Energy Efficiency in the Supply Chain through Coll.. (e-SAVE)
Energy Efficiency in the Supply Chain through Collaboration, Advanced Decision Support and Automatic Sensing
Date du début: 1 janv. 2012,
Date de fin: 30 juin 2014
The e-SAVE project aims to contribute to an energy-efficient supply chain by providing the system, services, collaboration platform and management tools that will help companies monitor, manage and share energy use and carbon footprint data in order to support operational as well as strategic decision making and supply chain design decisions. The project will specifically focus on the consumer goods sector, by involving the ECR Europe organisation, representing all major manufacturers and retailers in this sector, as well as one of its active members, Barilla, who pioneers in environmental sustainability practices. Emphasis is placed on industry adoption and quantifiable impact assessment.The e-SAVE technical approach relies on an interoperable information infrastructure that integrates ERP systems with automatic data capturing technologies (mainly smart energy meters and unique product identification technologies) in order to support generic components for energy efficiency monitoring and life cycle assessment; upon these e-SAVE deploys new optimization algorithms for energy-efficient supply chain operations, simulation models and tools for strategic supply chain design decisions and dynamic energy-efficiency product labelling. The project will further build on existing market-leading tools owned by the e-SAVE partners in the fields of energy-monitoring, life-cycle assessment and simulation. Contribution to information sharing standards and energy efficiency ontologies will also be sought.Overall, the e-SAVE project aims to deliver a modular and extensible information, collaboration and management support infrastructure that not only captures the data required for effectively monitoring energy use and other environmental measures, but also provides the management tools that utilize this information and support decisions and every day operations for reducing energy consumption and carbon emissions in a feedback loop.
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