Skip to main content
SpringerLink
Log in

The Challenge of Implementing Digital Twins in Operating Value Chains

  • Chapter
  • First Online:
Digital Twins

Part of the book series: Advances in Biochemical Engineering/Biotechnology ((ABE,volume 177))

Abstract

The concept of digital twins has become increasingly popular in recent years. To exploit their full potential, integration of systems and data across entire value chains is required. Implementing digital twins to newly built plants or production lines is challenging and even more complicated for currently operating production processes or factories. This chapter reviews and discusses strategies and tools to successfully implement digital twins into operating value chains in bioprocess and related industries. Furthermore, the implementation is exemplified with three recent case studies.

Graphical Abstract

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Forschungsunion, Acatech (2013) Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Final report of the Industrie 4.0 Working Group. https://www.din.de/blob/76902/e8cac883f42bf28536e7e8165993f1fd/recommendations-for-implementing-industry-4-0-data.pdf. Accessed 3 Jun 2020

  2. Negri E, Fumagalli L, Macchi M (2017) A review of the roles of digital twin in CPS-based production systems. Procedia Manuf 11:939–948. https://doi.org/10.1016/j.promfg.2017.07.198

    Article  Google Scholar 

  3. Kritzinger W, Karner M, Traar G et al (2018) Digital twin in manufacturing: a categorical literature review and classification. IFAC-PapersOnLine 51:1016–1022. https://doi.org/10.1016/j.ifacol.2018.08.474

    Article  Google Scholar 

  4. Rosen R, von Wichert G, Lo G et al (2015) About the importance of autonomy and digital twins for the future of manufacturing. IFAC-PapersOnLine 48:567–572. https://doi.org/10.1016/j.ifacol.2015.06.141

    Article  Google Scholar 

  5. Liu S (2013) Bioprocess engineering: kinetics, biosystems, sustainability, and reactor design, 1st edn. Elsevier, Amsterdam

    Google Scholar 

  6. Taylor DH (2005) Value chain analysis: an approach to supply chain improvement in agri-food chains. Int J Phys Distrib Logist Manag 35:744–761. https://doi.org/10.1108/09600030510634599

    Article  Google Scholar 

  7. Fearne A, Garcia Martinez M, Dent B (2012) Dimensions of sustainable value chains: implications for value chain analysis. Supply Chain Manag 17:575–581. https://doi.org/10.1108/13598541211269193

    Article  Google Scholar 

  8. Barrientos S (2001) Gender, flexibility and global value chains. IDS Bull 32:83–93. https://doi.org/10.1111/j.1759-5436.2001.mp32003009.x

    Article  Google Scholar 

  9. Alfaro L, Antràs P, Chor D et al (2019) Internalizing global value chains: a firm-level analysis. J Polit Econ 127:508–559. https://doi.org/10.1086/700935

    Article  Google Scholar 

  10. Trienekens JH (2011) Agricultural value chains in developing countries a framework for analysis. Int Food Agribusiness Manag Rev 14:51–82. https://doi.org/10.22004/ag.econ.103987

    Article  Google Scholar 

  11. Bittner K, Spence I (2002) Use case modeling. Safari books online. Addison-Wesley; safari books online, Boston, MA, Sebastopol, CA

    Google Scholar 

  12. Nebut C, Fleurey F, Le Traon Y et al (2006) Automatic test generation: a use case driven approach. IIEEE Trans Software Eng 32:140–155. https://doi.org/10.1109/TSE.2006.22

    Article  Google Scholar 

  13. Marsch P, Da Silva I, Bulakci O et al (2016) 5G radio access network architecture: design guidelines and key considerations. IEEE Commun Mag 54:24–32. https://doi.org/10.1109/MCOM.2016.1600147CM

    Article  Google Scholar 

  14. Ma X, Tao F, Zhang M et al (2019) Digital twin enhanced human-machine interaction in product lifecycle. Procedia CIRP 83:789–793. https://doi.org/10.1016/j.procir.2019.04.330

    Article  Google Scholar 

  15. Siepmann D, Graef N (2016) Industrie 4.0 – Grundlagen und Gesamtzusammenhang. In: Roth A (ed) Einführung und Umsetzung von Industrie 4.0: Grundlagen, Vorgehensmodell und Use Cases aus der Praxis. Springer, Berlin, Heidelberg, pp 17–82

