Smart Maintenance

Smart Maintenance through Industry 4.0 and Big Analytics.

Introduction

Nowadays not only Spanish industry, but also the European industry has to deal with global markets and strong competition from other regions where costs are much lower. Therefore, it becomes extremely relevant to increase the trust in product and service.

Maintenance operations have a significant influence on company costs (10%-40% depending on company size and industry branch). This makes necessary an innovative maintenance approach with a novel design, reliability based, in which the industrial system is considered as a whole.
Predictive maintenance -sometimes called “on-line monitoring”, “condition-based maintenance”, or “risk-based maintenance”- has a long history. From visual inspection, which is the oldest method, yet still one of the most powerful and widely-used predictive maintenance, has evolved to automated methods that use advanced signal processing techniques based on pattern recognition, including neural networks, fuzzy logic, and data-driven empirical and physical modeling.

These techniques can be divided into several categories. The first category uses signals from existing process sensors, to help verify the performance of the sensors and process-to-sensor interfaces, and also to identify problems in the process. Another category depends on signals from additional sensors that are installed on plant equipment. Variables read from those sensors are then trended to identify the onset of degradation or failure. With each additional parameter that can be measured and correlated with equipment condition, the diagnostic capabilities of the category can increase exponentially.

The innovative idea of connecting forecasts of assets damage to operational decisions is a challenge that will require the development of advanced tools and methodologies applicable but also capable of generalization to any industry.
Another challenge stems from the fact that maintenance and production departments are normally independent from each other. It is a challenge to change such structures, especially because decision makers are also unfamiliar with the consideration of damage propagation influencing the scheduled production of orders.
To achieve full benefits of the integrative view of prescriptive maintenance, both actions (organizational structures and decision making changes) are necessary.

There is an enormous and promising research field ahead, because of possibilities brought by the Digital Twin paradigm.

Related Publications

Some of the interesting papers produced in this research can be found underneath,

