Sustainable asset management: A repair-replacement decision model considering environmental impacts, maintenance quality, and risk. (October 2019) - Abdi, Abdollah; Taghipour, Sharareh
Highlights: A repair/replace model with both economic and environmental factors is designed. An automatic decision tool (called R/R Calculator) is developed. Quality of preventive/corrective maintenance and uncertainties/risks are modeled. An inference mechanism is proposed to predict GHG emissions of the operation phase. The model provides advanced analytical features for sustainable asset management. Abstract: Equipment repair/replacement decision is an important aspect of asset management, which aims to find the best time to retire an in-use system considering its lifecycle costs. Previous lifecycle analysis techniques assume that the distribution of equipment's failure and repair time remain unaltered during the usage phase. In reality, however, the actual parameters that represent equipment's reliability and maintainability could change by several causal factors, including the quality of preventive and corrective maintenance, which can be dynamically adjusted through management intervention. Another dimension of repair/replacement problem is the environmental impact of equipment, which is important to be considered because of carbon pricing schemes as well as the international concerns about global warming. Not every aspect of this issue has been addressed in the published replacement decision models. Most importantly, the causality between equipment failure behaviour and its greenhouse gas (GHG) emissions has been seldom examined. The contribution of this paper is twofold. First, an economic repair/replacement model is developed in two phases: (1) deterministic phase, in which the mathematical structure of the total repair and replacement costs are defined, and (2) probabilistic phase, which incorporates the uncertainty of input parameters, risk events, quality of preventive maintenance, and repair perfection. Second, the economic model is extended to a combined model, in which the emissions associated with different phases of equipment lifecycle are considered. An inference mechanism is proposed to predict the emissions of operation phase of in-use equipment based on its failure behaviour. A plastic shredder case study is presented to illustrate the application of the proposed approach.