IndTech Industrial Technology Graduate School

Swedish industrial production is currently undergoing a fundamental technological shift stemming from industry-wide digitalization of products, services and production processes. From a technological perspective, the core of the ongoing shift is the broad digitalization and connectiveness of industry through the development and widespread deployment of new technological areas such as artificial intelligence and Industrial Internet of Things. Although likely of a transient nature, the Covid-19 epidemy of 2020 have accelerated this shift. The term "IndTech" refers to modern digitalization solutions in industry, using core technologies from IoT, machine learning and optimization. Deployment using accessible devices (such as smartphones) while still considering past investments and experiences, industrial requirements integration with existing production systems and IT infrastructure provides fundamental challenges for the manufacturing industry of tomorrow . This distinguishes IndTech from consumer technology, and puts a strong emphasis on production and manufacturing know-how as well as industrial requirements for security and availability, while providing the simplicity and ease-of-use as is available today in the consumer market.

The deployment of such transformative industrial digital technologies in manufacturing and process industries is the core focus of the INDTECH industrial graduate school. Today, IndTech solutions marketed by international manufacturing companies based in Sweden are world-leading, and the area is therefore strategically important on a national level. Furthermore, the potential of the IndTech area is huge with productivity increases up to 30%. However, according to the World Economic Forum, at least half of all employees in industry are in need of upskilling and reskilling to be able to use the potential of digitalization, and already in 2022 it is predicted that 42% of core skills required to perform existing jobs will change. This strong need has furthermore also been expressed by the participating 14 industrial partners and have formed the core content and plan for the graduate school. In the rest of the document, we use the term INDTECH for the planned industrial graduate school.

[Show all publications]

Artificial Intelligence Techniques in System Testing (Jul 2023)
Michael Felderer , Eduard Paul Enoiu, Sahar Tahvili
Optimising the Software Development Process with Artificial Intelligence (Springer)

Time Series Anomaly Detection using Convolutional Neural Networks in the Manufacturing Process (May 2023)
Cristina Landin, Jie Liu , Sahar Tahvili
The 5th IEEE International Conference on Artificial Intelligence Testing (AITEST 2023) (AITest 2023)

Dynamic Maps Requirements for Autonomous Navigation on Construction Sites (Dec 2022)
Philip Wickberg, Anas Fattouh, Sara Afshar, Johan Sjöberg , Markus Bohlin
The 5th International Conference on Communications, Signal Processing, and their Applications (ICCSPA’22)

Artificial Intelligence Methods for Optimization of the Software Testing Process With Practical Examples and Exercises (Jul 2022)
Sahar Tahvili, Leo Hatvani

Mapping simulation optimization requirements for construction sites: A study in the heavy-duty vehicles industry
Abdulkarim Habbab, Anas Fattouh, Bobbie Frank , Koteshwar Chirumalla, Markus Bohlin
64th International Conference of Scandinavian Simulation Society (SIMS 2023)

Adopting a Digital Twin Framework for Autonomous Machine Operation at Construction Sites
Philip Wickberg, Anas Fattouh, Sara Afshar, Markus Bohlin
The 7th CAA International Conference on Vehicular Control and Intelligence (CVCI 2023)