Rizos Sakellariou
Jorge Buenabad-Chávez
ABSTRACT
Significant effort is currently being invested on enhancing digitization in all aspects of industrial processes and manufacturing on the quest for the next transformational change towards sustainable manufacturing and the factories of the future. This vision, commonly termed as Industry 4.0, is at the core of a number of funded projects in Europe. This short paper briefly reports experiences from the EU-funded project DISRUPT and focuses on the identification of some key challenges in the interplay between Industry 4.0 and High Performance Computing.
- Big Data Value Association. 2018. Big Data Challenges in Smart Manufacturing. (2018). Discussion paper available from http://www.bdva.eu.Google Scholar
- Rafael Ferreira da Silva, Rosa Filgueira, Ilia Pietri, Ming Jiang, Rizos Sakellariou, and Ewa Deelman. 2017. A characterization of workflow management systems for extreme-scale applications. Future Generation Computer Systems 75 (2017), 228 -- 238. DOI: http://dx.doi.org/Google ScholarCross Ref
- Pavlos Eirinakis, Jorge Buenabad-Chavez, Rosanna Fornasiero, Haluk Gokmen, Julien-Etienne Mascolo, Ioannis Mourtos, Sven Spieckermann, Vasilis Tountopoulos, Frank Werner, and Robert Woitsch. 2017. A Proposal of Decentralised Architecture for Optimised Operations in Manufacturing Ecosystem Collaboration. In Collaboration in a Data-Rich World, Luis M. Camarinha-Matos, Hamideh Afsarmanesh, and Rosanna Fornasiero (Eds.). Springer International Publishing, 128--137.Google Scholar
- Laurence Field and Rizos Sakellariou. 2017. An Evaluation of Information Consistency in Grid Information Systems. Journal of Grid Computing 15, 1 (01 Mar 2017), 127--137. Google ScholarDigital Library
- HPC4Manufacturing. 2018. High Performance Computing for Manufacturing (HPC4Mfg). (2018). https://hpc4mfg.llnl.gov/Google Scholar
- Sachin S. Kamble, Angappa Gunasekaran, and Shradha A. Gawankar. 2018. Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection 117 (2018), 408 -- 425. DOI: http://dx.doi.org/Google ScholarCross Ref
- Evangelia Kavakli, Jorge Buenabad-Chávez, Vasilios Tountopoulos, Pericles Loucopoulos, and Rizos Sakellariou. 2018. WiP: An Architecture for Disruption Management in Smart Manufacturing. In 2018 IEEE International Conference on Smart Computing (SMARTCOMP). 279--281.Google Scholar
- S. Kodiyalam, R.J. Yang, L. Gu, and C.-H. Tho. 2004. Multidisciplinary design optimization of a vehicle system in a scalable, high performance computing environment. Structural and Multidisciplinary Optimization 26, 3 (01 Feb 2004), 256--263. Google ScholarDigital Library
- László Monostori. 2014. Cyber-physical Production Systems: Roots, Expectations and R&D Challenges. Procedia CIRP 17 (2014), 9 -- 13. DOI: http://dx.doi.org/Google ScholarCross Ref
- Saeid Nahavandi, D. Creighton, V. T. Le, M. Johnstone, and J. Zhang. 2015. Future Integrated Factories: A System of Systems Engineering Perspective. Springer International Publishing, Cham, 147--161.Google Scholar
- Anwar Osseyran and Merle Giles. 2015. Industrial applications of high-performance computing: best global practices. Vol. 25. CRC Press. Google ScholarDigital Library
- Daniel A. Reed and Jack Dongarra. 2015. Exascale Computing and Big Data. Commun. ACM 58, 7 (June 2015), 56--68. Google ScholarDigital Library
- Frank Werner and Robert Woitsch. 2018. Data Processing in Industrie 4.0. Datenbank-Spektrum 18, 1 (01 Mar 2018), 15--25.Google Scholar
- Li Da Xu, Wu He, and Shancang Li. 2014. Internet of Things in Industries: A Survey. IEEE Transactions on Industrial Informatics 10, 4 (Nov 2014), 2233--2243.Google ScholarCross Ref
Index Terms
- High performance computing and industry 4.0: experiences from the DISRUPT project
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