Benefits and Challenges Using BIM for Operation and Maintenance

  • Bruno DaniottiEmail author
  • Alberto Pavan
  • Sonia Lupica Spagnolo
  • Vittorio Caffi
  • Daniela Pasini
  • Claudio Mirarchi
Part of the Springer Tracts in Civil Engineering book series (SPRTRCIENG)


Considering the remarkable shift that the digitalisation is nowadays bringing about in the building sector, the chapter presents how data and information collected and managed during design and construction stages improve building operation and maintenance. In particular, the chapter focuses on how the great amount of dynamic data collected around assets during the operational stage is changing the way buildings are experienced and managed. The integration and sharing of information supported by collaborative environments and recent information technologies enhance the management of the built asset. Within that context, the chapter outlines benefits and challenges in adopting BIM-based processes for the operation and maintenance of buildings. Particularly, the chapter presents how an ordered and structured information management allows delivering buildings as service providers, extracting knowledge from real-time data for tracking user behaviours and designing user interactions with buildings. The results allow: (1) implementing workflows for enriching building information in the operational stage and, consequently, operating buildings with an increased value originated by information. (2) Assessing how buildings work in the operational stage, especially taking into consideration the influence of users. (3) Defining strategies for engaging different actors in building operations and informing them about the behaviours of both buildings and users. (4) Providing control strategies when unexpected behaviours (e.g., energy-hungry behaviours, unusual comfort conditions and FM-related failures) are registered. Considering the concept of Industry 4.0, also the collection, storage and fruition of data collected in real-time is considered for an improved building operation and maintenance.


  1. 1.
    Becerik-Gerber B, Jazizadeh F, Li N, Calis G (2011) Application areas and data requirements for BIM-enabled facilities management. J Constr Eng Manage 138(3):431–442CrossRefGoogle Scholar
  2. 2.
    Chen W, Chen K, Cheng JC, Wang Q, Gan VJ (2018) BIM-based framework for automatic scheduling of facility maintenance work orders. Autom Constr 91:15–30CrossRefGoogle Scholar
  3. 3.
    Cavka HB, Staub-French S, Poirier EA (2017) Developing owner information requirements for BIM-enabled project delivery and asset management. Autom Constr 83:169–183. Scholar
  4. 4.
    Dave B, Buda A, Nurminen A, Främling K (2018) A framework for integrating BIM and IoT through open standards. Autom Constr 95:35–45. Scholar
  5. 5.
    Deutsch R (2015) Data-driven design and construction: 25 strategies for capturing, analyzing and applying building data. Wiley, Hoboken, NJGoogle Scholar
  6. 6.
    Gallaher MP, O’Conor AC, Dettbarn JL, Gilday LT (2004) Cost analysis of inadequate interoperability in the U.S. Capital Facilities Industry, National Institute of Standards & Technology, GaithersburgGoogle Scholar
  7. 7.
    Gerrish T, Ruikar K, Cook M, Johnson M, Phillip M, Lowry C (2017) BIM application to building energy performance visualisation and management: challenges and potential. Energy Build 144:218–228CrossRefGoogle Scholar
  8. 8.
    Gruber TR (1995) Toward principles for the design of ontologies used for knowledge sharing? Int J Hum Comput Stud 43(5–6):907–928CrossRefGoogle Scholar
  9. 9.
    Hong T, Taylor-Lange SC, D’Oca S, Yan D, Corgnati SP (2016) Advances in research and applications of energy-related occupant behavior in buildings. Energy Build 116:694–702. Scholar
  10. 10.
    Kaur H, Lechman E, Marszk A (eds) (2017) Catalyzing development through ICT adoption: the developing world experience. Springer, New YorkGoogle Scholar
  11. 11.
    Kim K, Kim H, Kim W, Kim C, Kim J, Yu J (2018) Integration of ifc objects and facility management work information using semantic web. Automation in Construction 87:173–187. Scholar
  12. 12.
    Kiviniemi A (2013) Value of BIM in FM/OM—why have we failed in attracting owners and operators? Last accessed on 22 July 2019
  13. 13.
    McArthur JJ, Shahbazi N, Fok R, Raghubar C, Bortoluzzi B, An A (2018) Machine learning and BIM visualization for maintenance issue classification and enhanced data collection. Adv Eng Inform 38:101–112. Scholar
  14. 14.
    Mirarchi C, Pasini D, Pavan A, Daniotti B (2017) Automated IFC-based processes in the construction sector: a method for improving the information flow. In: LC3 conference, HeraklionGoogle Scholar
  15. 15.
    Pasini D (2018) Connecting BIM and IoT for engaging users in building operation. J Struct Integrity MaintenanceGoogle Scholar
  16. 16.
    Pasini D, Mastrolembo Ventura S, Bolpagni M (2017) BIM-based process for managing property sets of objects extending the IFC schema. In: ISTeA conference, FirenzeGoogle Scholar
  17. 17.
    Pasini D, Reda F, Häkkinen T (2017) User engaging practices for energy saving in buildings: critical review and new enhanced procedure. Energy Build 148:74–88. Scholar
  18. 18.
    Peng Y, Lin JR, Zhang JP, Hu ZZ (2017) A hybrid data mining approach on BIM-based building operation and maintenance. Build Environ 126:483–495. Scholar
  19. 19.
    Pishdad-Bozorgi P, Gao X, Eastman C, Self AP (2018) Planning and developing facility management-enabled building information model (FM-enabled BIM). Autom Constr 87:22–38. Scholar
  20. 20.
    Qabshoqa M, Kocaturk T, Kiviniemi A (2017) A value-driven perspective to understand Data-driven futures in Architecture. eCAADeGoogle Scholar
  21. 21.
    Sattenini A, Azhar S, Thuston J (2011) Preparing a building information model for facility maintenance and management. In: 28th International symposium on automation and robotics in construction, Seoul, South Korea, pp 144–149Google Scholar
  22. 22.
    Young NW, Jones SA, Bernstein HM (2007) Interoperability in the construction industryGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Bruno Daniotti
    • 1
    Email author
  • Alberto Pavan
    • 2
  • Sonia Lupica Spagnolo
    • 3
  • Vittorio Caffi
    • 4
  • Daniela Pasini
    • 5
  • Claudio Mirarchi
    • 6
  1. 1.Dipartimento ABCPolitecnico di MilanoMilanItaly
  2. 2.Dipartimento ABCPolitecnico di MilanoMilanItaly
  3. 3.Dipartimento ABCPolitecnico di MilanoMilanItaly
  4. 4.Dipartimento ABCPolitecnico di MilanoMilanItaly
  5. 5.Dipartimento ABCPolitecnico di MilanoMilanItaly
  6. 6.Dipartimento ABCPolitecnico di MilanoMilanItaly

Personalised recommendations