Enhancing Process Efficiency through Process Mining in a Smart factory

The aim of this project is to understand and test how process mining techniques improve process efficiency and quality control in a vertically integrated small production line. To this end, the potential benefits of applying process mining techniques are explored and the impact of the application evaluated. At all phases, data, including event logs and sensor data, are collected for process mining analysis using Celonis software. Collaboration between academia and industry ensures practical application of research findings, facilitates knowledge transfer, and promotes innovation. Among the benefits of using digital tools to leverage the capabilities of smart factory systems and analyze process data is that companies can gain insights to optimize their operations and achieve higher levels of productivity, efficiency, and quality.

Industry 4.0 and Beckn protocol

The project “Industry 4.0 with Beckn” aims to develop flexibility and agility in dynamic environments. By connecting various shop floor systems to the company via the Beckn protocol, it is possible to decouple the supply chain, improve the company’s capacity or make resources and capacities available to others with full data transparency. The goal of this process is for a company to purchase, produce or sell goods more easily and quickly.

Survey on digital maturity assessment in industry

A survey on the degree of digitalization of companies in key areas of digitalization has been designed as part of a digital maturity assessment of the implementation of Industry 4.0 in companies. This survey has an international scope to compare the current situation in Germany and other countries.

Operational Excellence Strategies through Industry 4.0 and Lean Six Sigma

This project explores the possible integration of Industry 4.0 technologies and Lean Six Sigma tools and principles to achieve social and environmental sustainability. Data gathering comes from a vertically integrated production line.

Industry 4.All (planned)

Industry 4.All project aims to establish an infrastructure for testing supply chain technologies under real-world conditions, integrating AI and data-driven approaches in a non-critical environment. A vertically integrated smart factory (web store, ERP system, ME system and CPS) will be used for AI applications and data-driven analytics. This project reviews the current research landscape and explores how AI and data-driven approaches can improve quality assurance and real-time analytics in the supply chain. The project seeks to improve supply chain operations and promote sustainability through the transfer of science and new technologies. This smart factory is not just limited to automation and data integration, but also focuses on creating an easy-to-understand environment for all users. In addition, it serves as a test base for different Industry 4.0 use cases. By adopting the principles of Industry 4.0, the aim is to break down the barriers that limit companies in moving towards a digital transformation.