Fraunhofer Institute's solution to no more supply chain disruptions

Even before the pandemic challenged the validity of current supply chain models, there was talk of predictive analytics, of the need to move from simple Excel inventory to beyond-scope tools that combine market demand with inventory availability, with the goal of predicting the right actions based on order forecasts. All of this now makes you realize how important it is for the supply chain, it's not enough to adequately intercept demand, but you have to think about the broader situation. The wider the supply chain, the more complex it becomes, and it is interconnected with countless variables, even outside of logistics itself. A recent example emerged in the U.K. when supply chain problems occurred, supermarket shelves were empty and gas stations dried up.

ITWM's research at the Fraunhofer Institute for Industrial Mathematics focuses precisely on minimizing risk in supply chains, which has led to software that can provide mathematical answers to global supply chain problems.

Elastic Algorithm

Fortunately, even the most complex scenarios can be traced back to a set of mathematical models: researchers at the Fraunhofer Institute have done just that, analyzing the characteristics of the supply chain and simulating them with models. Therefore, any negative situations are predictable and, above all, analyzable: the main purpose of the software is precisely to highlight the critical points of the system, those that require more intervention. By grouping all the variables in the optimization of a problem according to multiple criteria, the researchers have developed a method to determine the best solution that combines resilience, cost and risk.

Overall Optimization

The challenge of this mathematical model is to optimize the supply chain through a holistic approach. The software algorithm calculates the optimal balance between the different input channels on which the supply chain relies (e.g., raw materials, suppliers, and storage) without neglecting the selection of alternative materials. The root of clarifying system weaknesses is to remove all unnecessary things and assume only those variables that are truly indispensable.

Preventing bottlenecks

Another branch of the Fraunhofer Institute, specializing in material flow and logistics (IML), has developed in parallel a simulator called OTD-NET, Order-To-Delivery-NETwork Simulator. The tool is designed to estimate and evaluate the planning process and material flow from order to delivery. The advantage of OTD-NET is the possibility to map the supply chain at different depths: all possible scenarios can be considered in the simulation, such as peaks in demand, market collapses or production interruptions. The Fraunhofer Institute has been working on these solutions, driven by the problems commonly experienced by the German and European automotive industries during the pandemic. It therefore has the opportunity to develop an additional set of analytical models to predict future demand peaks and their fluctuations.

Possible constraints on regions, order fulfillment capacity, and shipment frequency are just a few of the variables that need to be considered in order to provide companies with a quick feedback system on the risk margins they face and, therefore, the compensation they should take.