A new, uncertainty-aware cost-model for cost-benefit assessment of robot systems
Thomas Dietz, Andreas Pott, Martin Hägele, Alexander Verl
- 发表年份
- 2013
- 引用次数
- 7
摘要
This paper introduces a new cost-model for robot systems with cognitive features for the use in small and medium sized enterprises (SME). The model combines approaches from activity-based costing and life-cycle costing to reflect machine and production-centric aspects of the use of robot systems. Key contribution of this paper is the handling of uncertainty in the input parameters of the cost-model by using methods from interval analysis. This approach allows to compute explicitly best and worst case scenarios without manual variation of parameters. The cost-model is tested for an application scenario for robotic de-burring and shows the economic performance of the robot system in best and worst case in an intuitive way.
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