Data Analytics for Fault Detection in District Heating (DAD)

The purpose of this project is to, together with industry partners, apply, improve and develop new methods and algorithms for predictive data analytics in order to increase energy efficiency in heating systems via fault monitoring, detection and prediction activities.

Computational modelling for improved pretreatment of waste for ethanol and biogas production

The goal of this project is to use computational methods to identify and understand the chemistry that governs the decomposition of waste materials. Initial focus will be on lignocellulosic materials that can be found in, for example, paper tubes and cotton-based wastes. In the longer term these studies will be extended to keratin containing materials that can be found in, for example, feathers. These computational studies will be performed in close collaboration with current experimental work at the School of Engineering that uses these materials. This will allow for knowledge-based (instead of resource intensive) improvement of the decomposition of waste materials that can then be used for more efficient production of, for example, renewable energy.

Data-driven service development: advanced training for professionals

The ability to use data has become the most important success factor in terms of increased growth. With background in, among other things, the trends that show that companies increasingly want to use data to develop new services and business models, the project Data-driven service development at the University of Borås is being run. With the increased opportunities in data-driven service development, there are also some challenges, such as lack of appropriate digital solutions, problems with data availability, lack of confidence in data but also insufficient competence regarding advanced data analysis. In other words, data-driven service development is not only a technical challenge but also an organizational challenge, which is shared by many companies.

Computer based modeling for improved protein-based superabsorbents from waste

One of the main aims of the Waste Refinery Excellence Center is to produce new useful materials from waste. One example is zygomycetes fungi that can produce a variety of products when degrading lignocellulose, except fuel compounds also chitosan and protein materials which can be act as superabsorbents can be produced. The aim of this project is to model the protein superabsorbents produced and to propose treatments of the material to enhance the absorbing properties.

CelluTex Cellulose-based textile

The aim with the project: Financing influencing activities for the partners in the Swedish advocacy platform "CelluTex Cellulose based textiles".

Preventing multi-resistant bacteria by nanoparticle-enzyme printed medical textiles

Infections by bacteria that cannot be treated with common medicines are increasing (multi-resistant bacteria). This problem can be solved by making the treatment area safer; through antibacterial sheets, curtains and other textiles.

Circular and climate optimized concrete element for new construction

DESTEX

COST Action A32

Open Scholarly Communities on the Web

Automation and AI application in SME

Introduction and Background: The current industrial landscape grapples with inflexible processes, limited innovation, and declining profit margins, necessitating a transformative shift. Industry 4.0 emerges as a beacon of change, offering advanced solutions such as big data analysis, autonomous robots, and the Internet of Things (IoT). However, the widespread adoption of these technologies, especially among Small and Medium-sized Enterprises (SMEs), faces hurdles like technical expertise gaps and organizational complexities. Purpose of the Project: In response to the challenges faced by SMEs, this project is dedicated to leveraging artificial intelligence (AI) to revolutionize automation and manufacturing processes.