LDA) to build a cash flow where it was possible to verify the economic viability using the calculation of net present value (NPV), among the two proposed scenarios, reform or replacement, for the analyzed equipments. Also, it was possible to verify, by calculating the equivalent annual cost (EAC), the best time to implementation the most economically attractive scenario. Among the nine equipments analyzed, the results show that only four had a wearout behavior. Of these, an order of prioritization based on the highest potential savings was suggested. For the first two equipments of the order of prioritization, the immediate replacement was suggested, then of the third indicated the replacement in the year 2022 and the last one for the year 2023. In this way, the most attractive scenario, from a financial point of view, was the replacement of the four physical assets which presented savings in maintenance costs for the next seven years of R$ 990,145.00, in other words, the value of almost two new assets. In the context of the analyzed company, which has a serial process with an average of 400 large equipments, the study proved quite useful, because it allowed the company to identify the equipments that were in the wearout phase of the bathtub curve, to predict the costs and the future failures, analyze possible scenarios and identify the optimal replacement point, all in a quantitative manner and based on robust methodologies applied by reliability engineering. In addition, the study contributes to a clear and financial visualization for choosing the most advantageous strategy, facilitating managers' decision making and medium and long-term risk and investment management.