Skip to main content

Advertisement

Springer Nature Link
Log in

A traceability proposal for industry 4.0

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

This research examines traceability and its model in industry 4.0. Hence, this paper introduces the main design features of this model. The fourth industrial revolution is an environment that combines manufacturing with the Internet of Things and cyber-physical Systems. In such an environment, various sources (i.e., smart products, intelligent agents, and sensors) generate an increasing amount of data, which is essential for effective traceability. However, due to these heterogeneous sources, a traceability system should face the interoperability challenge and overcome the data integration issue. Moreover, the incorporation of this information in a traceability tool is motivated by the requirement to have access to a maximum amount of accurate product data. Thus, this article proposes to take advantage of industry 4.0 information. Also, the present study advocates that traceability should not only allow trace and track but also ensure product safety and quality. Accordingly, the proposal includes an intelligent traceability description, an ontology-based modeling, and a cloud-based application. This system provides users with a common knowledge base to access and represent data. Also, this model enables users to share and query remotely the traceable information using the cloud.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Alonso-Rorís VM, Álvarez-Sabucedo L, Santos-Gago JM, Ramos-Merino M (2016) Towards a cost-effective and reusable traceability system. A semantic approach. Comput Ind 83:1–11

    Google Scholar 

  • Appelhanz S, Osburg VS, Toporowski W, Schumann M (2016) Traceability system for capturing, processing and providing consumer-relevant information about wood products: system solution and its economic feasibility. J Clean Prod 110:132–148

    Google Scholar 

  • Barata J, da Cunha PR, Gonnagar AS, Mendes M (2018) Product traceability in ceramic industry 4.0: a design approach and cloud-based MES prototype. In: Paspallis N, Raspopoulos M, Barry C, Lang M, Linger H (eds) Advances in information systems development (lecture notes in information systems and organization), vol 26. Springer, Cham, pp 187–204. https://doi.org/10.1007/978-3-319-74817-7

  • Bettini C, Brdiczka O, Henricksen K, Indulska J, Nicklas D, Ranganathan A, Riboni D (2010) A survey of context modelling and reasoning techniques. Pervasive Mobile Comput 6(2):161–180

    Google Scholar 

  • Bortolini M et al (2017) Assembly system design in the industry 4.0 era: a general framework. In: IFAC-PapersOnLine, vol 50(1), pp 5700-5705

  • Bougdira A, Ahaitouf A, Akharraz I (2016a) Cloud of things-based decision-making process using product’s traceability. IEEE Proc. https://doi.org/10.1109/CloudTech.2016.7847701

    Article  Google Scholar 

  • Bougdira A, Ahaitouf A, Akharraz I (2016b) An intelligent traceability system: efficient tool for a supply chain sustainability. AIP Proc. https://doi.org/10.1063/1.4959406

    Article  Google Scholar 

  • Bougdira A, Ahaitouf A, Akharraz I (2016c) Towards an intelligent traceability system. IEEE Proc. https://doi.org/10.1109/it4od.2016.7479280

    Article  Google Scholar 

  • Bougdira A, Ahaitouf A, Akharraz I (2019) Fuzzy approach to enhance quality control within intelligent traceability systems. IEEE Proc. https://doi.org/10.1109/wits.2019.8723764

    Article  Google Scholar 

  • Bratt S (2007) Semantic web, and other technologies to watch. https://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/0130-sb-W3CTechSemWeb.pdf. Accessed 6 Mar 2019

  • Carter CR, Liane Easton P (2011) Sustainable supply chain management: evolution and future directions. Int J Phys Distrib Logist Manag 41(01):46–62

    Google Scholar 

  • Chaâri R, Ellouze F, Anis K, Basit Q, Nuno P, Habib Y, Eduardo T (2016) Cyber-physical systems clouds: a survey. Comput Netw 108:260–278 (issn 1389-1286)

    Google Scholar 

  • Chen RY (2015) Autonomous tracing system for backward design in food supply chain. Food Control 51:70–84

    Google Scholar 

  • Compton M et al (2012) The SSN ontology of the W3C semantic sensor network incubator group. J Web Semant 17:25632