    Google Scholar 

  16. Deutsches Institut für Normung e.V. (2014) Integration von Unternehmensführungs- und Leitsystemen – Teil 1: Modelle und Terminologie(62264–1:2013)

    Google Scholar 

  17. Redelinghuys A, Basson A, Kruger K (2019) A six-layer digital twin architecture for a manufacturing cell. In: Borangiu T, Trentesaux D, Thomas A et al (eds) Service orientation in Holonic and multi-agent manufacturing, vol 803. Springer, Cham, pp 412–423

    Chapter  Google Scholar 

  18. Guo N, Jia C (2017) Interpretation of cyber-physical systems whitepaper (2017). Inform Tech Stand 4:36–47

    Google Scholar 

  19. Ibarz A, Barbosa-Cánovas GV (2003) Unit operations in food engineering. Food preservation technology series. CRC Press, Boca Raton

    Google Scholar 

  20. Foust AS (1960, reprinted, with corrections, 1962) Principles of unit operations. Wiley, New York

    Google Scholar 

  21. International Society of Automation (2010) Batch control part 1: models and terminology (88.00.01-2010)

    Google Scholar 

  22. Weyer S, Schmitt M, Ohmer M et al (2015) Towards industry 4.0 – standardization as the crucial challenge for highly modular, multi-vendor production systems. IFAC-PapersOnLine 48:579–584. https://doi.org/10.1016/j.ifacol.2015.06.143

    Article  Google Scholar 

  23. Hallscheidt S, Adomeit N, Manske T et al (2019) 1x1 der Normung: Ein praxisorientierter Leitfaden für KMU. https://www.din.de/resource/blob/69886/5bd30d4f89c483b829994f52f57d8ac2/kleines-1x1-der-normung-neu-data.pdf. Accessed 3 Jun 2020

  24. Lu Y, Liu C, Wang KI-K et al (2020) Digital twin-driven smart manufacturing: connotation, reference model, applications and research issues. Robot Comput Integr Manuf 61:101837. https://doi.org/10.1016/j.rcim.2019.101837

    Article  Google Scholar 

  25. Deutsches Institut für Normung e.V. Normung auf einen Blick. https://www.din.de/resource/blob/249724/2dcba02aa757691193e37aa80a1a6e17/infografik-normung-auf-einen-blick-data.pdf. Accessed 31 Mar 2020 at 07:48pm

  26. International Organization for Standardization (under development) Digital twin manufacturing framework: part 1: overview and general principles (23247-1)

    Google Scholar 

  27. International Organization for Standardization (under development) Digital twin manufacturing framework: part 2: reference architecture (23247-2)

    Google Scholar 

  28. International Organization for Standardization (under development) Digital twin manufacturing framework: part 3: digital representation of physical manufacturing elements (23247-3)

    Google Scholar 

  29. International Organization for Standardization (under development) Digital twin manufacturing framework: part 4: information exchange (23247-4)

    Google Scholar 

  30. International Organization for Standardization (under development) Automation systems and integration — industrial data: visualization elements of digital twins (24464)

    Google Scholar 

  31. International Society of Automation (2001) Batch control part 2: data structures and guidelines for languages (88.00.02-2001)

    Google Scholar 

  32. International Society of Automation (2003) Batch control part 3: general and site recipe models and representation (88.00.03-2003)

    Google Scholar 

  33. International Society of Automation (2006) Batch control part 4: batch production records (88.00.04-2006)

    Google Scholar 

  34. International Society of Automation (2010) Enterprise-control system integration: part 1: models and terminology (95.00.01-2010 (IEC 62264-1 Mod))

    Google Scholar 

  35. International Society of Automation (2018) Enterprise-control system integration: part 2: objects and attributes for enterprise-control system integration (95.00.02-2018)

    Google Scholar 

  36. International Society of Automation (2013) Enterprise-control system integration: part 3: activity models of manufacturing operations management (95.00.03-2013)

    Google Scholar 

  37. International Society of Automation (2018) Enterprise-control system integration: part 4: objects and attributes for manufacturing operations management integration (95.00.04-2018)