  • [DOI] C. Ramírez-Aragón, F. Alba-Elías, A. González-Marcos, and J. Ordieres-Meré, “Improving the feeder shoe design of an eccentric tablet press machine,” Powder technology, vol. 372, pp. 542-562, 2020.
    [Bibtex] 
    @Article{RAMIREZARAGON2020542,
title = {Improving the feeder shoe design of an eccentric tablet press machine},
journal = {Powder Technology},
volume = {372},
pages = {542 - 562},
year = {2020},
issn = {0032-5910},
doi = {https://doi.org/10.1016/j.powtec.2020.05.104},
url = {http://www.sciencedirect.com/science/article/pii/S0032591020304782},
author = {Cristina Ram\'irez-Aragón and Fernando Alba-El\'ias and Ana González-Marcos and Joaquín Ordieres-Meré},
keywords = {Segregation, Granular material, Eccentric tablet press machine, Inserts, Experimental, Discrete element method (DEM)},
note = {\textbf{Q1}; 4.142; Engineering, Chemical},
gsid = {13964399972724302718},
gsid = {13964399972724302718},
ncites = {4},
ncites = {4},
}
  • [DOI] S. Sun, X. Zheng, J. Villalba-Díez, and J. Ordieres-Meré, “Data handling in industry 4.0: interoperability based on distributed ledger technology,” Sensors, vol. 20, iss. 11, p. 3046, 2020.
    [Bibtex] 
    @Article{sun2020data,
title = {Data Handling in Industry 4.0: Interoperability Based on Distributed Ledger Technology},
author = {Shengjing Sun and Xiaochen Zheng and Javier Villalba-Díez and Joaqu\'in Ordieres-Meré},
journal = {Sensors},
volume = {20},
number = {11},
pages = {3046},
year = {2020},
url = {https://www.mdpi.com/1424-8220/20/11/3046},
doi = {10.3390/s20113046},
publisher = {Multidisciplinary Digital Publishing Institute},
note = {\textbf{Q1}; 3.275; Instruments \& Instrumentation},
gsid = {16573729277343494954},
ncites = {37},
}
  • [DOI] D. Schmidt, J. Villalba Diez, J. Ordieres-Meré, R. Gevers, J. Schwiep, and M. Molina, “Industry 4.0 lean shopfloor management characterization using eeg sensors and deep learning,” Sensors, vol. 20, iss. 10, p. 2860, 2020.
    [Bibtex] 
    @Article{schmidt2020industry,
title = {Industry 4.0 Lean Shopfloor Management Characterization Using EEG Sensors and Deep Learning},
author = {Daniel Schmidt and Javier {Villalba Diez} and Joaqu\'in Ordieres-Meré and Roman Gevers and Joerg Schwiep and Martin Molina},
journal = {Sensors},
volume = {20},
number = {10},
pages = {2860},
year = {2020},
url = {https://www.mdpi.com/1424-8220/20/10/2860},
doi = {10.3390/s20102860},
publisher = {Multidisciplinary Digital Publishing Institute},
note = {\textbf{Q1}; 3.275; Instruments \& Instrumentation},
gsid = {14758651879465604820},
ncites = {27},
}
  • [DOI] S. Sun, X. Zheng, B. Gong, J. García Paredes, and J. Ordieres-Meré, “Healthy operator 4.0: a human cyber–physical system architecture for smart workplaces,” Sensors, vol. 20, iss. 7, p. 2011, 2020.
    [Bibtex] 
    @Article{sun2020healthy,
title = {Healthy Operator 4.0: A Human Cyber--Physical System Architecture for Smart Workplaces},
author = {Shengjing Sun and Xiaochen Zheng and Bing Gong and Jorge {García Paredes} and Joaqu\'in Ordieres-Meré},
journal = {Sensors},
volume = {20},
number = {7},
pages = {2011},
year = {2020},
url = {https://www.mdpi.com/1424-8220/20/7/2011},
doi = {10.3390/s20072011},
publisher = {Multidisciplinary Digital Publishing Institute},
note = {\textbf{Q1}; 3.275; Instruments \& Instrumentation},
gsid = {15229857575878997714},
ncites = {49},
}
  • [DOI] J. Ordieres-Meré, T. P. Remón, and J. Rubio, “Digitalization: an opportunity for contributing to sustainability from knowledge creation,” Sustainability, vol. 12, iss. 4, p. 1460, 2020.
    [Bibtex] 
    @Article{ordieres2020digitalization,
title = {Digitalization: An opportunity for contributing to sustainability from knowledge creation},
author = {Joaqu\'in Ordieres-Meré and Tomás Prieto Remón and Jesús Rubio},
journal = {Sustainability},
volume = {12},
number = {4},
pages = {1460},
year = {2020},
url = {https://www.mdpi.com/2071-1050/12/4/1460},
doi = {10.3390/su12041460},
publisher = {Multidisciplinary Digital Publishing Institute},
note = {\textbf{Q2}; 2.468; Environmental Science},
gsid = {8913950056194442005},
ncites = {101},
}
  • [DOI] J. Villalba-Díez, M. Molina, J. Ordieres-Meré, S. Sun, D. Schmidt, and W. Wellbrock, “Geometric deep lean learning: deep learning in industry 4.0 cyber–physical complex networks,” Sensors, vol. 20, iss. 3, p. 763, 2020.
    [Bibtex] 
    @Article{villalba2020geometric,
title = {Geometric Deep Lean Learning: Deep Learning in Industry 4.0 Cyber--Physical Complex Networks},
author = {Javier Villalba-Díez and Martin Molina and Joaqu\'in Ordieres-Meré and Shengjing Sun and Daniel Schmidt and Wanja Wellbrock},
journal = {Sensors},
volume = {20},
number = {3},
pages = {763},
year = {2020},
url = {https://www.mdpi.com/1424-8220/20/3/763},
doi = {10.3390/s20030763},
publisher = {Multidisciplinary Digital Publishing Institute},
