Basic research for supporting the realisation of cyber-physical production systems  Page description

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Details of project

 
Identifier
113038
Type K
Principal investigator Monostori, László
Title in Hungarian Kiber-fizikai gyártórendszerek létrehozását támogató alapkutatások
Title in English Basic research for supporting the realisation of cyber-physical production systems
Keywords in Hungarian Kiber-fizikai gyártórendszerek; robusztus ütemezés; elosztott, kooperatív, intelligens irányítás, ember-gép szimbiózis
Keywords in English Cyber-physical production systems; robust scheduling; distributed, cooperative, intelligent control; human-machine symbiosis
Discipline
Material Science and Technology (engineering and metallurgy) (Council of Physical Sciences)65 %
Ortelius classification: Metal technology
Automation and Computer Science (Council of Physical Sciences)35 %
Ortelius classification: Automation
Panel Engineering, Metallurgy, Architecture and Transport Sciences
Department or equivalent Computer and Automation Research Institute HAS
Participants Csáji, Balázs Csanád
Drótos, Márton
Egri, Péter
Erdos, Gábor
Gyulai, Dávid
Horváth, Gergely
Kádár, Botond
Kardos, Csaba
Karnok, Dávid
Kis, Tamás
Kovács, András
Pfeiffer, András
Popovics, Gergely
Váncza, József
Viharos, Zsolt János
Starting date 2015-01-01
Closing date 2019-06-30
Funding (in million HUF) 69.741
FTE (full time equivalent) 21.72
state running project





 

Final report

 
Results in Hungarian
A kutatás megalapozta a kiber-fizikai termelési rendszerek (CPPS) paradigmát, feltárta fő kihívásait és lehetőségeit, és bővítette azt a gyártás biológia transzformációja irányába, tekintettel a fenntarthatóságra is. • Erőforrások kooperatív megosztását támogató együttműködési (crowdsourcing) platform autonóm cégek számára; játék elméleti modellek igények és időbeli erőforrások illesztésre (tarifa optimalizálás). • Robusztus, gyenge feltételek mellett konfidencia halmazokat hatékonyan számító identifikációs és predikciós módszerek dinamikus sztochasztikus rendszerek számára. • Valós és virtuális gyártórendszerek fúziója új érzékelő, gépi tanulási és digitális ikermodellt alkalmazó módszerek integrálásával; ezek alkalmazása részben strukturált környezetben; SmartFactory létesítése. • Ember-robot szimbiózis megvalósítása mechanikus szerelésben, tervezés, off-line programozás, új vezérlési és ember-gép kapcsolat módszerek. • Robusztus termeléstervezés és -ütemezés manuális, ill. moduláris szerelési rendszerekben; kiterjesztés a jól gyártható termékek tervezése irányába. Az eredményeket összesen 44 publikáció (18 IF folyóiratban) közli. A CPPS területet megalapozó keynote cikk az egyik vezető folyóiratban a 2016 óta megjelent cikkek közt eddig a legtöbb hivatkozást kapta (Monostori, L.; Kádár, B. et al., 2016, Cyber-physical systems in manufacturing, CIRP Annals 65(2):621-641;Googlescholar: 428, Scopus: 287). 1 regisztrált nemzetközi szabadalom, 1 elbírálás alatt.
Results in English
The research set the foundations of the Cyber-Physical Production Systems (CPPS) paradigm, with its key challenges and opportunities, and its extension towards the biological transformation of manufacturing incorporating sustainability. Main results achieved: • Crowdsourcing collaboration platform for autonomous factories, facilitating cooperative share of resources; game-theoretic models for demand-response management (tariff optimization). • Robust, distribution-free and tractable methods for the identification and prediction of the behavior of stochastic dynamic systems with confidence regions. • Fusion of real and virtual systems by sensor, machine learning and digital twin technologies, lead time prediction, robot operation and calibration in semi-structured environment, setup of a SmartFactory. • Human-robot symbiosis in collaborative assembly, planning, off-line programming, new control and human-machine interface. • Robust production planning (PP) and scheduling model for manual and modular assembly systems, PP extended with design for manufacturing and assembly. Results appeared in 44 publications (18 in IF journals). Keynote on the grounds of CPPS is the most cited paper published since 2016 in a leading journal of the field (Monostori, L.; Kádár, B. et al., 2016, Cyber-physical systems in manufacturing, CIRP Annals 65(2):621-641;Googlescholar: 428, Scopus: 287). 1 international patent registered, 1 is pending.
Full text https://www.otka-palyazat.hu/download.php?type=zarobeszamolo&projektid=113038
Decision
Yes





