Skip to main content
SpringerLink
Log in

Evaluation Model for Assessment of Cyber-Physical Production Systems

  • Chapter
  • First Online:
Industrial Internet of Things

Part of the book series: Springer Series in Wireless Technology ((SSWT))

Abstract

Cyber-physical production systems based on technologies such as machine to machine communication, the Internet of Things and other cutting edge technologies are going to advance manufacturing automation and industrial production. Information technology seems once again to be the driving force for change in manufacturing automation. But what are the characteristics of such systems in comparison to the existing approaches? In this article we recommend an evaluation model for cyber-physical production systems is proposed based on a set of system characteristics, which defines specific abilities and performance indicators. Furthermore, an analysis and verification of that model is presented sketching the typical pattern and impact of cyber-physical production systems. As a result a refined evaluation model is available, suitable for the characterization of cyber-physical technologies and thereby enabling a technological assessment.

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 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 299.99
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. Austin RD, DeMarco T, Lister TR (1996) Measuring and managing performance in organizations. Dorset House Publishing, New York

    Google Scholar 

  2. Baccarini D (1996) The concept of project complexity–a review. Int J Project Manage 14:201–204

    Article  Google Scholar 

  3. Ball M, Callaghan V (2012) Explorations of autonomy: an investigation of adjustable autonomy in intelligent environments. In: Proceedings of the 8th international conference on intelligent environments (IE), Guanajuato, Mexico, 26–29 June 2012, IEEE. doi:10.1109/IE.2012.62

  4. Belassi W, Tukel OI (1996) A new framework for determining critical success/failure factors in projects. Int J Project Manage 14(3):141–151. doi:10.1016/0263-7863(95)00064-X

    Article  Google Scholar 

  5. Bi ZM, Lang SY, Shen W, Wang L (2008) Reconfigurable manufacturing systems: the state of the art. Int J Prod Res 46(4):967–992

    Article  MATH  Google Scholar 

  6. BusinessDictionary.com: Production Efficiency. WebFinance, Inc. http://www.businessdictionary.com/definition/production-efficiency.html. Accessed 09 Apr 2016

  7. Cakar E, Mnif M, Müller-Schloer C, Richter U, Schmeck H (2007) Towards a quantitative notion of self-organisation. In: Proceedings of the IEEE congress on evolutionary computation (CEC 2007), Singapore, Singapore, 28–28 September 2007. doi:10.1109/CEC.2007.4425022

  8. Chidamber S, Kemerer C (1994) A metrics suite for object oriented design. IEEE Trans Softw Eng 20(6):476–493. doi:10.1109/32.295895

    Article  Google Scholar 

  9. DKE VDE (2015) German standardisation roadmap Industrie 4.0. DKE, VDE: Die Deutsche Normungs-Roadmap Industrie 4.0. Version 2.0 (Stand October 2015)

    Google Scholar 

  10. Dryden J (2015) Autonomy. In: Internet encyclopaedia of philosophy—a peer reviewed academic resource. http://www.iep.utm.edu/autonomy/ Accessed 25 Oct 2014

  11. ElMaraghy HA, Wiendahl HP (2009) Changeability—an introduction. In: ElMaraghy HA (ed) Changeable and reconfigurable manufacturing systems. Springer series in advanced manufacturing. Springer, London, pp 17–18

    Google Scholar 

  12. Farrell MJ (1957) The measurement of productive efficiency. J Roy Stat Soc Ser A (General) 120(3):253–290

    Google Scholar 

  13. Geisberger E, Broy M (eds.) (2012) Agenda CPS: Integrierte Forschungsagenda Cyber-Physical Systems, vol 1. Springer, Heidelberg

    Google Scholar 

  14. Gronau N, Lämmer A, Andresen K (2007) Entwicklung wandlungsfähiger Auftragsabwicklungssysteme. Wandlungsfähige ERP-Systeme: Entwicklung, Auswahl und Methoden, p 45

    Google Scholar 

  15. Halstead MH (1977) Elements of software science. Elsevier, Amsterdam

    MATH  Google Scholar 

  16. Heisel U, Meitzner M (2006) Progress in reconfigurable manufacturing systems. In: Reconfigurable manufacturing systems and transformable factories. Springer, Berlin, pp 47–62

    Google Scholar 

  17. Hofmann S, Rollwagen I, Schneider S (2007) Germany 2020—new challenges of a land on expedition. https://www.dbrsearch.com/PROD/DBR_INTERNET_ENPROD/PROD000000000021082/Germany_2020_New_challenges_for_a_land_on_expedi.pdf. Accessed 16 Oct 2015

  18. Hohnen T, Pollmanns J, Feldhusen J (2013) Cost-effects of product modularity–an approach to describe manufacturing costs as a function of modularity. In: Smart product engineering. Springer, Berlin, pp 745–754

    Google Scholar 

  19. ISO 13482:2014: Robots and robotic devices—safety requirement for personal care robots. Autonomy: “Ability to perform intended tasks based on current state and sensing, without human intervention”

