Automated manufacturing systems (AMSs) may be defined as discrete production systems in which the handled materials are discrete entities, e.g. parts that are processed or assembled. As a result, AMSs can be effectively represented as discrete event systems (DESs) whose dynamics depends on the interaction of asynchronous discrete events, such as the arrival or departure of parts or products in a buffer, the start of an operation, the completion of a task and the failure of a machine. Petri nets (PNs) are one of the DES formalisms that most effectively allow to model AMSs, thanks to a series of key features: they are both a graphical and a mathematical formalism; they provide a compact and modular representation of large and complex systems; they allow to explicitly represent the notion of concurrency, namely activities that can be performed in parallel; the state is a vector that allows to solve a variety of problems using integer programming; finally, they allow to deal with systems having an infinite state space.

Several classes of PN models have been defined in the literature in the last decades, including Place/Transition nets, timed PNs, continuous PNs, hybrid PNs, colored PNs, fuzzy PNs, and so on. All such classes revealed particularly suited for the solution of relevant problems in AMSs, such as modeling, simulation, deadlock analysis, supervisory control, performance analysis and optimization, as well as problems related to the partial observability of the system state, in particular, fault diagnosis and diagnosability analysis, both in a centralized and in a decentralized framework.

The goal of this talk is twofold. First, a survey of the most significant contributions in this framework is provided. Then, future trends and open issues are discussed.

Carla Seatzu received her Ph.D. degree in Electronic and Computer Engineering from the University of Cagliari, Italy in 2000. Since 2011 she is Associate Professor of Automatic Control at the Department of Electrical and Electronic Engineering of the University of Cagliari, which she joined in 2002 as an Assistant Professor. In 2013 she got the Italian National Abilitation to Full Professor of Automatic Control. She is Coordinator of the B.Sc. Degree in Electrical, Electronic and Computer Engineering and Vice-Coordinator of the Ph.D. Program in Electronic and Computer Engineering at the University of Cagliari. In 2015-2018 she was Vice-President of the Faculty Committee of Engineering and Architecture.

Carla Seatzu’s research interests include discrete-event systems, Petri nets, hybrid systems, networked control systems, manufacturing and transportation systems. She is author of over 230 publications, including 70 papers in international journals and one textbook. She is editor of two international books and the proceedings of two international conferences. Her h-index in Scopus is equal to 30.

Currently she is Senior Editor of one international journal: IEEE Control Systems Letters, and Associate Editor of 2 international journals: IEEE Trans. on Automatic Control and Discrete Event Dynamic Systems. She has also been Associate Editor for: IEEE Trans. on Automation Science and Engineering (2015-2017) and Nonlinear Analysis – Hybrid Systems (2007-2016). She actively collaborated to the organization of several international events: she was Program Chair of the 23rd IEEE Int. Conf. on Emerging Technologies and Factory Automation (2018), Workshop Chair of the 55th IEEE Conf. on Decision and Control (2016) and General Co-chair of the 18th IEEE Int. Conf. on Emerging Technologies and Factory Automation (2013). Since 2017 she is Senior Editor of the IEEE Conf. on Automation Science and Engineering.

She is Vice Co-chair of the IFAC Technical Committee of Discrete Event and Hybrid Systems and Co-Chair of the IEEE Industrial Electronic Society – Technical Subcommittee on Industrial Automated Systems and Control.

She has been visiting professor in several foreign universities in Spain (Zaragoza), USA (Atlanta), Mexico (Guadalajara), and China (Xi’an, Hangzhou).

Industrial automation has progressed for more than one century. A factory / an industrial plant is traditionally a physical location where things are made, row material evolves and value is created, but the digitization of industry is transforming it into something much more: A collection of skills, abilities, and systems that get smarter over time, thereby enabling businesses to innovate what, how, who, and where manufacturing gets done. The automation systems, typically performing precisely defined instructions within a limited scope of operation, will now act “autonomously“ [1] on a more complex level, encompassing also what is not known or foreseen. This transition will unlock greater value by improving productivity and increasing efficiency. The shift will happen over a period of time where we will face various challenging problems, technical as well as societal, to be solved. In this talk we will share our (ABB’s) experiences and learnings from this extremely exciting transformation.

[1]- David P. Watson and David H. Scheidt, Autonomous Systems, Johns Hopkins APL Technical Digest, Volume 26, Number 4, p. 368-376 (2005).

Shiva Sander Tavallaey received a MSc in Mechanical Engineering 1988 from Chalmers University of Technology (CTH) and a PhD in Sound and Vibration/ Technical Acoustics in 2000 from Royal Institute of Technology (KTH), Sweden. After graduating as MSc, she started at Volvo Car AB as Senior designer, where she among the others initiated an R&D project in collaboration with Royal Institute of Technology (KTH) which in turn lead to her increased interest in the field of wave propagation in different media as well as signal processing.

In January 2001 she joined ABB Corporate Research in Västerås, Sweden. After a specialist career within condition monitoring and diagnostics, culminating in an appointment to Principal Scientist in 2009, she started in a management position leading a team of 15-20 specialists in modeling and control of industrial automation applications. During this period, she continued working with different applications and projects applying state of the art approaches such as AI/ ML for anomaly detection, predictive and prescriptive maintenance. In 2015, she was appointed as Adjunct professor at Royal Institute of Technology (KTH) in the department of Vehicle Engineering, at Marcus Wallenberg Laboratory of sound and vibration. In February 2018 she stepped off the management team to follow the specialist career. She was appointed in May 2018 as Senior Principal Scientist in Applied Analytics. She is since March 2018 appointed as AI-Lead in Sweden coordinating the AI-related activities in ABB Sweden.