Special Sessions/Tracks

Special Session/ Special Track Proposal

Please use the provided template to prepare proposals for special sessions. Please submit your special session proposals to APMS 2020 program committee by February 15, 2020. Please e-mail your proposals to: info@apms-conference.org. (also please cc the conference organizing chair umarjano@uns.ac.rs at on your submission e-mail )

Confirmed Special Sessions/ Tracks

Digital Lean Manufacturing and its Emerging Practices

Description: Digital technologies have given rise to a new era of “digital lean manufacturing” practices, which extends the lean philosophy to the “digital world”. This special track aims to attract papers exploring the new “digital frontier” for lean thinking and its emerging practices in the lean manufacturing domain. In this sense, we define the Digital Lean paradigm as the convergence between the principles and practices of lean thinking and the technology-driven vision of Industry 4.0 in order to support digital transformation initiatives at the shop-floor, combining different digital technologies with lean methods and tools. Furthermore, Digital Lean Manufacturing is defined as a digital lean strategy that builds on new data acquisition, data integration, data processing and data visualization capabilities to create different descriptive, predictive and prescriptive analytics applications to detect, fix, predict and prevent unstable process parameters and/or avoid quality issues inside defined tolerance ranges that may lead to any type of waste within the cyber- and physical- worlds towards higher levels of operational excellence and customer satisfaction1-2. This track welcomes research contributions on, but not limited to, digital waste, cyber-physical waste, digital quality management systems, digital Kanban systems, Jidoka 4.0 systems, digital poka-yokes, etc.

  • Daryl Powell, Norwegian University of Science and Technology, Norway, daryl.j.powell@ntnu.no
  • David Romero, Tecnológico de Monterrey, Mexico, david.romero.diaz@gmail.com
  • Paolo Gaiardelli, University of Bergamo, Italy, paolo.gaiardelli@unibg.it
  • Thorsten Wuest, West Virginia University, USA, thwuest@mail.wvu.edu


Operations Management in Engineer-to-Order Manufacturing

Description: Engineer-To-Order (ETO) is a manufacturing approach where design and engineering activities are included in the order fulfilment process. ETO manufacturing is used when engineering specifications of products are not known in detail upon receipt of customer order, and is common in mechanical industries, construction, shipbuilding, off shore supplier industries, and other types of project-based manufacturing, industries typically facing several unique challenges as the products are often one-of-a-kind and/or highly customized. This track welcomes research contributions on operations management enabling effective ETO manufacturing, including Industry 4.0 technologies, supply chain management, lean operations, planning and control, production strategies and product platforms.

  • Erlend Alfnes, Norwegian University of Science and Technology, Norway, erlend.alfnes@ntnu.no
  • Martin Rudberg, Linköping University, Sweden, martin.rudberg@liu.se


Digital Transformation Approaches in Production Management

Description: Digital Transformation has disrupted every domain of production management, from products design and engineering to innovations in materials, manufacturing processes and production planning and control approaches. Digital Technologies are influencing all aspects of design, engineering and manufacturing at the emerging smart factories under the promise of being able to support manufacturing enterprises with the challenge of mass-customization and personalization demands at a competitive cost compared to the mass-production costs with shortest possible development time and production time. This market challenge requires production systems to change from more labour-intensive processes to information technology-enabled mechatronic processes. This special session aims to attract practice-oriented papers and real case studies trying to answer the questions of (i) What is the reality of digital transformation in today’s manufacturing enterprises? (ii) Which are the approaches, models, technologies and tools used today for their digital transformations? What are the challenges that manufacturing enterprises are facing when digitally transforming their production systems?