    Google Scholar 

  20. ISO 22400-2:2014: Automation systems and integration—key performance indicators (KPIs) for manufacturing operations management

    Google Scholar 

  21. ISO/IEC 15438: (ISO/IEC 15416) Information technology—automatic identification and data capture techniques

    Google Scholar 

  22. Jazdi N (2014) Cyber-physical systems in the context of industry 4.0. In: IEEE international conference on automation, quality and testing, robotics, Cluj-Napoca, Romania

    Google Scholar 

  23. Kagermann H, Wahlster, W, Helbig J (2013) Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0. Abschlussbericht des Arbeitskreises Industrie, 4

    Google Scholar 

  24. Kagermann H, Helbig J, Hellinger A, Wahlster W (2013). Recommendations for Implementing the strategic initiative INDUSTRIE 4.0: securing the future of German manufacturing industry; final report of the Industrie 4.0 working group. Forschungsunion

    Google Scholar 

  25. Kennzahlen. www.vdma.org/documents/…/63acfab3-4546-4e1a-b396-1551f53f9c32. Accessed 15 Oct 2015

  26. Klocke F, Backmeyer M, Blattner M, Eisenblätter G, Jamal R, Joseph Y., Trächtler A (2014) Sensoren in der digitalen Produktion. In: Brecher C, Klocke F, Schmitt R, Schuh G (eds) Industrie 4.0: Aachener Perspektiven: Aachener Werkzeugmaschinenkolloquium 2014, 1st edn. Shaker, Herzogenrath, pp 271–96

    Google Scholar 

  27. Lass S, Theuer H, Gronau N (2012) A new approach for simulation and modelling of autonomous production processes. In: Proceedings of the 45th Hawaii international conference on system science (HICSS), Maui, Hawaii, 4–7 January 2012. IEEE

    Google Scholar 

  28. Lee EA (2006) Cyber-physical systems—are computing foundations adequate. Position paper for national science foundation workshop on cyber-physical systems, 16 October 2006, Austin, TX, USA

    Google Scholar 

  29. Lee EA (2008). Cyber physical systems: design challenges. In: 2008 11th IEEE international symposium on Object oriented real-time distributed computing (ISORC), May 2008. IEEE, pp 363–369

    Google Scholar 

  30. Legat C, Steden F, Feldmann S, Weyrich M, Vogel-Heuser B (2014) Co-evolution and reuse of automation control and simulation software: identification and definition of modification actions and strategies. In: IECON 2014—40th annual conference of the IEEE industrial electronics society, pp 2525–2531

    Google Scholar 

  31. Leitao P (2009) Agent-based distributed manufacturing control: a state-of-the-art survey. Eng Appl Artif Intell 22(7):979–991

    Article  MathSciNet  Google Scholar 

  32. Mitchell M (2009) Complexity a guided tour. Oxford University Press, Oxford, p 366

    MATH  Google Scholar 

  33. Neely A, Gregory M, Platts K (2005) Performance measurement system design: a literature review and research agenda. Int J Oper Prod Manage 25(12):1228–1263. doi:10.1108/01443570510633639

    Article  Google Scholar 

  34. Nyhuis P, Fronia P, Pachow-Frauenhofer J, Wulf S (2009) Wandlungsfähige Produktionssysteme–Ergebnisse der BMBF-Vorstudie “Wandlungsfähige Produktionssysteme”. wt Werkstattstechnik online 99 (2009) Nr. 4, pp 205–210. Internet: www.werkstattstechnik.de. Springer-VDI-Verlag, Düsseldorf

  35. Parasuraman R, Sheridan TB, Wickens CD (2000) A model for types and levels of human interaction with automation. IEEE Trans Syst Man Cybern Part A Syst Hum 30(3):286–297. doi:10.1109/3468.844354

    Article  Google Scholar 

  36. Piper M (2015) Autonomy (normative). In: Internet encyclopaedia of philosophy—a peer reviewed academic resource. http://www.iep.utm.edu/aut-norm/. Accessed 25 Oct 2014

  37. Porter ME, Heppelmann JE (2014) How smart, connected products are transforming competition. Harv Bus Rev 92(11):11–64

    Google Scholar 

  38. Rother M, Harris R (2001) Creating continuous flow. Lean Enterprise Institute, Brookline

    Google Scholar 

  39. Ruiu M, Ullrich A, Weber E (2012) Change capability as a strategic success factor-a behavior pattern approach for operationalizing change capability. In: Proceedings of the conference on strategic management, pp 23–31

    Google Scholar 

  40. Samsonowa T (2012) Industrial research performance management: Key performance indicators in the ICT industry. Contributions to management science. Physica-Verlag, Heidelberg

    Google Scholar 

  41. Scholz-Reiter B, Sowade, S (2010) Der Beitrag der Selbststeuerung zur Wandlungsfähigkeit von Produktionssystemen. http://www.sfb637.uni-bremen.de/pubdb/repository/SFB637-B2-10-005-IIC.pdf, Accessed 16 Oct 2015

  42. Stryker AC (2010) Development of measures to assess product modularity and reconfigurability. Dissertation, Wright-Patterson Air Force Base, Ohio