note = {\textbf{Q1}; 3.275; Instruments \& Instrumentation},
gsid = {15286386535255665589},
ncites = {21},
}
  • [DOI] J. Villalba-Diez, D. Schmidt, R. Gevers, J. Ordieres-Meré, M. Buchwitz, and W. Wellbrock, “Deep learning for industrial computer vision quality control in the printing industry 4.0,” Sensors, vol. 19, iss. 18, p. 3987, 2019.
    [Bibtex] 
    @Article{villalba2019deep,
title = {Deep Learning for Industrial Computer Vision Quality Control in the Printing Industry 4.0},
author = {Javier Villalba-Diez and Daniel Schmidt and Roman Gevers and Joaqu\'in Ordieres-Meré and Martin Buchwitz and Wanja Wellbrock},
journal = {Sensors},
volume = {19},
number = {18},
pages = {3987},
year = {2019},
url = {https://www.mdpi.com/1424-8220/19/18/3987},
doi = {10.3390/s19183987},
publisher = {Multidisciplinary Digital Publishing Institute},
note = {\textbf{Q1}; 3.275; Instruments \& Instrumentation},
gsid = {13137413968855254348},
ncites = {60},
}
  • X. Zheng, S. Sun, R. R. Mukkamala, R. Vatrapu, and J. Ordieres-Meré, “Accelerating health data sharing: a solution based on the internet of things and distributed ledger technologies,” Journal of medical internet research, vol. 21, iss. 6, p. e13583, 2019.
    [Bibtex] 
    @Article{zheng2019accelerating,
title = {Accelerating Health Data Sharing: A Solution Based on the Internet of Things and Distributed Ledger Technologies},
author = {Xiaochen Zheng and Shengjing Sun and Raghava Rao Mukkamala and Ravi Vatrapu and Joaqu\'in Ordieres-Meré},
journal = {Journal of medical Internet research},
volume = {21},
number = {6},
pages = {e13583},
year = {2019},
publisher = {JMIR Publications Inc., Toronto, Canada},
note = {\textbf{Q1}; 5.034; Medical Informatics},
gsid = {11896143269341442310},
ncites = {88},
}
  • M. Á. Antón, J. Ordieres-Meré, U. Saralegui, and S. Sun, “Non-invasive ambient intelligence in real life: dealing with noisy patterns to help older people,” Sensors, vol. 19, iss. 14, p. 3113, 2019.
    [Bibtex] 
    @Article{anton2019non,
title = {Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People},
author = {Miguel Ángel Antón and Joaqu\'in Ordieres-Meré and Unai Saralegui and Shengjing Sun},
journal = {Sensors},
volume = {19},
number = {14},
pages = {3113},
year = {2019},
url = {https://www.mdpi.com/1424-8220/19/14/3113},
publisher = {Multidisciplinary Digital Publishing Institute},
note = {\textbf{Q1}; 3.275; Instruments \& Instrumentation},
gsid = {10402819281666227884},
ncites = {15},
}
  • [DOI] G. Bing, Z. Xiaochen, G. Qing, and J. Ordieres-Meré, “Discovering the patterns of energy consumption, gdp, and $CO_{2}$ emissions in china using the cluster method,” Energy, vol. 166, p. 1149–1167, 2019.
    [Bibtex] 
    @Article{bing2018discovering,
title = {Discovering the patterns of energy consumption, GDP, and $CO_{2}$ emissions in China using the cluster method},
author = {Gong Bing and Zheng Xiaochen and Guo Qing and Joaqu\'in Ordieres-Meré},
journal = {Energy},
pages = {1149--1167},
volume = {166},
year = {2019},
publisher = {Elsevier},
url = {https://www.sciencedirect.com/science/article/pii/S0360544218321388},
doi = {10.1016/j.energy.2018.10.143},
note = {\textbf{Q1}; 6.082; Energy \& Fuels},
gsid = {6260347305797686885},
ncites = {25},
}
  • [DOI] I. D. Sanctis, J. O. Meré, and F. E. Ciarapica, “Resilience for lean organisational network,” International journal of production research, pp. 1-20, 2018.
    [Bibtex] 
    @Article{doi:10.1080/00207543.2018.1457810,
author = {Ilaria De Sanctis and Joaqu\'in Ordieres Meré and Filippo Emanuele Ciarapica},
title = {Resilience for lean organisational network},
journal = {International Journal of Production Research},
volume = {0},
number = {0},
pages = {1-20},
year = {2018},
publisher = {Taylor \& Francis},
doi = {10.1080/00207543.2018.1457810},
url = {https://doi.org/10.1080/00207543.2018.1457810 },
note = {\textbf{Q1}; 3.199; Operational Research \& Management Sciences},
gsid = {1481311593624838045},
ncites = {29},
}
  • [DOI] F. Shrouf, B. Gong, and J. Ordieres-Meré, “Multi-level awareness of energy used in production processes,” Journal of cleaner production, vol. 142, Part 4, pp. 2570-2585, 2017.
    [Bibtex] 
    @Article{Shrouf20172570,
title = {Multi-level awareness of energy used in production processes },
journal = {Journal of Cleaner Production },
volume = {142, Part 4},
pages = {2570 - 2585},
year = {2017},
issn = {0959-6526},
doi = {http://dx.doi.org/10.1016/j.jclepro.2016.11.019},
url = {http://www.sciencedirect.com/science/article/pii/S0959652616318534},
author = {Fadi Shrouf and Bing Gong and Joaquin Ordieres-Meré},
keywords = {Multi-level energy awareness},
comment = {Jmr2JHQAAAAJ:t7zJ5fGR-2UC},
note = {\textbf{Q1}; 5.651; Engineering, Environmental},
gsid = {2215004895783949673},
ncites = {37},
}

