Supply chain optimisation with mathematical precision

Improvement measures for your supply chain: What works best? 

Resilient, responsive and sustainable - this is how your supply chains should ideally be in order to compete internationally. What specifically can you do to achieve this? What are the right measures to optimise your supply chain?

Scientific calculations provide well-founded answers

"Mathematics twin" without artificial intelligence (AI). Our solution is a digital twin that - unlike usual digital twins - does not work with AI, but with mathematics. The basis for the precise calculations of the effects of internal and external changes in your supply chain is the patented X-ACT algorithm - with its roots in science: X-ACT was developed in the 1970s as part of a NASA project and has been perfected in hundreds of practical applications. 

Description of your entire supply chain without measurement data 

No collecting, collating and interpreting historical data. The "mathematics twin" provides a complete, descriptive digital image of a system, i.e. your supply chain. The only information we need from you for this are parameters of your infrastructure, e.g. number and type of transport vehicles. However, X-ACT already "knows" how a 40-tonne lorry, for example, behaves in terms of CO2 emissions. This statistical data, like countless others, is contained in X-ACT's database of 20,000 libraries. 

Fast problem solving - first results in a few weeks

"Running through" new scenarios instead of analysing old data. Once the "mathematics twin" has been created, various possible scenarios, e.g. the use of hydrogen instead of diesel lorries, are entered into the model as changes and the results are emulated. In contrast to AI-based twins, X-ACT does not evaluate historical data, but calculates the dependencies and interactions - within a very short time. The first results are already available after a few weeks.

Mathematics: better than artificial intelligence

Apart from speed, X-ACT offers a number of other advantages over AI-based solutions. Two key advantages are:

1. Precise forecasts. X-ACT delivers highly accurate results compared to AI. This is because it is calculated in advance instead of analysed retrospectively, as is the case with AI, under the assumption that the future will behave in exactly the same way.
2. Boundless complexity. X-ACT is able to map complexity without restrictions. With currently around 3.6 billion variables, any number of dependencies can be modelled. AI, on the other hand, is only capable of calculations in the range of several 1,000 data points.