    Google Scholar 

  • Corallo A, Latino ME, Menegoli M (2018) From industry 4.0 to agriculture 4.0: a framework to manage product data in agri-food supply chain for voluntary traceability. Int J Nutr Food Eng 12(5):146–150

    Google Scholar 

  • Erl T (2005) Service-oriented architecture (paperback): concepts, technology, and design. Prentice Hall International, Upper Saddle River. https://www.arcitura.com/wp-content/uploads/2017/09/Erl_SOABook2_Ch07-2.pdf

  • García CG, Núñez-Valdez ER, García-Díaz V, Pelayo G, Bustelo C, Cueva-Lovelle JM (2019) A review of artificial intelligence in the Internet of Things. Int J Interact Multimed Artif Intell 05(04):9–20

    Google Scholar 

  • García-Castro R, Gómez-Pérez A (2010) Interoperability results for semantic web technologies using OWL as the interchange language. Web semantics: science, services and agents on the World Wide Web. J Web Semant 8(4):278–291. https://doi.org/10.1016/j.websem.2010.08.008

    Article  Google Scholar 

  • Giustozzi F, Saunier J, Zanni-Merk C (2018) Context modeling for industry 4.0: an ontology-based proposal. Procedia Comput Sci 126:675–684. https://doi.org/10.1016/j.procs.2018.08.001

    Article  Google Scholar 

  • Gruber TR (1993) A translation approach to portable ontology specifications. Knowl Acquis 5(2):199–220

    Google Scholar 

  • Hashizume K, Rosado DG, Fernández-Medina E, Fernandez EB (2013) An analysis of security issues for cloud computing. J Internet Serv Appl 4(1):1–13

    Google Scholar 

  • Hofmann E, Rüsch M (2017) Industry 4.0 and the current status as well as future prospects on logistics. Comput Ind 89:23–34

    Google Scholar 

  • Horrocks I, Patel-Schneider PF, van Harmelen F (2003) From SHIQ and RDF to OWL: the making of a web ontology language. Web semantics: science, services and agents on the World Wide Web. J Web Semant 1(1):7–26. https://doi.org/10.1016/j.websem.2003.07.001

    Article  Google Scholar 

  • Ivanova V, Lambrix P, Lohmann S, Pesquita C (2018) Visualization and interaction for ontologies and linked data-editorial, web semantics: science, services and agents on the World Wide Web. J Web Semant. https://doi.org/10.1016/j.websem.2018.10.001

    Article  Google Scholar 

  • Janowicz K, Haller A, Cox SJD, Le Phuoc D, Lefrançois M (2018) SOSA: a lightweight ontology for sensors, observations, samples, and actuators. J Web Semant. https://doi.org/10.1016/j.websem.2018.06.003

    Article  Google Scholar 

  • Jansen-Vullers M, van Dorp CA, Beulens AJ (2003) Managing traceability information in manufacture. Int J Inf Manag 23(5):395–413

    Google Scholar 

  • Karlsen K, Donnelly KA-M, Olsen O (2011) Granularity and its importance for traceability in a farmed salmon supply chain. J Food Eng 102(1):1–8

    Google Scholar 

  • Kontchakov R, Pratt-Hartmann I, Zakharyaschev M (2014) Spatial reasoning with RCC8 and connectedness constraints in Euclidean spaces. Artif Intell 217:43–75

    MATH  Google Scholar 

  • Lorezo W, Gonzalez-Crespo R, Castillo-Sanz A (2010) A prototype for linear features generalization, International Journal of interactive multimedia and artificial. Intelligence 01(03):60–66

    Google Scholar 

  • Mania I, Delgado AM, Barone C, Parisi S (2018) Food traceability system in Europe: basic and regulatory requirements. In: Traceability in the dairy industry in Europe: theory and practice. https://doi.org/10.1007/978-3-030-00446-0_1

  • Matkovic P, Tumbas P, Pavlicevic V (2014) Decision making in logistics processes supported by cloud computing. Int Sci J Manag Inf Syst 09(01):11–20

    Google Scholar 

  • Miragliotta G, Sianesi A, Elisa C, Distante R (2018) Data driven management in industry 4.0: a method to measure data productivity. IFAC-PapersOnLine 51(11):19–24