 

List of publications

 
Csáji B Cs: Score Permutation Based Finite Sample Inference for Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Models, JOURNAL OF MACHINE LEARNING RESEARCH WORKSHOP AND CONFERENCE PROCEEDINGS 51: pp. 296-304., 2016
Kovács A , Bátai R , Csáji B Cs , Dudás P , Háy B , Pedone G , Révész T , Váncza J: Intelligent control for energy-positive street lighting, ENERGY 114: pp. 40-51., 2016
Kardos Cs , Kovács A , Váncza J: Towards Feature-based Human-robot Assembly Process Planning, PROCEDIA CIRP 57: pp. 516-521, 2016
Egri P , Kádár B , Váncza J: Towards coordination in robust supply networks, IFAC-PAPERSONLINE 49:(12) pp. 41-46, 2016
Gyulai D , Pfeiffer A , Kádár B , Monostori L: Simulation-based Production Planning and Execution Control for Reconfigurable Assembly Cells, PROCEDIA CIRP 57: pp. 445-450, 2016
Erdős G , Kovács A , Váncza J: Optimized joint motion planning for redundant industrial robots, CIRP ANNALS-MANUFACTURING TECHNOLOGY 65:(1) pp. 451-454., 2016
Váncza J: Production networks, CIRP Encyclopedia of Production Engineering . Heidelberg: Springer, 2016. pp. 1-8., 2016
Caré A, Csáji B Cs, Campi MC, Weyer E: Finite-Sample System Identification: An Overview and a New Correlation Method, 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017. Melbourne, Ausztrália, 2017.12.12 -2017.12.15. Piscataway: IEEE, 2017. pp. 4 (ISBN:978-1-5090-2872-6), 2017
Gyulai D, Pfeiffer A, Monostori L: Robust production planning and control for multi-stage systems with flexible final assembly lines, INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 55:(13) pp. 3657-3673., 2017
Gyulai D, Monostori L: Capacity management of modular assembly systems, JOURNAL OF MANUFACTURING SYSTEMS 43: pp. 88-99., 2017
Gyulai D, Kádár B, Monostori L: Scheduling and Operator Control in Reconfigurable Assembly Systems, PROCEDIA CIRP 63: pp. 459-464., 2017
Horváth G, Erdős G: Gesture Control of Cyber Physical Systems, PROCEDIA CIRP 63: pp. 184-188. (, 2017
Horváth G, Erdős G: Point cloud based robot cell calibration, CIRP ANNALS-MANUFACTURING TECHNOLOGY 66:(1) pp. 145-148., 2017
Nonaka Y, Nakano T, Ohya K, Enomoto A, Erdős G, Horváth G, Váncza J: Engineering Support Systems for Industrial Machines and Plants, Redding L, Roy R, Shaw A (szerk.) Advances in Through-life Engineering Services. Cham: Springer, 2017. pp. 199-220. (Decision Engineering) (ISBN:978-3-319-49937-6), 2017
Váncza J, Monostori L: Cyber-physical Manufacturing in the Light of Professor Kanji Ueda's Legacy, PROCEDIA CIRP 63: pp. 631-638., 2017
Weyer E, Campi M C, Csáji B Cs: Asymptotic properties of SPS confidence regions, AUTOMATICA 82: pp. 287-294., 2017
Byrne, G ; Dimitrov, D ; Monostori, L ; Teti, R ; van Houten, F ; Wertheim, R.: Biologicalisation: Biological transformation in manufacturing, CIRP Journal of Manufacturing Science and Technology, 2018
Cserteg, T ; Erdős, G ; Horváth, G.: Digital twin assisted human-robot collaborative workcell control, ERCIM News, 2018
