The well-known British-Dutch transnational company, Unilever, delivers consumer goods to 2.5 billion people in 190 countries around the globe. More than 150 thousands Unilever employees are working their best everyday to achieve their world changing purpose, to make sustainable living commonplace.
One of the focuses of Unilever in the path towards becoming more sustainable is to decrease packaging waste by making the packaging smarter and more efficient.
Unilever makes use of a machine learning based solution for modelling the packaging process.
T-Mobile Netherlands (TMNL), is a leading telecom provider in the Netherlands with an annual growth of 5% in the number of clients. TMNL currently serves more than 6 million mobile subscribers, using more than 6 thousands antenna bases installed around the country. When it comes to customer satisfaction, TMNL has been the top one in the Netherlands for several years in a row.
TMNL upgrades the capacity of the access network every year to assure a high quality of the network and to achieve an even higher customer satisfaction rate while limiting the unnecessary expenses.
Celsian Glass & Solar B.V. is a leading glass operations consultancy company. They spin out of TNO Glass Group, built on multiple years of high precision glass moulding at Royal Dutch Philips.
Glass manufacturers use the Celsian modelling software to optimize their glass melting processes. When a furnace is designed and deployed, most settings go precisely according to the process program. However, subtle changes in the glass production process lead to quality issues such as blisters in the eventual product which for example in case of bottles can cause them to burst later in the filling process.
AkzoNobel is a well-known Dutch multinational company in chemical industry. They provide high quality paints and performance coatings for thousands of paint distributors across the globe and large retail outlets such as B&Q, Leroy Merlin and OBI.
For creating new paintings and updating the components in their existing productions, they use chemical and physical models to predict important characteristics of candidate formulas before performing expensive tests on them which requires lengthy manual iterations on ingredient concentrations to meet the specifications desired.