    Google Scholar 

  38. International Society of Automation (2018) Enterprise-control system integration: part 5: business-to-manufacturing transactions (95.00.05-2018)

    Google Scholar 

  39. International Society of Automation. Enterprise-control system integration: part 6: messaging service model (95.00.06-2014)

    Google Scholar 

  40. International Society of Automation (2017) Enterprise-control system integration: part 7: alias service model (95.00.07-2017)

    Google Scholar 

  41. International Society of Automation (2015) Machine and Unit States: an implementation example of ANSI/ISA-88.00.01(TR88.00.02-2015)

    Google Scholar 

  42. International Society of Automation. Procedure automation for continuous process operations: models and terminology (106.00.01)

    Google Scholar 

  43. International Society of Automation (2017) Procedure automation for continuous process operations: work processes (106.00.02-2017)

    Google Scholar 

  44. International Society of Automation (2008) Using ISA-88 and ISA-95 together (88.95.01-2008)

    Google Scholar 

  45. International Society of Automation. Enterprise-control system integration: TR01: master data profile template (95.01-2018)

    Google Scholar 

  46. International Society of Automation (2015) Human machine interfaces for process automation systems (101.01-2015)

    Google Scholar 

  47. ZVEI – Zentralverband Elektrotechnik- und Elektronikindustrie e. V. (2015) Modulbasierte Produktion in der Prozessindustrie – Auswirkungen auf die Automation im Umfeld von Industrie 4.0: Empfehlungen des AK Modulare Automation zur NE 148 der Namur, Frankfurt am Main

    Google Scholar 

  48. International Organization for Standardization (2015) Quality management systems: requirements (9001:2015)

    Google Scholar 

  49. International Organization for Standardization (2018) Energy management systems: requirements with guidance for use (50001:2018)

    Google Scholar 

  50. International Organization for Standardization (2018) Occupational health and safety management systems: requirements with guidance for use (45001:2018)

    Google Scholar 

  51. International Organization for Standardization (2018) Food safety management (22000:2018)

    Google Scholar 

  52. International Organization for Standardization (2013) Food safety management systems: requirements for bodies providing audit and certification of food safety management systems (22003:2013)

    Google Scholar 

  53. International Organization for Standardization (2007) Traceability in the feed and food chain: general principles and basic requirements for system design and implementation (22005:2007)

    Google Scholar 

  54. Deutsches Institut für Normung e.V. (2000) Chargenorientierte Fahrweise: Teil 1: Modelle und Terminologie (61512)

    Google Scholar 

  55. International Electrotechnical Commission (1997) Batch control: part 1: models and terminology (61512-1:1997)

    Google Scholar 

  56. International Society of Automation (1996) Possible recipe procedure presentation formats (88.0.03-1996)

    Google Scholar 

  57. Heidel R, Hoffmeister M, Hankel M et al (2017) Industrie4.0 Basiswissen RAMI4.0: Referenzarchitekturmodell mit Industrie4.0-Komponente, 1st edn. VDE Verlag GmbH; Beuth Verlag GmbH, Berlin, Wien, Zürich

    Google Scholar 

  58. Affairs and Energy, Federal Ministry for Economics (2020) Project GAIA-X. https://www.bmwi.de/Redaktion/EN/Publikationen/Digitale-Welt/project-gaia-x.html. Accessed 21 Apr 2020

  59. Otto B, Steinbuß S, Teuscher A, Lohmann S (2019) Reference architekture model 2019: version 3.0. https://www.internationaldataspaces.org/wp-content/uploads/2019/03/IDS-Reference-Architecture-Model-3.0.pdf. Accessed 30 Mar 2020

  60. Tools.ietf.org, Rfcmarkup Version 1.129d On (2020) RFC 3987 – Internationalized Resource Identifiers (IRIs). https://tools.ietf.org/html/rfc3987. Accessed 21 Apr 2020

  61. (2020) eCl@ss: home. https://www.eclass.eu/en/index.html. Accessed 21 Apr 2020

  62. International Electrotechnical Commission (2017) Standard data element types with associated classification scheme: part 1: definitions – principles and methods (61360-1:2017)

