Investigation on the use of energy efficiency for condition-based maintenance decision-making

Condition-based maintenance (CBM) has been introduced in industrial systems to maintain preventively the correct equipment at the right time with regards to its current health condition represented mainly the conventional indicators such as oil temperature, harmonics data, vibration, etc. The monitoring of these indicators is done through sensors or inspection tasks leading to incorporate in the maintenance optimization models, additional costs related to CBM. Nevertheless, while this practice is quite mastered in terms of benefits and costs, it is not well adapted to face now the new challenge encountered by the industry of the future such as the sustainable one. Indeed CBM indicators and maintenance cost model are not really taken into account today emergent indicators (and their impacts) related to energy consumption, energy efficiency or footprint tracking. In that way, this paper is investigating the interest to use energy efficiency (EE) for CBM decision-making. Investigation is consisting first to propose a new EE-based CBM model by using energy efficiency indicator (EEI) which is defined as the amount of energy consumption to produce one useful output unit. The proposed model leads to consider energy directly in the maintenance optimization. An extension of an existing CBM by integrating energy consumption in optimization model is also investigated in the way to compare the new CBM approach with conventional (extended) one. The comparison step is developed on the case study of the TELMA platform allowing to assess the impact of EE on existing CBM strategies and to conclude on the interest of a new EE-based CBM practice both in terms of cost and efficiency. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.