TY - CHAP A1 - Miller, Eddi A1 - Schmitt, Anna-Maria A1 - Kaupp, Tobias A1 - Batres, Rafael A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - A Peak Shaving Approach in Manufacturing Combining Machine Learning and Job Shop Scheduling T2 - Lecture Notes in Mechanical Engineering N2 - Computerized Numerical Control (CNC) plays an important role in highly autonomous manufacturing systems with multiple machine tools. The necessary Numerical Control (NC) programs to manufacture the parts are mostly written in standardized G-code. An a priori evaluation of the energy demand of CNC-based machine processes opens up the possibility of scheduling multiple jobs according to balanced energy consumption over a production period. Due to this, we present a combined Machine Learning (ML) and Job-Shop-Scheduling (JSS) approach to evaluate G-code for a CNC-milling process with respect to the energy demand of each G-command. The ML model training data are derived by the Latin hypercube sampling (LHS) method facing the main G-code operations G00, G01, and G02. The resulting energy demand for each job enhances a JSS algorithm to smooth the energy demand for multiple jobs, as peak power consumption needs to be avoided due to its expense. Y1 - 2025 SN - 9783031774287 U6 - https://doi.org/10.1007/978-3-031-77429-4_59 SN - 2195-4356 SP - 535 EP - 543 PB - Springer Nature Switzerland CY - Cham ER - TY - CHAP A1 - Schmitt, Anna-Maria A1 - Miller, Eddi A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - Energy Prediction for CNC Machines Using G-Code Evaluation, Machine Learning and a Real-World Training Part T2 - 2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE) Y1 - 2025 U6 - https://doi.org/10.1109/ICMRE64970.2025.10976308 ER - TY - CHAP A1 - Miller, Eddi A1 - Schmitt, Anna-Maria A1 - Kaupp, Tobias A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - Deep Reinforcement Learning for Adaptive Job Shop Scheduling in Robotic Cells: Handling Disruptions Effectively T2 - 2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE) Y1 - 2025 UR - 10.1109/ICMRE64970.2025.10976238 ER - TY - JOUR A1 - Schirmer, Fabian A1 - Kranz, Philipp A1 - Rose, Chad G. A1 - Schmitt, Jan A1 - Kaupp, Tobias T1 - Towards Dynamic Human–Robot Collaboration: A Holistic Framework for Assembly Planning JF - Electronics N2 - The combination of human cognitive skills and dexterity with the endurance and repeatability of robots is a promising approach to modern assembly. However, efficiently allocating tasks and planning an assembly sequence between humans and robots is a manual, complex, and time-consuming activity. This work presents a framework named “Extract–Enrich–Assess–Plan–Review” that facilitates holistic planning of human–robot assembly processes. The framework automatically Extracts data from heterogeneous sources, Assesses the suitability of each assembly step to be performed by the human or robot, and Plans multiple assembly sequence plans (ASP) according to boundary conditions. Those sequences allow for a dynamic adaptation at runtime and incorporate different human–robot interaction modalities that are Synchronized, Cooperative, or Collaborative. An expert remains in the loop to Enrich the extracted data, and Review the results of the Assess and Plan steps with options to modify the process. To experimentally validate this framework, we compare the achieved degree of automation using three different CAD formats. We also demonstrate and analyze multiple assembly sequence plans that are generated by our system according to process time and the interaction modalities used. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57825 SN - 2079-9292 VL - 14 IS - 1 PB - MDPI ER - TY - CHAP A1 - Kranz, Philipp A1 - Kristhofen, Dennis A1 - Schirmer, Fabian A1 - Rose, Chad G. A1 - Schmitt, Jan A1 - Kaupp, Tobias T1 - Gesture vs. Touch Control for Unforeseen Situations of Human-Robot Collaborative Assembly T2 - 2025 20th ACM/IEEE International Conference on Human-Robot Interaction (HRI) Y1 - 2025 U6 - https://doi.org/10.1109/HRI61500.2025.10974148 SP - 1433 EP - 1437 PB - IEEE ER - TY - CHAP A1 - Schirmer, Fabian A1 - Kranz, Philipp A1 - Rose, Chad G. A1 - Willert, Volker A1 - Schmitt, Jan A1 - Kaupp, Tobias T1 - Utilizing Eye Gaze for Human-Robot Collaborative Assembly T2 - 2025 20th ACM/IEEE International Conference on Human-Robot Interaction (HRI) Y1 - 2025 U6 - https://doi.org/10.1109/HRI61500.2025.10974041 SP - 1603 EP - 1607 PB - IEEE ER - TY - CHAP A1 - Pfeuffer, Katharina A1 - Fischer, Sophie A1 - Schmitt, Jan A1 - Bräutigam, Volker T1 - Human or Robot Resource Management? The Future of Work in the Digital Transformation of Manufactoring Companies T2 - Proceedings of the Conference on Production Systems and Logistics: CPSL 2025 N2 - This article examines the transformative effects of Smart Factory technologies - such as human-robot collaboration, intelligent assistance systems and cyber-physical production systems - on organizational design, with a particular focus on central fields of action for Human Resources management (HRM) and operational management. A case study of a German automotive supplier is used to examine how digitalization and automation are changing human work and organizational structures. Two future scenarios for organizational models are proposed: the swarm organization, which consists exclusively of highly qualified employees while robots take over routine tasks, and the polarized organization, which is characterized by a division between highly qualified specialists and low-skilled employees. Each scenario brings different challenges and opportunities for HR management, as companies need to adapt to digital skills, new models of collaboration and the management of a highly specialized or polarized workforce. This paper provides a conceptual framework and actionable insights for HRM and production management to manage the shift towards advanced, automated organizational models and ensure a smooth transition to the Smart Factory of the future. Y1 - 2025 U6 - https://doi.org/10.15488/18885 PB - publish-Ing. CY - Offenburg ER -