Related Theses

Indeed, it is possible to make reference to specific thesis already finished, which are related to this research line

  • S. Sun, “Digitalization capacity for knowledge acquisition: learning from health.,” Tesis PhD Thesis, 2020.
    [Bibtex] 
    @PHDTHESIS{upm20200706,
title = { Digitalization Capacity for Knowledge Acquisition: Learning from Health.},
school = {Industrial Engieering. Universidad Polit\'ecnica de Madrid},
author = {Shengjing Sun},
year = {2020},
type = {Tesis},
note = {autor, Shengjing Sun,
Advisors, Joaqu\'in Ordieres Mer\'e},
university = {Universidad Polit\'ecnica de Madrid,
Programa DEGIN,
Departamento de Ingenier\'ia de
Organizaci\'on Administraci\'on de Empresas y Estad\'istica,
Universidad Polit\'ecnica de Madrid}
}
  • X. Zheng, “Relevant framework for social applications of internet of things by means of machine learning.,” Tesis PhD Thesis, 2019.
    [Bibtex] 
    @PHDTHESIS{upm20190429,
title = {Relevant framework for social applications of internet of things by means of machine learning.},
school = {Industrial Engieering. Universidad Polit\'ecnica de Madrid},
author = {Xiaochen Zheng},
year = {2019},
type = {Tesis},
note = {autor, Xiaochen Zheng,
Advisors, Joaqu\'in Ordieres Mer\'e},
university = {Universidad Polit\'ecnica de Madrid,
Programa DEGIN,
Departamento de Ingenier\'ia de
Organizaci\'on Administraci\'on de Empresas y Estad\'istica,
Universidad Polit\'ecnica de Madrid}
}
  • F. Shrouf, “Utilizing the internet of things to promote energy awareness and efficiency at discrete production processes: practices and methodology,” Tesis PhD Thesis, 2015.
    [Bibtex] 
    @PHDTHESIS{Shrouf2015,
author = {Shrouf, Fadi},
title = {Utilizing the Internet of Things to promote energy awareness and
efficiency at discrete production processes: Practices and methodology},
school = {Industrial Engieering. Universidad Polit\'ecnica de Madrid},
year = {2015},
type = {Tesis},
note = {autor, Fadi Shrouf ; Advisors, Joaqu\'in Ordieres Mer\'e and Giovanni Miragliotta},
owner = {jb},
url = {http://oa.upm.es/37542/},
timestamp = {2015.07.21},
university = {Universidad Polit\'ecnica de Madrid, Departamento de Ingenier\'a de
Organizaci\'on Administraci\'on de Empresas y Estad\'stica,
Universidad Polit\'ecnica de Madrid}
}

Related Research Projects

Some research projects are aligned to this research line, such as,

CodeURL of the project / TitleFunding source
WISESThttp://wisestproject.com/European Commission
SMASHINGhttps://biba.etsii.upm.es/pmq/smashing/National Research Agency
AUTOSURVEILLANCEhttps://www.cetic.be/AutoSurveillance-enEuropean Commission
CONTROLinSTEELhttps://www.santannapisa.it/it/ricerca/progetti/control-steel-diffusione-e-valorizzazione-dei-risultati-di-rfcs-nel-campo-delleEuropean Commission