Digitalisation

Industrial plants can benefit from digitalisation – like artificial intelligence and sensors – to enable efficient use of energy and resources. Our program Digitalisation supports the application of digital technologies in research, operations, and maintenance.

Digital technology can improve traceability of transactions and enable certification of green products and energy. This way we can obtain predictive quality, predictive cost, predictive supply and predictive maintenance, and to enable information sharing across the supply and value chain and across production plants.

Internet of things & Industry 4.0

Current technological advances in communication, connectivity, computing and artificial intelligence lead to future industrial plants where equipment is augmented with sensors and wireless connectivity. It’s linked to a system that can visualise the entire production, control it, and make decisions on its own.

This is the concept of Industry 4.0, that includes aspects such as smart manufacturing, smart factories and the industrial internet of things.

Topics and activities

Main topics are:

Artificial intelligence, with applications for advanced process control (project INSPEC)
Predictive maintenance (project ERGO)
Applied and fundamental research (project Internet of Food and AIDA)
Technology scouting for multiple applications
Building chains of sensors, data analysis and visualisation (project Measurements4Management).

The consortium consists of 25 partners and is linked with multiple networks on digitalisation, like the Dutch AI Coalition. Together we work on enabling the Netherlands to be part of the front runners in Europe in the field of knowledge and application of AI.

Join us

We are always open for new ideas, suggestions and partners to start new innovation or coordination and support actions.

Latest news

Digital innovation: obstacles and possible adoptions

Digitalisation offers endless opportunities for the process industry to overcome challenges in sustainability and efficiency. What are the barriers and possible adoptions?

Tested: platforms calculating the benefits from recycling waste heat and cold

During a hands-on workshop participants were able to test platforms, developed by the EU funded projects EMB3Rs and R-ACES, that help reusing excess thermal energy.

January 30, 2023

“Behavioral change requires a reliable outlook for the future”

John Harinck shares his outlook on the future's sustainable value chains. How can we effectively change behaviour? And what does the industry need?

October 25, 2022

Electrification requires adaptability and flexibility

Electrification is the best way to reach sustainability goals. Yet, solar and wind energies are fickle and their output changes regularly.

October 4, 2022

Samotics: solving costly problems around power loss

How to apply artificial intelligence to save energy and raise safety & reliability? Our partner Samotics tells us how it's done.

September 26, 2022

The impact of artificial intelligence (AI) in the sustainability of the steel industry

Utrecht University is studying the impact of digitalization and artificial intelligence (AI) in the sustainability of the steel industry.

September 6, 2022

HAI smart4industries: “The best results come from cooperation”

HAI cooperates with ISPT in the Engineering for Business Intelligence (EBI) project. CEO Peter de Haer talks about this special collaboration.

August 17, 2022

Groot potentieel voor digital twin in de procesindustrie

Een digital twin in de procestechnologie biedt grote kansen voor verduurzaming en kostenbesparing. Een interview met John Harinck, specialist Industrie 4.0 bij ISPT.

Related projects

AIDA – Accelerate the Integration of Digitalization Acceptation

The AIDA project performs research towards predictive capabilities and integration of digital technologies at the various levels of individual processes.

Measurements 4 Management

The aim of Measurement for Management (M4M) is to develop operational predictive technologies that (1) are transparent and include all available process information, (2) provide predictions of Key Performance Indicators...

GRIP on Drying

This project investigates how inline sensors can help improving product quality and efficiency.

R-ACES – FRamework for Actual Cooperation on Energy on Sites and Parks

R-ACES aims to turn high-potential, high-impact industrial clusters into eco-regions with at least 10% reduction in emissions in smart energy.

IMPROVISE – Improved process operation via rigorous simulation models

Improved daily operations of important chemical processes in the Dutch chemical industry through operation technology based on detailed physical models. Incentive Being able to anticipate what a chemical process is...

The Heat Is On

The Heat is On aims to make processes for dewatering, drying and heat integration more efficient.

Smart Maintenance Skillslab

In a Smart Maintenance Skillslab industry and educational institutions can collaborate on new forms of education to solve shortage on the labor market.

SAAI – Social Acceptance of AI in Industry

The SAAI project focuses on accelerating the implementation of Artificial Intelligence (AI) in industry, leading to an energy use reduction of 5-40%, an increased competitiveness of industry, and increased economic...

WeCare – We Create Awareness & Reduce Energy

The WeCARE project demonstrated the possibilities of Artificial Intelligence technology of EnergQ at a selected number of end users. EnerGQ’s self-learning energy management technology unveiled the excessive energy consumption and with that...

EBI – Engineering Business Intelligence

The EBI project uses data collection, data analytics and data visualization to reduce energy usage in existing processes by 5-25%.

ERGO – Energy Reduction by Condition-based Monitoring

Using SAM4 to detect energy-inefficiencies and realize energy reduction. Semiotic Labs’ SAM4 provides a novel and unique approach to condition monitoring for critical AC motors and rotating equipment such as...

IoF – Internet of Food

The Internet of Food (IoF) project defines the sharing of data and models in order to improve sensing systems in food production.

INSPEC – Integrating sensor based process monitoring and advanced process control

INSPEC quantitatively integrates information from state-of-the-art Process Analytical Technology, process measurements and dynamic process models (data driven or physics-based) into Advanced Process Control. This will induce a step-change with respect to...