Fabio Fruggiero, Università degli Studi della Basilicata, Italy
Short Bio: Fabio Fruggiero graduated in Mechanical Engineering at the University of Salerno with a dissertation about newly formed meta-heuristics for the industrial scheduling optimisation, 2004. He conducted his PhD in Mechanical Engineering at the University of Salerno - Italy with a dissertation about Digital Factory Application from Manufacturing to Service Environment, 2008.
Formerly, in 2008, He was post PhD student at the Mechanical Engineering Department of the University of Salerno with main topic of research: Operations Management Strategies for HealthCare optimisation.
Currently, he is Associate Professor, and responsible of the area and lab, in Industrial Systems Engineering at the School of Engineering – Mechanical Engineering Area - of the University of Basilicata- Italy. He runs courses for both Industrial System Engineering and Operations Management. Member of the PhD board in “Engineering for Innovation and Industrial Development” at the University of Basilicata.
He works as referee for different International Journals (e.g., IJSOI, IJAMT, IJPR, CPPB, EIS, TPMR, TSMSI, IJEBM, UHSE, Cogent OA etc ...) and the national minister of research. He is editor and editorial member of: Cogent Engineering Journal, Industrial and Systems Engineering, the Ergonomics Open Journal and International, Journal of Engineering Business Management. Member of the Scientific committee for BAA, MESIC, IWAR, CODIT, ISM conference. Editor of SI: “Cloud Manufacturing and Digitalization to Sustain Industrial Efficiency” for Applied Sciences; “Smart Interaction For The 4.0 Domains: Modelling and Simulating the context of Future” for IJSPM; “Industrial Sustainability: Production Systems Design and Optimization across Sustainability” for Sustainability.
Fabio has been engaged in the auto sector for both Human Factor analysis and Ergonomic research, scheduling optimization, production management, predictive maintenance. He has collaboration with firms of the production and service sector applying the results of his work to help multinational companies and SMEs to generate safety and Optimize services and profits.
He is acting as consultant to several major companies and patent initiatives. He is active in initiative for knowledge transfer to industry. His research's activity, reported in several publications in: international journals
and conferences and book chapters, encompassed the area of: Human Factor and Corporate Strategy; Industrial System Design Processes; Additive Manufacturing and Advanced Manufacturing; Simulation and Virtual modelling; Agent Based Modelling; Assembly Line Balancing; HealthCare Management and Clinical Risk Assessment; Scheduling and Optimisation; Safety and Risk analysis.
Title: Cognitive Control in Collaborative Systems
Abstract: The technology driven progress of Industry 4.0 has emphasized the social dimension of the production. Digital technologies, in a service-oriented approach, are adapting to worker’s need in a shadowing
approach. New models for individualized human-machine interaction systems are developing for facing with new challenges. This is forcing a human centric perspective that points on the sustainable resilience of smart operators, i.e., operators with «augmented» collaborative capabilities. Smart operators have to collaborate with automatic devices (fixed and moving resources) in a flexible, reliable, safe, inclusive, metacognitive way. They work on products taking through scheduled paths (typically in assembly process) or, partially, deciding sequence of tasks based on product state (generally in dis-assembly processes) and reaction to system failures/un-suitability.
Here, resources and operators are likely to adopt bi-directional learning strategies based on: stated (common) procedural rules, acquisition of signals and interpretation of intentions, inherent knowledge and construction of intelligence, achievement of results over performances. This is resulting in collaborative systems with superior cognitive capabilities. It mixes the quantitative (physical and stressor) perception with the qualitative (psychological and psychosocial) comprehension of system state.
A cognitive based control in collaborative systems can tackle unexpected situation and/or help to execute/predict complex manipulation. It can be used, especially in remanufacturing context, to unlock Human-Robot synergy and to propose proactive paths.
