The overall architecture of the E2COMATION project is composed by several subsystems, each aiming at the realization of a specific set of functionalities that could contribute to a coherent and coordinate management of the sustainability and energy optimization for the manufacturing industry.

All of these subsystems need to elaborate a big amount of information, the majority being extracted from the production environment. To this aim, they need to be integrated and complementary to the existing automation and management architecture of a company, in order to continuously obtain energy-related information from any location of interest at the factory floor. Such an information, combined with enterprise-wide information, enable them to analyse all relevant correlation of competing aspects in order to derive useful elements to drive the foreseen optimization.

ECOMATION will provide a set of high-end optimization tools, addressing digital twin image of process, predicting variables trends, optimizing energy performances of production process and/or ancillary systems, and performing line simulation and LCA/LCC.

All the high end tools are depicted in the reference framework below.

e2com ref framework

IEC 61499 Modular and reconfigurable distributed monitoring, automation and control

A scalable automation solution to seamlessly move across the automation pyramid from machine, to cell, to line, till plant level:
  • Gathering data from all greenfield sensors and sending them to EMon (as unique collector)
  • Providing the control action
  • EMon – Energy Monitoring

    A comprehensive and holistic strategy to energy monitoring which is based on multichannel measurement methodology:
  • Fingerprint measurement
  • Component analysis / monitoring
  • KPI / EnPI
  • MQTT as E2COMATION backbone for communication

    MQTT is an OASIS standard messaging protocol for the Internet of Things (IoT). It is designed as an extremely lightweight publish/subscribe messaging transport that is ideal for connecting remote devices with a small code footprint and minimal network bandwidth.

    APAMA Stream Analytics: holistic analysis of energy-related data streams for production performance forecasting

    Live analysing and elaborating the data flows coming from the physical systems for:
  • Empowering the updating of DT model
  • Specific pattern/event recognition to detect triggering conditions
  • SDS: Distributed  Stream  Computing  platform  for  life-cycle  data analytics

    Handling, complementing, composing and offering aggregated views for high level tool use.

    Self Service Analytics

    User oriented “S.M.E.”tool to address:
  • How to visualize sensor data for operational storytelling?
  • How to analyse data to find root causes of deviating behaviours fast?
  • How to predict what’s likely to happen?
  • Digital twin of process factory asset

    A computational model to assess the effect of various changes in the process:

    • Process monitoring: detect deviations between DT and real process, and generate information that’s not directly/continuously measurable e.g. total energy usage, product quality, …
    • Process optimization – Using DT model to simulate the asset for different operational settings and find best control setpoints

    Energy and environmental performance-enabled multi-perspective simulation

    Simulation framework in which the dynamic digital twins of the manufacturing assets of the factory, composed of several independent behavioral models, will run and interact. Combine material flow analysis with energy specific and resource specific flows

    Energy Aware P&S/Process Control

    Energy Aware Optimization (Planning & Scheduling in Discrete manufacturing/Process Control in Process Industry) of production process, conjugating production efficiency and energy saving, by:
  • using flexibility in energy contracts based on real time exploitation of energy hourly price and
  • leveraging on available degrees of freedom in production process
  • SMART TEG Tool

    Smart Thermal/Electric Energy Grid  Management, capable of optimally controlling on-site energy generation units based on high-level dynamic models and forecast of the resource demand (from EAPO):
  • Unit commitment of generators
  • Optimal operating point (set-point)
  • LCA&Costing Tool

    Modular and dynamic tool to assess Life Cycle Assessment and Costing at factory/value chain levels against PEF/OEF, and also to predict environmental footprint.

    S-CAPP Tool

    Generative CAPP Tool where the system automatically checks for requirements of components and selects the right processes. Generating new production pipelines based on different EPD/PEF factors of energy efficiency and environmental impact (sustainability-driven).

    LCA driven SCM tool

    Integrated management system, by evolving the Bloomy Decision AID based platform, to improve the value chain in both economic and sustainability terms. 

    E2COMATION DSS Platform

    Decision support platform for energy optimization and life cycle management

    • Implements a Cloud based solution that integrates all tools and modules into one robust platform
    • Handles the interaction of the different modules


  • Blockchain-based data management concept for facilitating LCA
  • Sharing of environmental impact data of processes and products accessible by everyone thanks to a public infrastructure