PLASS

Platform for analytic supply chain management services

Application industry: Production, process industry, logistics, transport and traffic
Technology area: Machine learning, semantic technologies, data and service management, blockchain/distributed ledger technology

PLASS is creating the basis for a better supply chain management. The platform is using AI-based analysis of multilingual raw data to provide information about technologies and their suppliers and is helping manufacturing companies optimize their supply chain.

The baseline
Trust in the functioning and high-quality, stable supply chains is essential for the densely interconnected and globally active economy. If confidence in suppliers declines, costs rise, for example, because storage capacities must be taken into account. If I do not buy the right technologies, I will fall behind the competition.
Typical questions manufacturing companies ask themselves therefore are: Who supplies what? What information is available about a supplier? Which suppliers are suitable for technology? What opportunities and what risks are there for technologies or their suppliers? If a company recognises in good time that a supplier is failing, can it switch to another supplier and thus save costs for storage and logistics? Experts assume that production costs can be reduced by 5 to 10 percent in this manner.

The project goal
PLASS is using methods and models of artificial intelligence (AI) to optimize supply chains (supply chain management). The goal of the project is to develop a B2B platform that supports companies in making decisions and weighing risks concerning their suppliers. The solution filters machine-readable knowledge about suppliers, alternative suppliers, products, and technologies from global and multilingual sources. AI-based analysis of this data enables opportunities and risks to be identified, for example, alternative suppliers of technology. In the so-called human-in-the-loop approach, the system is supported by humans in situations that are not yet known. This concept enables the system to learn continuously. Distributed ledger technology additionally ensures that the information is always traceable.

Application and practical benefit
Both the manufacturing industry and suppliers, in particular ‘fast’ start-ups or small and medium-sized enterprises, will benefit from the solution. As PLASS users, manufacturing companies can use the PLASS ‘Microservices’ to quickly adapt their supply chain.

Term: 1 July 2019 to 30 June 2022

PLASS is a joint German-Austrian project.

Consortium: Siemens AG (lead member), DFKI GmbH, Ubermetrics Technologies GmbH, Institute for Applied Computer Science e. V., Beuth University of Applied Sciences Berlin

Contact:
Mark Buckley
Siemens AG

E-Mail: mark.buckley@siemens.com

Website: www.plass.io