    Google Scholar 

  63. The World Wide Web Consortium (2018) XML schema part 2: datatypes second edition. https://www.w3.org/TR/xmlschema-2/. Accessed 21 Apr 2020

  64. Wang XV, Wang L (2019) Digital twin-based WEEE recycling, recovery and remanufacturing in the background of industry 4.0. Int J Prod Res 57:3892–3902. https://doi.org/10.1080/00207543.2018.1497819

    Article  Google Scholar 

  65. Wagner C, Grothoff J, Epple U et al (2017) The role of the industry 4.0 asset administration shell and the digital twin during the life cycle of a plant: September 12–15, 2017, Limassol, Cyprus: 1–8. https://doi.org/10.1109/ETFA.2017.8247583

  66. Otto B, ten Homplel M, Wrobel S (2018) Industrial Data Spaces: Referenzarchitektur für die Digitalisierung der Wirtschaft. In: Neugebauer R (ed) Digitalisierung: Schlüsseltechnologien für Wirtschaft und Gesellschaft, 1st edn. Springer, Berlin, pp 113–133

    Google Scholar 

  67. Capiello C, Gal A, Jarke M et al (2020) Data ecosystems: sovereign data exchange among organizations (Dagstuhl Seminar 19391). https://doi.org/10.4230/DAGREP.9.9.66

  68. Steinmetz C, Rettberg A, Ribeiro FGC et al (2018) Internet of things ontology for digital twin in cyber physical systems. In: SBESC 2018: 2018 VIII Brazilian symposium on computing systems engineering: proceedings: Salvador, Brazil, 6–9 November 2018. Conference Publishing Services, IEEE Computer Society, Los Alamitos, CA, pp 154–159

    Google Scholar 

  69. Jung C, Eitel A, Schwarz R (2014) Enhancing cloud security with context-aware usage control policies. In: Plödereder E, Grunske L, Schneider E et al (eds) Informatik 2014: Big Data – Komplexität meistern: 22–26 September 2014, Stuttgart: proceedings. Gesellschaft für Informatik, Bonn, pp 211–222

    Google Scholar 

  70. Bussard L, Neven G, Preiss F-S (2010) Downstream usage control. In: IEEE international symposium on policies for distributed systems and networks (POLICY), 2010: 21–23 July 2010, Fairfax, Virginia, USA; proceedings. IEEE, Piscataway, NJ, pp 22–29

    Google Scholar 

  71. Zrenner J, Möller FO, Jung C et al (2019) Usage control architecture options for data sovereignty in business ecosystems. J Enterprise Inform Manag 32:477–495. https://doi.org/10.1108/JEIM-03-2018-0058

    Article  Google Scholar 

  72. International Data Spaces e.V. https://www.internationaldataspaces.org. Accessed 23 Jun 2020

  73. (2020) DIN SPEC 27070:2020-03, Anforderungen und Referenzarchitektur eines Security Gateways zum Austausch von Industriedaten und Diensten. https://doi.org/10.31030/3139499

  74. (2020) Home|Industrie 4.0 Recht-Testbed. https://legaltestbed.org/en/start/. Accessed 21 Apr 2020

  75. unn | UNITED NEWS NETWORK GmbH (2020) Die Bedeutung von IDS für die Europäische Digital-Wirtschaft. https://www.pressebox.de/pressemitteilung/industrial-data-space-e-v/Die-Bedeutung-von-IDS-fuer-die-Europaeische-Digital-Wirtschaft/boxid/993608. Accessed 21 Apr 2020

  76. Siemens AG (2020) MindSphere. https://siemens.mindsphere.io. Accessed 28 May 2020

  77. Werner R, Beugholt A, Takacs R, Geier D, Becker T, Sollacher R, Mauermann M, Weißenberg N, Roest M, Istaitih J (2020) Standardized digitalization of an existing pudding production by introducing a digital twin management system. International Dairy Magazine

    Google Scholar 

  78. Copa Cogeca, CEMA, Fertilizers Europe et al (2018) EU code of conduct on agriculture data sharing: Guidelines for correct use of agriculture data. http://www.fao.org/family-farming/detail/en/c/1127623/. Accessed 28 May 2020