    Google Scholar 

  43. Takeda H (2006) Das synchrone Produktionssystem. Just-in-Time für das ganze Unternehmen; 5, aktualisierte Auflage; Verlag Moderne Industrie; Landsberg

    Google Scholar 

  44. VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (2014) Statusbericht; Industrie 4.0; Gegenstände, Entitäten, Komponenten. VDI e.V., Düsseldorf. https://www.vdi.de/fileadmin/vdi_de/redakteur_dateien/sk_dateien/VDI_Industrie_4.0_Komponenten_2014.pdf. Accessed 9 Oct 2015

  45. VDMA-Einheitsblatt 66412-1 (2009) Manufacturing Execution Systems (MES)

    Google Scholar 

  46. Vogel-Heuser B, Weber J, Folmer J (2015) Evaluating reconfiguration abilities of automated production systems in Industrie 4.0 with metrics. In: Proceedings of the IEEE 20th conference on emerging technologies and factory automation (ETFA 2015), Luxembourg, Luxembourg, 8–11 September 2015. IEEE

    Google Scholar 

  47. Wahlster W (2014) Industrie 4.0-Künstliche Intelligenz in der Produktion, Konferenz zu Ideen 2020, 03 February 2014, Saarbrücken

    Google Scholar 

  48. Wahlster W (2014) Normung und Standardisierung-Schlüssel zum Erfolg von Industrie 4.0. In: Workshop Plattform I40 und DKE, 18 February 2014, Berlin

    Google Scholar 

  49. Weyrich M, Klein P, Steden F (2014) Reuse of modules for mechatronic modeling and evaluation of manufacturing systems in the conceptual design and basic engineering phase. In: IFAC world

    Google Scholar 

  50. Weyrich M, Wior I, Bchennati D, Fay A (2014) Flexibilisierung von Automatisierungssystemen: Systematisierung der Flexibilitätsanforderungen von Industrie 4.0; wt-online 3–2014, pp 106–111

    Google Scholar 

  51. Weyrich M, Diedrich C, Fay A, Wollschläger M, Kowalewski S, Göhner P, Vogel-Heuser B (2014) Industrie 4.0 am Beispiel einer Verbundanlage. Automatisierungstechnische Praxis (atp) 56(7):52–61

    Google Scholar 

  52. Wiendahl H, ElMaraghy HA, Nyhuis P, Zäh MF, Wiendahl H, Duffie N, Brieke M (2007) Changeable manufacturing—classification, design and operation. CIRP Ann Manuf Technol 56(2):783–809. doi:10.1016/j.cirp.2007.10.003

    Article  Google Scholar 

  53. Windt K (2008) Ermittlung des angemessenen Selbststeuerungsgrades in der Logistik-Grenzen der Selbststeuerung. In: Nyhuis P (ed) Beiträge zu einer Theorie der Logistik. Springer, Berlin, pp 349–372

    Chapter  Google Scholar 

  54. Windt K, Hülsmann M (2007) Changing paradigms in logistics—understanding the shift from conventional control to autonomous cooperation and control. In: Understanding autonomous cooperation and control in logistics. Springer, Heidelberg, pp 1–16

    Google Scholar 

  55. Zuehlke D (2010) SmartFactory—towards a factory-of-things. Ann Rev Control 34(1):129–138. doi:10.1016/j.arcontrol.2010.02.008

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Industrial Automation and Software Engineering, University of Stuttgart, Pfaffenwaldring 47, 70569, Stuttgart, Germany

    Michael Weyrich, Matthias Klein, Jan-Philipp Schmidt & Nasser Jazdi

  2. Siemens Corporation, 755 College Road East, Princeton, New Jersey, 08540, USA

    Kurt D. Bettenhausen

  3. Siemens AG, Otto-Hahn-Ring 6, 81739, Munich, Germany

    Frank Buschmann, Michael Pirker & Kai Wurm

  4. Siemens AG, Günther-Scharowsky-Str. 1, 91058, Erlangen, Germany

    Carolin Rubner

Authors
  1. Michael Weyrich
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Matthias Klein
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jan-Philipp Schmidt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nasser Jazdi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kurt D. Bettenhausen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Frank Buschmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Carolin Rubner
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Michael Pirker
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Kai Wurm
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael Weyrich .

Editor information

Editors and Affiliations

  1. RWTH Aachen University, Aachen, Germany

    Sabina Jeschke

  2. RWTH Aachen University, Aachen, Germany

    Christian Brecher

  3. West Virginia University, Montgomery, West Virginia, USA

    Houbing Song

  4. Howard University, Washington, District of Columbia, USA

    Danda B. Rawat

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Weyrich, M. et al. (2017). Evaluation Model for Assessment of Cyber-Physical Production Systems. In: Jeschke, S., Brecher, C., Song, H., Rawat, D. (eds) Industrial Internet of Things. Springer Series in Wireless Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-42559-7_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-42559-7_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42558-0

  • Online ISBN: 978-3-319-42559-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation