In PreCoM project, Vertech is leading the Predictive Cognitive Maintenance performance analysis Work Package that includes four tasks: in-service availability analysis, work safety analysis, environmental impact assessment and costs evaluation. Vertech oversees the environmental and economic assessments using Life Cycle Thinking methodologies with the objective of demonstrating the potential benefits of the PreCoM solution regarding both environmental and economic aspects. Vertech aims at showing that an optimized maintenance system can potentially reduce the overall production costs and decrease the environmental impacts of the production lines.

Environmental performances are evaluated with the Life Cycle Assessment (LCA) methodology, a standardized tool (ISO 14040) to estimate the potential environmental impacts of a product or process through all its life cycle stages (material extraction, production, transport, end-of-life, etc.). LCA method is divided is four main steps: the definition of the goal and scope of the study, the collection of a life cycle inventory, the impact assessment using dedicated software and databases to convert the inventory into different categories of environmental impacts (e.g. global warming, eutrophication, resource depletion), and the conclusion. Life Cycle Cost assessment (LCC) is a similar methodology used for evaluating economic indicators such as the operational costs, the investment and the potential revenues from the studied product or process.

In the context of the PreCoM project, the LCA and LCC are applied to a maintenance service. The methodology and scope of the assessment are tailored to the specificity of the service provided by the PreCoM solution. A specific calculation model is currently under construction to evaluate the environmental and economic potential benefits of the PreCoM solution. This model is balancing the saving and benefit of reducing the failures and maintenance time of the industrial demonstrator line compared to the initial investment and operating costs for running the PreCoM maintenance solution. The model is especially showing the additional revenues available with a reduction of production stoppage (occurrence and duration). In the same idea, the environmental burdens linked to the production and operation of the PreCoM module are compared with the avoided environmental impacts due to failure and maintenance time (e.g. waste generated, low quality production after restart). A first version of the model has been developed and is being improved and adapted to the specificities of the demonstration lines. This work should shortly allow the comparison of environmental and economic performances before and after the development of the PreCoM modules in the industrial sites.