Research & industry transfer
The IPEM Chair at the University of Siegen sees itself as a reliable and competent partner and service provider for the manufacturing industry with the aim of driving forward the digital transformation in South Westphalia and beyond. To this end, we offer you the opportunity to collaborate directly in individual planning and consulting projects as well as in publicly funded research projects. We contribute our expertise in a targeted manner to the joint development of solutions. To ensure that the manufacturing industry can also regularly participate in the latest research developments, there is also the opportunity to actively participate in one of our working groups. The Best Practice Circle Production and the Innovation Circle: Digital Business Models create a platform for intensive exchange, content-related impulses, the discussion of selected issues and the network for further cooperation. We also offer a wide range of training courses to prepare you and your employees for the challenges of tomorrow.
You can find more information on the SDFS website.
Publications
Current publications
From human to machine: high-impact tasks for AI in production management – an expert study to reshape decision-making
From human to machine: high-impact tasks for AI in production management – an expert study to reshape decision-making
A design concept for data-driven brewing: sensor-based system architecture and ML applications for sustainability in micro-breweries
A design concept for data-driven brewing: sensor-based system architecture and ML applications for sustainability in micro-breweries
From human to machine: high-impact tasks for AI in production management - an expert study to reshape decision-making
From human to machine: high-impact tasks for AI in production management - an expert study to reshape decision-making
Effects of AI explanations on trust and reliance: a study in job shop scheduling
Effects of AI explanations on trust and reliance: a study in job shop scheduling
Improve Quality Control with Predictive Analytics: Using Machine Learning and IO-Link Sensors for Early Detection of Defects in Modern Production
Improve Quality Control with Predictive Analytics: Using Machine Learning and IO-Link Sensors for Early Detection of Defects in Modern Production
Improve Quality Control with Predictive Analytics: Using Machine Learning and IO-Link Sensors for Early Detection of Defects in Modern Production
Improve Quality Control with Predictive Analytics: Using Machine Learning and IO-Link Sensors for Early Detection of Defects in Modern Production
Human-AI Collaboration in Production Management
Human-AI Collaboration in Production Management
A design concept for data-driven brewing: sensor-based system architecture and ML applications for sustainability in micro-breweries
A design concept for data-driven brewing: sensor-based system architecture and ML applications for sustainability in micro-breweries
Effects of AI explanations on trust and reliance: a study in job shop scheduling
Effects of AI explanations on trust and reliance: a study in job shop scheduling
Bridging human expertise and machine learning in production management: a case study on ML-based decision support systems to prevent missing parts at assembly
Bridging human expertise and machine learning in production management: a case study on ML-based decision support systems to prevent missing parts at assembly
Hybrid intelligence – systematic approach and framework to determine the level of Human-AI collaboration for production management use cases
Hybrid intelligence – systematic approach and framework to determine the level of Human-AI collaboration for production management use cases
A systematic review of machine learning for hybrid intelligence in production management
A systematic review of machine learning for hybrid intelligence in production management