Artificial Intelligence changes supply chain management

The world has been moving towards a digital future over the years and Industry 4.0 technologies are considered to be the way of the future. One of the most prominent of these technologies (including blockchain, IoT, cloud computing, etc.) is artificial intelligence (AI).

In the age of information technology and increasingly complex technical and industrial processes, agile and efficient logistics processes play a central role. High logistic requirements such as reliability, transparency and flexibility combined with optimal economic conditions, form the foundation for a successful supply chain (SC). Dynamically changing processes require a technology that is able to cope with the increasing complexity of supply chain management. Using AI leads to problem-solving with higher accuracy, higher speed and a larger amount of inputs. AI is neither a new subject nor a new academic field of study; however, only recently have technological developments shown that AI has a vast set of applications, including supply chain management (SCM) Intelligent decision support using advanced decision technologies and analytics methodologies are of the utmost importance in logistics and SCM. Therefore, ERP systems are at the heart of these changes. For this reason, artificial intelligence is mentioned as one of the top 10 trends changing within ERP systems.

At InfoConsulting to bridge the gap between scientific development in operations research and industrial applications, we have started a R&D project consisting of development and implementation of a mobile solution for material logistics in manufacturing and trading companies based on artificial intelligence and machine learning technologies. The project is developing an innovative solution allowing for the modelling and simulation of logistics processes as well as the implementation, automation and optimization of material logistics processes. We are consulting our ideas with AGH University of Science and Technology in Krakow, one of the largest technical universities in Poland. The solution will work using communication from mobile devices and will communicate with typical ERP systems. We have used a metaheuristic optimization algorithm from the field of computational intelligence.

The solution will provide a predefined set of optimization algorithms for tasks in logistics processes, process patterns and a low code development technology platform. The solution will significantly reduce the operating costs of the material logistics area by optimizing the handling of logistic transactions by personnel and equipment. The developed tool and methodology will allow us to provide services and provide customers with an effective platform for optimization and management of material logistics without performing many months of configuration, building optimization algorithms and building interfaces with ERP systems from scratch.

Ph. D. Katarzyna Grobler-Dębska