    Google Scholar 

  • Moe T (1998) Perspectives on traceability in food manufacture. Trends Food Sci Technol 9:211–214

    Google Scholar 

  • Molano JIR, Lovelle JMC, Montenegro CE, Granados JJR, Crespo RG (2018) Metamodel for integration of internet of things, social networks, the cloud and industry 4.0. J Ambient Intell Humaniz Comput 09(03):709–723

    Google Scholar 

  • Nighot M, Ghatol A, Thakare V (2017) Self-organized hybrid wireless sensor network for finding randomly moving target in unknown environment. Int J Interact Multimed Artif Intell 05(01):16–28

    Google Scholar 

  • Olsen P, Borit M (2013) How to define traceability. Trends Food Sci Technol 29:142–150

    Google Scholar 

  • Olsen P, Borit M (2018) The components of a food traceability system. Trends Food Sci Technol 77:143–149

    Google Scholar 

  • Pérez F, Irisarri E, Orive D., Marcos M, Estevez E (2015) A CPPS Architecture approach for industry 4.0. In: IEEE 20th conference on emerging technologies and factory automation (ETFA), Luxembourg, 2015, pp 1–4. https://doi.org/10.1109/etfa.2015.7301606

  • Petrasch R, Hentschke R (2016) Process modeling for industry 4.0 applications: ToWARDS an industry 4.0 process modeling language and method. In: IEEE 13th International joint conference on computer science and software engineering (JCSSE), Khon Kaen, 2016, pp 1–5. https://doi.org/10.1109/jcsse.2016.7748885

  • Pfohl HC, Yahsi B, Tamer K (2015) The impact of industry 4.0 on the supply chain. In: Kersten W, Blecker T, Ringle CM (eds) Innovations and strategies for logistics and supply chains. epubli GmbH, pp 31–58. https://www.researchgate.net/publication/288466876_The_Impact_of_Industry_40_on_the_Supply_Chain

  • Pizzuti T, Mirabelli G, Sanz-Bobi MA, Goméz-Gonzaléz F (2014) Food track and trace ontology for helping the food traceability control. J Food Eng 120:17–30

    Google Scholar 

  • Pizzuti T, Mirabelli G, Grasso G, Paldino G (2017) MESCO (MEat Supply Chain Ontology): an ontology for supporting traceability in the meat supply chain. Food Control 72:123–133

    Google Scholar 

  • Ristoski P, Paulheim H (2016) Semantic Web in data mining and knowledge discovery: a comprehensive survey, web semantics: science, services and agents on the World Wide Web. J Web Semant. https://doi.org/10.1016/j.websem.2016.01.001

    Article  Google Scholar 

  • Salampasis M, Tektonidis D, Kalogianni EP (2012) TraceALL: a semantic web framework for food traceability systems. J Syst Inf Technol 14(04):302–317

    Google Scholar 

  • Sánchez BB, Alcarria R, Martín D, Robles T (2015) TF4SM: A framework for developing traceability solutions in small manufacturing companies. Sensors 15(11):78–80

    Google Scholar 

  • Saucedo-Martínez JA et al (2018) Industry 4.0 framework for management and operations: a review. J Ambient Intell Humaniz Comput 9(3):789–801

    Google Scholar 

  • Singh S, Jeong YS, Park JH (2016) A survey on cloud computing security: issues, threats, and solutions. J Netw Comput Appl 75:200–222

    Google Scholar 

  • Solanki M, Brewster C (2014) EPCIS event-based traceability in pharmaceutical supply chains via automated generation of linked pedigrees. In: The semantic web—ISWC 2014, lecture notes in computer science, vol 8796. Springer, pp 82–97

  • Storøy VC (2017) Conceptual modeling meets domain ontology development: a reconciliation. J Database Manag 28(1):18–30

    Google Scholar 

  • Strandhagen JO, Vallandingham LR, Fragapane G, Strandhagen JW, Stangeland ABH, Sharma N (2017a) Logistics 4.0 and emerging sustainable business models. Adv Manuf 5(4):359–369

