The challenges of engineering future high-tech systems and factories are growing exponentially.
To empower industry to become more socially, environmentally and economically sustainable for everyone, we need to create systems and factories that deliver more throughput, precision, intelligence and interoperability, year over year, while still reducing their negative impact on our world.
An important related trend is the shift by industry from offshoring to onshoring. To shorten supply chains in the West a significant reduction in manual labour costs will be required to remain competitive. Traditional engineering methods fall short in providing future-proof and fitting solutions.
In collaboration with industry partners we will work on innovative and disruptive solutions. Merging AI and engineering disciplines, we will pave the way to designing, servicing and operating future autonomous, zero-waste high-tech systems and factories.
Explainable data-driven decision support
Our world is full of uncertainties.
In inventory management, the uncertainty of demand is one of the main challenges. New technologies, innovations, fast-developing logistics, and international competitions are rapidly changing our lifestyle as well as bringing unprecedented uncertainties to the market demands.
We, confronting this challenge of highly uncertain demands, are not satisfied with using a traditional approach of assuming a certain distribution to deal with the demand uncertainty. The availability of large datasets and the presence of powerful computation capacity facilitate us to explore a new approach to tackle the demand uncertainty.
Our research will inspire companies, scientists, and social scientists to integrate a data-driven approach in inventory management and examining its interaction with human inventory planners.