  • Bahrudin Hrnjica, Faculty of Technical Sciences, University of Bihac, Bosnia & Herzegovina, bahrudin.hrnjica@unbi.ba
  • Egon Lüftenegger, IT & Business Informatics, CAMPUS 02 University of Applied Sciences, Austria, egon.lueftenegger@campus02.at
  • Ioan Turcin, Automation Technologies, CAMPUS 02 University of Applied Sciences, Austria, ioan.turcin@campus02.at
  • Selver Softic, IT& Business Informatics, CAMPUS 02 University of Applied Sciences, Austria, selver.softic@campus02.at
  • Vlad Bocanet, Faculty of Machine Building, Technical University Cluj-Napoca, Romania, vlad.bocanet@tcm.utcluj.ro


The Future of Lean Thinking and Practice

Description: The session seeks to deepen the academic foundations of lean thinking. In collaboration with IFIP WG5.7 special interest group (SIG) for The Future of Lean Thinking and Practice, we are looking for papers that contribute to our understanding of how to reduce waste, unevenness, and overburden along entire value streams. Areas of interest include lean manufacturing, lean management, lean shop-floor control, lean and green, lean in services, and the role of lean in Industry 4.0. Particularly valuable is research that merges academic rigour with practical applications in industry. Case reports of practical experiences in manufacturing and comparison of manufacturing approaches are also very welcome.

  • Daryl Powell, Norwegian University of Science and Technology, Norway, daryl.j.powell@ntnu.no
  • Torbjørn Netland, ETH Zurich, Switzerland, tnetland@ethz.ch
  • Christoph Roser, Karlsruhe University of Applied Sciences, Germany, christoph.roser@hs-karlsruhe.de


The Operator 4.0: New Physical and Cognitive Evolutionary Paths

Description: According to recent studies on the Future of Work, robotization, automation and digitalization are changing human work through three distinct but related channels: substituting human workers, complementarity with humans, and new tasks creation. The role of operators in Industry 4.0 will most probably undergo through these three evolutionary paths. This special track is focused on technology’s complementarity with humans. This track aims to explore newly available physical and cognitive technological means, from exoskeletons and other types of wearables and support systems to collaborative robots to intelligent personal assistants for supporting and aiding the physical and cognitive work of the emerging Operators 4.0* at the Smart Factories of the Future. In this context, the special track welcomes research contributions on, but not limited to, advanced human-machine interfaces, joint cognitive systems, and human cyber-physical systems aiming at the augmentation of human physical and cognitive capabilities.

*The Operator 4.0 is “a smart and skilled operator who performs not only – ‘cooperative work’ with robots – but also – ‘work aided’ by machines as and if needed – by means of human cyber-physical systems, advanced human-machine interaction technologies and adaptive automation towards “human-automation symbiosis work systems” (Romero et al., 2016).


  • David Romero, Tecnológico de Monterrey, Mexico, dromero@tec.mx, david.romero.diaz@gmail.com
  • Johan Stahre, Chalmers University of Technology, Sweden,  johan.stahre@chalmers.se
  • Eija Kaasinen, VTT, Finland, eija.kaasinen@vtt.fi
  • Thorsten Wuest, West Virginia University, USA, thwuest@mail.wvu.edu
  • Åsa Fasth-Berglund, Chalmers University of Technology, Sweden, asa.fasth@chalmers.se
  • Sarbjeet Singh, Luleå University of Technology, Sweden, sarbjeet.singh@ltu.se


Data-Driven Applications in Smart Manufacturing and Logistics Systems

Description: Recent advancements in technology infrastructure for capturing and managing real-time data are key enablers of smart production systems and are expected to empower companies to adopt data-driven strategies for more responsive, efficient and sustainable manufacturing and logistics systems. This track explores new technological developments in data-driven applications, such as digital twins, for the planning and operation of smart manufacturing and logistics systems. The track welcomes research contributions and case studies on practical experiences implementing and using data-driven applications in smart manufacturing and logistics systems. Discussions on extended benefits concerning sustainability dimensions are welcome.

  • Magnus Wiktorsson, KTH Royal Institute of Technology, Sweden, magwik@kth.se
  • Sang Do Noh, Sungkyunkwan University (SKKU), Republic of Korea, sdnoh@skku.edu

Organized by