Digitalization, Artificial Intelligence and Related Technologies for Energy Efficiency and GHG Emissions Reduction in Industry
Start date 2018-11-01
End date 2023-12-31
The Final Report for Subtask 1 – Needs and Interests Assessment – was approved by written procedure 13 September 2021.
The proposals for Subtask 2 – Methods and Applications of Digital Twins and Subtask 3 – Lessons learned and value created with digitalization were approved by the IETS ExCo at the 33rd ExCo meeting in November 2021.
Austria, Canada, Denmark, France, Germany, Italy, Netherlands, Portugal and Sweden and organizations in Finland (VTT).
Mouloud Amazouz, CanmetENERGY, Natural Resources Canada
This Task seeks to advance knowledge and development of digitalization, artificial intelligence and related technologies to improve the economic and environmental performance of targeted energy and GHG-intensive industries. The initiative would seek to assemble a network of academic, research labs, IT providers and process industry stakeholders to cooperate on the availability, quality and use of data (quality, quantity, location, operational, energy, etc.); to align capacity; and inform decision-making relevant to the targeted sectors;
The objective of this Task is therefore to stimulate the adoption and digitalization technologies for energy efficiency improvement and GHG emissions reduction in the process industries. To achieve this objective, the Task sub-goals are:
- To create an international network and information infrastructure for stakeholders to exchange knowledge in the area of digitalization technologies
- To facilitate joint development of new knowledge and expertise on Digitalization
- To support and accelerate the deployment of digitalization practises in the energy-intensive process industries.
Subtask 2 – Methods and Applications of DigitalTwins
Task managers: René Hofmann (TU Wien, Austria) and Lauri Kujanpää (VTT, Finland)
Time frame: completed in 2024.
Subtask 2 focuses on Methods and Applications of Digital Twins to promote the application of DTs in industry, in order to improve energy efficiency and reduce GHG emissions. Subtask 2 has the following sub
- Overview of methods and applications of DTs and their requirements for different industry sectors
- Analysis of the potential benefits of these methods, focusing on the impact on energy efficiency and GHG emissions reduction
- Creation of an international, interdisciplinary network of research and industry
Work Plan for 2021-2022
- Hold three meetings for project presentations (December 7, 2021 and January 11 and 26, 2022)
- Evaluation of a survey on the state of the art of digital twins in industry among subtask participants and other stakeholders
- Hold a meeting to present and discuss the results of the survey (Feb. March, 2022)
- Analysis of Digital Twin methods and application along its life cycle (Q2 Q3, 2022)
Subtask 3 – Lessons Learned and Created Values by Digitalization
Task Managers: Zheng (Grace) Ma (SDU, Denmark) and Michelle Levesque (NRCan, Canada)
Time frame: completed in 2024.
Subtask 3 will review and explore the barriers and incentives and existing business models. It will include:
- Literature study to review the barriers and incentives and existing business models.
- Qualitative and quantitative data collection from case studies.
- Simulations (agent based modeling and discrete event simulation) to investigate the stakeholders’ adoption of digitalization strategies
Work Plan for 2021-2022
- Conduct a survey regarding case studies dissemination
- Identify and collect additional case studies (including meeting with Subtask 2 participants)
- Lesson learned activity via a Ph.D. visiting
- Continue the literature review on case studies
About the completed Subtask 1: Structure and Benefits
Subtask 1 started in 2019 and was completed in 2021.
Subtask Manager: Paul Stuart, Polytechnique Montréal (Canada)
The “needs and interests assessment” phase included the following work plan:
- Summary of the state-of-the-art: Digitalization, artificial intelligence and related technologies vocabulary, types of data, methods for their analysis, potential applications, an assessment of the growth drivers, barriers and needs (technology and knowledge) to adoption of digitalization, artificial intelligence and related technologies
- Overview of broad trends in industry Big Data and Data Analytics
- Survey of Big Data, Digitalization and Data Analytics centres of excellence and energy-intensive process sectors Big Data projects in participating IETS countries
- Case study reviews: Existing case studies on the use of Big Data in manufacturing plants
- Assessment of potential impact of Big Data on different process industry sectors, such as the forestry, the mining and smelting, oil and gas, energy production, and chemical and fertilizer sectors
- Identification of RD&D opportunities for strategic development of Big Data tools, methods and applications in the energy-intensive process sectors.
- Conduct a critical analysis collaboratively, and narrow to «common target area(s)» of interest by Task participants
Outcome: Establish the scope of the next Subtasks based on these discussions. Future Subtasks related to more defined areas of Big Data and Digitalization will be defined.
The objective of Subtask 1 is ambitious in the context of the very embryonic nature of digitalization, artificial intelligence and related technologies in the large emitter industrial sectors. Most researchers working in the targeted domain of the Task are not typically affiliated with the GHG emissions reduction and/or energy analytics community. The onus will be on Subtask 1 members in participating countries to be effective at identifying and attracting these researchers. It is critical to succeed in Subtask 1 to have long-term success in the new Task.
The main value proposal from participating in Subtask 1 includes:
- Familiarizing with the field of Big Data and Data Analytics broadly
- Understanding the actors and the opportunity for industry
- Becoming aware of the needs and the actions envisioned to help support energy-intensive process sectors
- Influencing the direction of future tasks in the Annex.
Participating countries in Subtask 1 will also give access to:
- Major conclusions on major barriers towards energy efficiency in the process industry (delivered via scientific publication on barriers and drivers)
- Summary and major findings of the Task 1 results to be freely disseminated, including recommendation for future research and developments.
- Proceedings/summaries of workshops.
- Executive project summaries presented to the IEA IETS Executive Committee.
- Newsletters presented at the IEA IETS homepage.
The deliverables for Subtask 1 were the following:
- White Paper:
- Basic definitions and context of the digitalization, artificial intelligence and related technologies field pertinent to the energy-intensive process sectors
- Types of data, methods for their analysis, potential applications, an assessment of the growth drivers, barriers and needs (technology and knowledge) to adoption of digitalization, artificial intelligence and related technologies
- List of the centres of excellence in the domain for participating countries
- Identification of case studies where digitalization, artificial intelligence and related technologies are deployed
- Trends in digitalization, artificial intelligence and related technologies
- Definition of gaps and priority areas in the domain for energy-intensive processes
- Identification of potential impacts of digitalization, artificial intelligence and related technologies on targeted industrial sectors
- Identification of RD&D opportunities for strategic development of tools, methods and applications in the energy-intensive process sectors.
- Critical analysis collaboratively, and identification of «common target area(s)» of interest by Annex participants
- Proposals for future Subtasks:
- The outcomes of Subtask 1 will highlight the needs, actions and opportunities of applying digitalization, artificial intelligence and related technologies to support energy-intensive process sectors. The white paper will help to establish the objectives, the scope and direction of future tasks in the Task.