Вход на сайт

Просмотр новости

Найдите то, что Вас интересует

“CleanGreen” launches: AI-based approaches for more energy-efficient industrial component cleaning

Дата публикации: 21-09-2026 12:00:00

With the kick-off meeting of the “CleanGreen” joint research project in September 2026, partners from industry and research began working together on new approaches for more energy- and resource-efficient industrial compo-nent cleaning. The project’s goal is to develop methods that will allow the energy, water, and chemical consumption of aqueous cleaning systems to be better adapted to actual cleaning requirements in the future.

Основное содержимое страницы с новостью.

With the kick-off meeting of the “CleanGreen” joint research project in September 2026, partners from industry and research began working together on new approaches for more energy- and resource-efficient industrial compo-nent cleaning. The project’s goal is to develop methods that will allow the energy, water, and chemical consumption of aqueous cleaning systems to be better adapted to actual cleaning requirements in the future.

Industrial cleaning processes are a key component of manufacturing in numerous industries. Aqueous cleaning processes, in particular, can consume significant amounts of energy depending on the system and process control. When designing systems and processes, the actual level of contamination on the components is generally not taken into account. Instead, cleaning processes are often designed and operated in such a way that components with varying degrees of contamination reliably achieve the required level of cleanliness. However, information on the actual level of contamination on the components and the current condition of the cleaning baths has often been lacking, preventing the adjustment of cleaning processes to meet actual needs. This is precisely where the “CleanGreen” project comes in. As part of the project, various data sources are to be consolidated and made available for intelligent process control. The plan is to link information from plant control systems, bath monitoring, production planning, and newly developed optical measurement methods.

Research platform at the Fraunhofer IST

For this work, an industrial cleaning system at the Fraunhofer Institute for Surface Engineering and Thin Films IST is being used as a research platform and is being gradually expanded to include additional measurement and sensor technology. On this basis, the necessary data will be collected, and various approaches to process evaluation and optimization will be investigated. As the project progresses, the plan is to test selected developments in prototype form at the industry partners’ facilities. In particular, the goal is to assess the extent to which the developed concepts can be transferred to both existing and new cleaning systems.

Making contaminants visible

In order to qualitatively and quantitatively detect organic contaminants on component surfaces in particular, an automated fluorescence measurement system using an F-scanner will be developed and integrated with the expertise of the Fraunhofer Institute for Physical Measurement Techniques IPM. The project participants aim to investigate to what extent this information can be used to assess the degree of contamination prior to cleaning and to evaluate the success of the cleaning process afterward. The data obtained will then be incorporated, together with additional process and sensor data, into AI-supported evaluation methods. The goal is to better understand the relationships between component condition, the cleaning process, and the cleaning result, and to derive recommendations for needs-based process control.

Contribution to energy efficiency and digitalization

The project addresses key challenges in industrial production. Companies are increasingly faced with the task of reducing energy and resource consumption while simultaneously ensuring high quality standards. “CleanGreen” aims to lay the groundwork for this by systematically consolidating data from various sources and making it usable for digital, data-driven decision-making processes. The long-term goal is to create the conditions for automated and demand-driven control of cleaning processes. In the future, integration into existing plants should also be possible. In addition, the information obtained is to be made available for subsequent manufacturing steps such as painting, electroplating, coating, bonding, or soldering processes.

About the project

“CleanGreen” – Energy-Efficient Cleaning Based on Quantified Component Contamination and AI-Optimized Wet-Chemical Cleaning Processes

In the “CleanGreen” joint research project, partners from industry and research are working together to address issues in the fields of industrial cleaning, optical metrology, sensor technology, data analysis, and AI-supported process control:

Project partners:

B+T Oberflächentechnik GmbH (coordination)
Fraunhofer Institute for Surface Engineering and Thin Films IST
Fraunhofer Institute for Physical Measurement Techniques IPM
Institute for Machine Tools and Manufacturing Technology (IWF) at the Technical University of Braunschweig
GNS Systems GmbH
G&M Galvanik UG

Project duration: July 2026 – June 2029

Funding reference: The project is funded by the German Federal Ministry for Economic Affairs and Energy (BMWE) under the grant number 03EN2151D.

Merkmale dieser Pressemitteilung:
Journalisten, Studierende, Wirtschaftsvertreter, Wissenschaftler, jedermann
Energie, Informationstechnik, Maschinenbau, Werkstoffwissenschaften
überregional
Buntes aus der Wissenschaft, Forschungsprojekte
Englisch

Схожие новости

#Наименование новостиТональностьИнформативностьДата публикации
1»CleanGreen« startet: KI-gestützte Ansätze für eine energie-effizientere industrielle Bauteilreinigung011.6821-09-2026
2Less scrap, better decisions: Project AluKauKi tackles manufacturing quality and waste using causal AI07.6424-09-2026
3Cleaner gas turbines using additive manufacturing: New technology works with a range of fuels 06.5224-09-2026
4Combining Generative AI and Knowledge Graphs in an Agent-Based Framework for Explainable Industrial Plant Intelligence018.1411-08-2026
5Chemists race to turn industrial waste into renewable resource06.8906-08-2026
6Less greenwashing and more clarity on environmental claims08.0325-09-2026
7World Cleanup Day: Effiziente Müllsammlung per KI08.4220-09-2026
8Green synthesis of Halloysite-Silver Nanocomposite: using Acalypha australisExtract, anti-E. coli effect and gene expression02510-08-2026
9How AI-Powered Preventive Maintenance Is Improving Workplace Safety015.4303-08-2026
10Ученые разработали концепцию фотонного "микропылесоса" для очистки чипов от наночастиц0009-09-2019

Классификация: Пресс-релизы. Схожих патентов: 0. Схожих новостей: 10. Тональность: 0. Информативность: 11.55. Источник: idw-online.de.