Process industry is increasingly committed to decrease the environmental impact of its processes while, maximizing its economic performance. Industrial processes, encompassing production, marketing, sales and supply activities, usually interact with each other and share a large amount of data and information. Therefore, the integration of environmental assessment and economic performance optimization is a highly challenging objective. The effective integration of environmental and economic issues within the enterprise structure can only be achieved improving information sharing and communication. A promising solution approach stems from the application of knowledge management technologies. Several works in the literature consider environmental assessment within enterprise frameworks (1,2); however, none of them combines the potential of integrating environmental and economic issues with available enterprise data systems and analytical methods. Therefore, the representation of the life cycle inventory within a knowledge management model will provide decision makers a framework to assess and evaluate the environmental and economic impact of the enterprise activities. The aim of this work is to provide process analytical models with the necessary data and information related to the life cycle assessment, in order to optimize and evaluate them from an environmental and economic perspective thus supporting decision-making. The scope of these decisions encompasses the operational, tactical and strategic levels. Therefore, a semantic model approach representing an integrated enterprise framework and considering the different enterprise decision levels is proposed. A semantic model is developed using a systematic methodology for ontology development [3]. As a result, more environmentally conscious production processes can be obtained. The environmental performance is calculated using different environmental performance indicators. The assessment of these indicators is based on the resources consumption (energetic, raw material, human, etc.) and pollutants generation of products and processes.
Several examples related to waste-to-energy systems in the industry have been studied since it stands as an opportunity for providing decision makers with new technologies to assess and evaluate the plant performance. The framework supports information management based on a semantic representation of the whole process and its waste treatment, namely its operational and logistics functions, and assesses the potential of energy generation and savings. It is demonstrated that the ontological framework can adapt and recognize the different elements found through the hierarchy levels associated with the enterprise functions and relate them to their environmental and economic impact. As a result, it allows assessing the economic and environmental performance of the enterprises by communicating process life cycle data to analytical models.
As a whole, the main contribution of this work lies in a higher efficiency in communication and coordination procedures within the enterprise in order to assess and optimize its environmental and economic performance.
