Industry dependence on data-driven decision-making is increasing. Predictive models play a vital role in creating process resilience, sustainability, and efficiency. However, a shared and mutually trusted framework for managing and maintaining digital predictive models is still missing. The CareFree Models project provides a solution by introducing a more efficient and automated approach to model development and maintenance.
In short:
- Automated and adaptive process model management – The project develops a framework that enables predictive models to maintain themselves, adapt to changing conditions, and transfer seamlessly to new processes.
- A more efficient and sustainable industry – By reducing manual interventions and improving predictive accuracy, resources such as raw materials, energy, and time are used more efficiently, leading to less waste and lower costs.
- An accessible and scalable Industry 4.0 framework – The project establishes a standard for managing digital infrastructures that can be easily implemented across industries such as food, chemicals, and circular economy sectors.
- A major impact on industrial decision-making – Reliable, up-to-date predictive models improve real-time decision-making, resulting in better product quality, increased efficiency, and a more resilient production environment.
The challenge
The industry faces daily challenges due to the degradation of models within the digital infrastructure. Maintaining these models requires considerable resources, such as labor, numerous process samples, and comprehensive measurements. Without regular maintenance, model prediction declines, leading to suboptimal decision-making that harms both sustainability and economic performance.
This results in several challenges:
- Deteriorating model performance. Sensors can drift, maintenance is required, and factors such as mechanical wear and fluctuating raw materials impact model accuracy.
- High maintenance costs and reactive management. Manually updating and recalibrating models is time-consuming and often done too late to retain optimal performance.
- Adaptation and transfer difficulties. Models need to adjust to new conditions (such as different product formulations or suppliers), increasing complexity and costs. Additionally, existing models are often not efficiently reused, leading to unnecessary extra work when setting up new process lines or facilities.
CareFree Models: a predictive framework
The goal of the CareFree Models project is to develop an automated and predictive framework that integrates the maintenance, adaptation, and transfer of process models. This framework enhances the accessibility and value of Industry 4.0 by making processes more efficient, cost-effective, and sustainable.
The project focuses on:
- Developing a framework to onboard, deploy, monitor and evaluate CareFree Models at industrial end-users, substantiated in the selected cases and sharing best practices within a broad process industry community.
- Creating a broad portfolio of industrial case studies to test process models for their maintenance, adaptation, and transfer capabilities.
- Developing new methods to automatically update predictive models, adapt them to systematic changes and transfer them to new processes in a cost-effective and valuable way.
Project results will include
- Maintenance, adaptation, and transfer of new and existing predictive models, implemented at industrial environment as valuable case-studies for the CareFree Model framework in food, chemical and circular industry.
- Innovative digital tools for better model development, monitoring, and maintenance in an integrated framework, stand-alone and/or implemented in existing software platforms.
- Guidance to the broader process Industry via dissemination with best practices on the deployment, required resources and obtained process value for the CFM framework.
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Let’s get in touch
Anne van der Zwaan
Also in our team
Gerjen Tinnevelt
Mickey Lukkien
Acknowledgement & partners
This work is an Institute for Sustainable Process Technology (ISPT) project, i.e. CareFree Models (CFM - Project number: I40-DA-03). Partners in this project are KraftHeinz - Teijin Aramid - Avri/Cirtex - Cosun - Chemometric Brain - Fuqon - Radboud University - TU Eindhoven and ISPT. This project is co-funded by TKI-Energy with the supplementary grant 'TKI- Toeslag' for Topconsortia for Knowledge and Innovation (TKI’s) of the Ministry of Economic Affairs and Climate Policy
