The maintenance Cost Allocation in Product Life Cycle

Abstract

This article describes the concept by the customer view of the consuming life cycle. Because the purchase price the customer pays is equal to the cost of the producer plus value added, the life cycle costs of the customer perspective will most often be complete. The article focuses on the customer’s perspective to the lifecycle costs and not so much on the product life cycle. There are developed four main different ways of performing LCC depending on the amount of resources available, the time available, the degree of accuracy and other aspects. This study utilizes a combination of product life cycle analysis, advanced modern costing methods and regression data analysis processing for the product maintenance costs calculations in its life cycle. The combination is necessary for solving the research task; life cycle costs analysis considers only product maintenance costs in this article. In this article we use life time as a cost driver helping us to allocate the maintenance costs between different trucks in their different life time. This study presents the evaluation of the regression functions, describes its elements, illustrates the comparison and chooses the best. The elasticity analysis presenting the percent of the maintenance costs change if time has changed 1 %, is also used. The life cycle curve’s estimation shows that the longer exploitation period is, the bigger maintenance costs are. This can help to make a decision about the further exploitation of the truck during its valuable life cycle and after it. It is the main purpose why life cycle costing system was created and developed, using non traditional life cycle costing curve estimation. After the regression-correlation and elasticity analysis between trucks’ maintenance costs and the time of its exploitation, it is clear that the exponential correlation exists between them because correlation and determination as well as elasticity rates are the biggest in this model. At the end of the article it is calculated at what point of time the direct regression curve breaks exponent regression curve. The break even means the point where companies should use exponential regression formula for allocating maintenance costs to different trucks in order to get the most exact result for cost management. The procedure is demonstrated according to one of the iteration methods – string method. The main aspect of this method is that the chosen interval should be isolating and it should meet all the requirements for isolating interval: 1. Function changes its sign in the interval; 2. The first derivative function does not change its sign in the interval; 3. The second derivative function does not change its sign in the interval. The calculation manifests that the break even exists and is equal 6.15568 periods for Mercedes Benz trucks in the real transport company.