Development of a dynamic costing model for assessing downtime and unused capacity costs in manufacturing
Lincoln, Andrew R.
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While costing methods have developed over time, they are often static in nature and ill-suited to the dynamic nature of production lines. Static costing systems are often developed for long-term analysis. Due to this, they lack the ability to aid short-term decision-making. In addition, the use of averaged data prohibits a static costing system from accurately tracing the cost effects of changing system behavior like random downtime events. A dynamic costing system, however, can capture the cost effects of changing system behavior in a manner that can aid short-term operational management. The proposed methodology is a dynamic activity-based costing method that relies on real-time production line data to track costs, specifically the added costs of unused capacity and downtime events. The methodology aims to trace these costs to responsible cost centers on the production line to give a better representation of the total cost of production, specifically in regards to normal production costs, added downtime costs, and added costs from unused capacity. In addition to monetary costs, the methodology provides a framework for tracking environmental costs, such as energy use, in order to aid plant managers with determining the environmental impact of their operations. The methodology addresses a gap between activity-based costing and downtime costing by combining the two under a single methodology. It traces both monetary and environmental costs to cost centers on the manufacturing line to aid continuous improvement efforts and the allocation of resources. By using real-time data, the methodology alerts management to changing system performance in a shorter time frame than static costing systems. The methodology will be shown in a case study of an automotive assembly plant. The case study will model the resource use of an automotive paint shop and trace this resource use to line segments in order to highlight areas of possible improvement.