Care, A. ; Csaji, B.C. ; Campi, M.C. ; Weyer, E.: Finite-sample system identification: An overview and a new correlation method, IEEE Control Systems Letters, 2(1):61-66, 2018
Kadar, B ; Egri, P ; Pedone, G ; Chida, T.: Smart, simulation-based resource sharing in federated production networks, CIRP Annals -- Manufacturing Technology 67(1):503-506, 2018
Tsutsumi, D ; Gyulai, D ; Kovács, A ; Tipary, B ; Ueno, Y ; Nonaka, Y ; Monostori, L: Towards joint optimization of product design, process planning and production planning in multi-product assembly, CIRP Annals -- Manufacturing Technology 67(1):441-446, 2018
Byrne, G ; Dimitrov, D ; Monostori, L ; Teti, R ; van Houten, F ; Wertheim, R.: Biologicalisation: Biological transformation in manufacturing, CIRP Journal of Manufacturing Science and Technology, 2018
Kadar, B ; Egri, P ; Pedone, G ; Chida, T.: Smart, simulation-based resource sharing in federated production networks, CIRP Annals -- Manufacturing Technology 67(1):503-506, 2018
Tsutsumi, D ; Gyulai, D ; Kovács, A ; Tipary, B ; Ueno, Y ; Nonaka, Y ; Monostori, L: Towards joint optimization of product design, process planning and production planning in multi-product assembly, CIRP Annals -- Manufacturing Technology 67(1):441-446, 2018
Fekula M., Horváth G.: Determining stable equilibria of spatial objects and validating the results with drop simulation, Procedia CIRP, 2019
Erdős G, Nakano T, Horváth G, Nonaka Y, Váncza J: Recognition of complex engineering objects from large-scale point clouds, CIRP Annals – Manufacturing Technology, 64(1), pp.165-168., 2015
Stricker N, Pfeiffer A, Moser E, Kádár B, Lanza G, Monostori L: Supporting multi-level and robust production planning and execution, CIRP Annals – Manufacturing Technology, 64(1), pp.415-418., 2015
Monostori L, Valckenaers P, Dolgui A, Panetto H, Brdys M, Csáji BCs: Cooperative Control in Production and Logistics, Annual Reviews in Control, Vol. 39., 2015, pp. 12-29, 2015
Monostori L: Cyber-physical production systems: Roots from manufacturing science and technology, at AUTOMATISIERUNGSTECHNIK 63:(10) pp.766-776., 2015
Erdős G, Kardos Cs, Kemény Zs, Kovács A, Váncza J: Planning and off-line robot programming system for remote laser welding, 25th International Conference on Automated Planning and Scheduling (ICAPS 2015) June 7-11, 2015 Jerusalem, Israel, System Demonstrations, p.1., 2015
Csáji BCs, Weyer E: Closed-Loop Applicability of the sign-perturbed sums method, 54th IEEE Conference on Decision and Control (CDC), Dec. 15-18, 2015 Osaka, Japan, pp. 1441-1446, 2015
Vople V, Csáji BCs, Care A, Weyer E, Marco C: Sign-Perturbed Sums with Instrumental Variables for the Identification of ARX Systems, 54th IEEE Conference on Decision and Control (CDC), Dec. 15-18, 2015 Osaka, Japan, pp. 2115-2120, 2015
Egri P.: Information elicitation for aggregate demand prediction with costly forecasting, Autonomous Agents and Multi-Agent Systems DOI 10.1007/s10458-015-9301-9 Published on-line 21 June 2015, 2015
Pfeiffer A., Gyulai D., Kádár B., Monostori L.: Manufacturing lead time estimation with the combination of simulation and statistical learning methods, Procedia CIRP (in print), 2015