  79. Tebbje S, Karthikeyan G, Friesen M et al Entwicklung einer IT-Sicherheitsinfrastruktur für verteilte Automatisierungssysteme: Schlussbericht zu IGF-Vorhaben Nr. 19117 N. https://serwiss.bib.hs-hannover.de/frontdoor/deliver/index/docId/1626/file/Schlussbericht_V31.pdf. Accessed 27 May 2020

  80. Singh S, Shehab E, Higgins N et al (2018) Challenges of digital twin in high value manufacturing. In: SAE technical paper series. SAE International400 commonwealth drive, Warrendale, PA, USA

    Google Scholar 

  81. Colombo AW, Karnouskos S, Kaynak O et al (2017) Industrial cyberphysical systems: a backbone of the fourth industrial revolution. EEE Ind Electron Mag 11:6–16. https://doi.org/10.1109/MIE.2017.2648857

    Article  Google Scholar 

  82. Biffl S, Eckhart M, Lüder A et al (2019) Security and quality in cyber-physical systems engineering: with forewords by Robert M. Lee and Tom Gilb, 1st edn. Springer, Cham

    Google Scholar 

  83. Werner R, Beugholt B, Takacs R et al (2020) Digitalisierung einer bestehenden Puddingproduktion – Implementierung eines Managementsystems für digitale Zwillinge. molkerei-industrie: 24–28

    Google Scholar 

  84. EIT Food (2020) https://www.eitfood.eu/innovation/projects/the-development-of-organic-supply-chains-that-drive-fair-transparent-and-healthy-options-for-the-consumer-2020. Accessed 21 Apr 2020

  85. Über den CCIT (2020) https://www.cit.fraunhofer.de/de/ueber-ccit.html. Accessed 21 Apr 2020

  86. Haße H, Li B, Weißenberg N et al (2019) Digital twin for real-time data processing in logistics. Proceedings of the Hamburg international conference of logistics (HICL). https://doi.org/10.15480/882.2462

  87. Susto GA, Schirru A, Pampuri S et al (2015) Machine learning for predictive maintenance: a multiple classifier approach. IEEE Trans Ind Inf 11:812–820. https://doi.org/10.1109/TII.2014.2349359

    Article  Google Scholar 

  88. Rajesh PK, Manikandan N, Ramshankar CS et al (2019) Digital twin of an automotive brake pad for predictive maintenance. Procedia Comput Sci 165:18–24. https://doi.org/10.1016/j.procs.2020.01.061

    Article  Google Scholar 

  89. Uhlemann TH-J, Lehmann C, Steinhilper R (2017) The digital twin: realizing the cyber-physical production system for industry 4.0. Procedia CIRP 61:335–340. https://doi.org/10.1016/j.procir.2016.11.152

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Chair of Brewing and Beverage Technology, Technical University of Munich, Munich, Germany

    Roman Werner, Ronny Takacs, Dominik Geier & Thomas Becker

  2. Fraunhofer Institute for Software and Systems Engineering, ISST, Dortmund, Germany

    Norbert Weißenberg & Hendrik Haße

  3. Siemens AG, Munich, Germany

    Rudolf Sollacher, Michael Thalhofer, Bernhard Schumm & Ines Steinke

Authors
  1. Roman Werner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ronny Takacs
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dominik Geier
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Thomas Becker
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Norbert Weißenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hendrik Haße
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rudolf Sollacher
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Michael Thalhofer
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Bernhard Schumm
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ines Steinke
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dominik Geier .

Editor information

Editors and Affiliations

  1. Institute of Chemical, Environmental and Bioscience Engineering, Vienna University of Technology, Wien, Austria

    Christoph Herwig

  2. Institute of Bioprocess and Biosystems Engineering, Hamburg University of Technology, Hamburg, Germany

    Ralf Pörtner

  3. Institute of Bioprocess and Biosystems Engineering, Hamburg University of Technology, Hamburg, Germany

    Johannes Möller

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Werner, R. et al. (2020). The Challenge of Implementing Digital Twins in Operating Value Chains. In: Herwig, C., Pörtner, R., Möller, J. (eds) Digital Twins. Advances in Biochemical Engineering/Biotechnology, vol 177. Springer, Cham. https://doi.org/10.1007/10_2020_153

Download citation

Publish with us

Policies and ethics

Search

Navigation