Towards a Decision Support Framework for Sustainable Manufacturing

Every enterprise should track and asses its environmental impact for accountability reasons towards its consumers, employees, government, and society. The objective of this study is to design an eco-tracking framework and a decision support system architecture in order to provide energy visibility to enterprises by close monitoring the energy consumption of their manufacturing processes. The proposed architecture uses the energy consumption and production activity data as input. Energy consumption data is collected from meters and production activity data from manufacturing automation equipment (e.g. PLCs, CNCs, etc.). Collected energy data which is stored in a central data warehouse, is processed, contextualized with activity data and transformed to eco-KPIs in order to benchmark energy efficiency of the production processes and enable factory supervisors to make decisions towards better environmental footprint of the enterprise. The proposed decision support framework is founded on Software as a Service (SaaS) approach which can enable fast visibility of data throughout enterprise and provide easy scalability.