The increasing variability in modern manufacturing, particularly in High-Mix Low-Volume (HMLV) production, demands flexible, adaptable and sustainable automation solutions. This Research Topic focuses on advancements in adaptive robotic process automation that enable fast, flexible, and efficient setups. Key themes include challenges like rapid robot deployment, process knowledge transfer across diverse products and scenarios, and the automation of complex tasks.

Central to this topic is the development of intuitive Programming by Demonstration (PbD) techniques, which simplify robot programming and minimize reliance on specialized expertise. PbD facilitates the seamless integration of robots into HMLV workflows, especially for small and medium enterprises. Complementing PbD, knowledge transfer methods empower robots to adapt processes such as surface processing (e.g., polishing, gluing, painting) and (dis)-assembly tasks (e.g., (un)-screwing, manipulation, grasping, fastening, cutting) to different products with similar geometrical features, including furniture, molds, battery cells, and automotive parts. These innovations are vital for managing variability in geometries, materials, and production scenarios.

This Research Topic also addresses variability in operational contexts, such as handling deviations in product orientations or tool configurations. Example applications include adaptive grasping and manipulation of diverse printed circuit boards, polishing of diverse washbasin molds with variations in topology etc. Contributions are encouraged on these and related areas, emphasizing interdisciplinary approaches that combine robotics, artificial intelligence, and sustainable practices (social, economic, and/or environmental) to advance adaptive automation and drive innovation in HMLV production environments.

Key objectives include:
1. Simplified Programming by Demonstration (PbD): Enabling intuitive robot programming for diverse tasks, reducing the skill barrier for automation setup.
2. Knowledge Transfer for Diversity in Products and Situations: Exploring methods for transferring robotic process knowledge to different yet similar products and manufacturing environments.
3. Automatic Process Planning: Advancing computational tools for the rapid design and deployment of specific robotic tasks tailored to complex geometries and product requirements.

This research topic invites contributions addressing the following themes (but is not limited to):

1. Process Knowledge Transfer to Different Products with Similar Features and Geometry
• Techniques for transferring robotic knowledge to tasks like:
i. Surface Processing: Polishing, painting, oiling (applications in furniture, molds, battery macro cells, automotive, and aerospace industries).
ii. Grasping and Manipulation: Handling similar products (e.g., printed circuit boards, battery macro cells) with variations in configurations.
iii. Assembly and Disassembly Tasks: Screwing, unscrewing, cutting, gluing for variable products.

2. Fast (Re)-Configuration of Robot Based Process Towards Flexible Automation
• Rapid robot setup in flexible manufacturing environments.
• Handling deviations in product geometry, orientations or tool configurations.
• Adapting to environmental variability, such as changes in workpiece or tool positions, deviations in expected human behaviors in interactive processes, etc.

3. Sustainable Automation: Social, Economic, and/or Environmental (at least one)
• Leveraging human-in-the-loop paradigm for social inclusion in manufacturing.
• Avoid robot reprogramming for product deviations, fast setup, optimized cycle time, etc., offering economic benefits.
• Environmentally friendly applications, eco-friendly manufacturing etc.

Are you interested in contributing a manuscript to this Research Topic?

Flexible and Sustainable Robotic Process Automation for High-Mix Low-Volume Production

Topic Coordinator