Environmental assessment of consequences from predictive maintenance with artificial intelligence techniques: Importance of the system boundary
Annelie Carlson, Tomohiko Sakao
Abstract
This paper analyses a case of maintenance planning that was researched in previous work and thereby improved using predictive maintenance with an artificial intelligence (AI) technique. In particular, the environmental implications are presented using a life cycle assessment. Using AI to develop maintenance planning could be a feasible method that can outperform other strategies. However, the results of this analysis show that the economic and environmental performance depends largely on the assessment setting. Therefore, applying appropriate system boundaries and functional unit is of major importance to avoid sub-optimization when maintenance planning is developed.
Topics & Concepts
Predictive maintenanceEngineeringWork (physics)Computer scienceRisk analysis (engineering)Artificial intelligenceReliability engineeringBusinessMechanical engineeringTechnology Assessment and ManagementManufacturing Process and OptimizationDigital Transformation in Industry