Gyulai, D.; Kádár, B.; Monostori, L.: Robust production planning and capacity control for flexible assembly lines, IFAC-PapersOnLine, Vol. 48, No. 3, 2015, pp. 2312-2317. (ISSN: 1474-6670) (DOI: 10.1016/j.ifacol.2015.06.432), 2015
Ilie-Zudor, E.; Ekárt, A.; Kemény, Zs.; Buckingham, C.D.; Welch, P.G.; Monostori, L.: Advanced predictive-analysis-based decision support for collaborative logistics networks, Supply Chain Management: An International Journal, 2015, Vol 20, No. 4, pp. 369-388, (DOI: 10.1108/SCM-10-2014-0323), 2015
Pfeiffer A., Gyulai D., Kádár B., Monostori L.: Manufacturing lead time estimation with the combination of simulation and statistical learning methods, Procedia CIRP 41: pp. 75-80, 2016
Monostori L , Kádár B, Bauernhansl T, Kondoh S, Kumara S, Reinhart G, Sauer O, Schuh , Sihn W, Ueda K.: Cyber-physical systems in manufacturing, CIRP Annals-Manufacturing Technology 65:(2) pp. 621-641., 2016
Csáji B Cs , Kovács A , Váncza J: Online Learning for Aggregating Forecasts in Renewable Energy Systems, ERCIM NEWS (107) pp. 40-41, 2016
Kovács A: Bilevel programming approach to optimizing a time-variant electricity tariff for demand response, 7th IEEE International Conference on Smart Grid Communications, IEEE Communications Society, 2016. pp. 698-703., 2016
Gyulai D , Szaller Á , VIharos Zs J: Simulation-based Flexible Layout Planning Considering Stochastic Effects, PROCEDIA CIRP 57: pp. 177-182, 2016
Popovics G , Monostori L: An approach to Determine Simulation Model Complexity, PROCEDIA CIRP 52: pp. 257-261., 2016
Kemény Zs , Nacsa J , Erdős G , Glawar R , Sihn W , Monostori L , Ilie-Zudor E: Complementary research and education opportunities – a comparison of learning factory facilities and methodologies at TU Wien and MTA SZTAKI, PROCEDIA CIRP 54: pp. 47-52., 2016
Kemény Zs , Beregi R J , Erdős G , Nacsa J: The MTA SZTAKI Smart Factory: Platform for Research and Project-oriented Skill Development in Higher Education, PROCEDIA CIRP 54: pp. 53-58., 2016
Viharos Zs J , Csanaki J , Nacsa J , Edelényi M , Péntek Cs , Kis K B , Fodor Á , Csempesz J: Production trend identification and forecast for shop-floor business intelligence, ACTA IMEKO 5:(4) pp. 49-55., 2016
Horváth G , Erdős F G: Pontfelhő alapú hossztengely keresés OpenGL GLSL nyelven: Largest principal axis search based on point clouds, utilizing OpenGL GLSL, 24th International Conference on Mechanical Enginering . 516 p. pp. 202-205., 2016
Panetto H , Zdravkovic M , Jardim-Goncalves R , Romero D , Cecil J , Mezgár I: New perspectives for the future interoperable enterprise systems, COMPUTERS IN INDUSTRY 79: pp. 43-63., 2016
Gyulai D., Pfeiffer A., Monostori L.: Robust production planning and control for multi-stage systems with flexible final assembly lines (accepted), International Journal of Production Research (2016): 1-17.http://dx.doi.org/10.1080/00207543.2016.1198506, 2016





 

Events of the project

 
2016-02-28 19:23:27
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