    Google Scholar 

  • Strandhagen JW, Alfnes E, Strandhagen JO, Vallandingham LR (2017b) The fit of industry 4.0 applications in manufacturing logistics: a multiple case study. Adv Manuf 5(4):344–358

    Google Scholar 

  • Suri K, Cadavid J, Alferez M, Dhouib S, Tucci-Piergiovanni S (2017) Modeling business motivation and underlying processes for RAMI 4.0-aligned cyber-physical production systems. In: 22nd IEEE international conference on emerging technologies and factory automation (ETFA), Limassol, 2017, pp 1–6. https://doi.org/10.1109/etfa.2017.8247702

  • Timothy L et al (2013) PROV-O: the PROV ontology. https://www.w3.org/TR/prov-o/. Accessed 15 Feb 2019

  • Topcu F (2011) Context modeling and reasoning techniques. SNET seminar in the ST, pp 1–8

  • Trappey AJC, Trappey CV, Govindarajan UH, Chuang AC, Sun JJ (2017) A review of essential standards and patent landscapes for the Internet of Things: a key enabler for industry 4.0. Adv Eng Inform 33:208–229 (issn 1474-0346)

    Google Scholar 

  • Trillo R, Po L, Ilarri S, Bergamaschi S, Mena E (2011) Using semantic techniques to access web data. Inf Syst 36(2):117–133

    Google Scholar 

  • Wang KS (2014) Intelligent and integrated RFID (II-RFID) system for improving traceability in manufacturing. Adv Manuf 02(02):106–120

    Google Scholar 

  • Wang J, Yue H, Zhou Z (2017a) An improved traceability system for food quality assurance and evaluation based on fuzzy classification and neural network. Food Control 79:363–370

    Google Scholar 

  • Wang W, De S, Cassar G, Moessner K (2017b) Knowledge representation in the internet of things: semantic modelling and its applications. J Control Meas Electron Comput Commun 54(4):388–400

    Google Scholar 

  • Xiao X, Fu Z, Qi L, Mira T, Zhang X (2015) Development and evaluation on an intelligent traceability system for frozen tilapia fillet processing. J Sci Food Agric 95(13):2693–2703

    Google Scholar 

  • Xiao Xinqing, Fu Z, Yongjun Z, Zhaohui P, Xiaoshuan Z (2016) Developing an intelligent traceability system for aquatic products in cold chain logistics integrated WSN with SPC. J Food Process Preserv 40(06):1448–1458

    Google Scholar 

  • Xu LD, Xu EL, Li L (2018) Industry 4.0: state of the art and future trends. Int J Prod Res 56(80):2941–2962

    Google Scholar 

  • Zhang Y, Wang W, Yan L, Branko G, Zhang X (2019) Development and evaluation of an intelligent traceability system for waterless live fish transportation. Food Control 95:283–297

    Google Scholar 

  • Zheng P et al (2018) Smart manufacturing systems for industry 4.0: conceptual framework, scenarios, and future perspectives. Front Mech Eng 13(2):137–150

    Google Scholar 

  • Zhong R, Xu X, Klotz E, Newman ST (2017) Intelligent manufacturing in the context of industry 4.0: a review. Engineering 3(5):616–630 (issn 2095-8099)

    Google Scholar 

  • Ziegler P, Dittrich K (2007) Data Integration-problems, approaches, and perspectives. In: Krogstie J, Opdahl AL, Brinkkemper S (eds) Conceptual modelling in information systems engineering. Springer, Berlin, Heidelberg, pp 39–58. https://doi.org/10.1007/978-3-540-72677-7

  • Zissis D, Lekkas D (2012) Addressing cloud computing security issues. Future Gen Comput Syst 28(3):583–592

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Laboratory of Engineering Sciences, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Abdesselam Bougdira, Ismail Akharraz & Abdelaziz Ahaitouf

Authors
  1. Abdesselam Bougdira
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Ismail Akharraz
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Abdelaziz Ahaitouf
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Abdesselam Bougdira.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bougdira, A., Akharraz, I. & Ahaitouf, A. A traceability proposal for industry 4.0. J Ambient Intell Human Comput 11, 3355–3369 (2020). https://doi.org/10.1007/s12652-019-01532-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-019-01532-7

Keywords