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«Quantifying the effect of using BIM and COBie for facility management on work order processing times: a case study Sarel, Lavy1 and Nishaant, Saxena2 ...»

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This contradiction in the findings is significant because most of the earlier studies utilized interviews and surveys to determine potential savings, while this study utilized actual work order processing data to derive its conclusions. Nevertheless, the findings of this study may not necessarily convey an accurate scenario for facilities that use BIM for FM, as there were significant limitations associated with standardization in recording work orders throughout the various campuses. Hence, in order to validate the effects of using BIM and COBie data for FM, it would be important for owners and facility managers to establish standard procedures from the very beginning of a project to accurately collect and record work order data. Using BIM and COBie data for FM is helpful in data integration for FM and it may help to solve problems with interoperability, data storage, etc. that reduce efficiency of O&M activities. However, with the integration of BIM and COBie data into the CMMS, the battle against inefficiency in FM is only half won. Efficient use of BIM for FM will require more effort in the form of process improvement during the early adoption stages. This research shows that in order to extract the best results from data integration, consistent data recording and periodic data validation are necessary.

This paper focuses on work order processing times to determine the benefits of using BIM and COBie-based data for FM. In order to fully understand the real value addition of using BIM and COBie for FM, future research should consider additional factors, such as user satisfaction, ease of use, time difference in accessing information for a building system/component, frequency of accessing information for a system/component, and the corresponding effects on work order processing times. In addition, future research may also consider determining the appropriate data field/s to be tracked for O&M processes based on factors such as building size, building type, geographic location, expected life of the building, expected return from implementing the BIM and COBie based FM process, and correspondence with an organization’s goals.

Acknowledgements

The researchers would like to express their deepest gratitude to Mr. Mark Cervenka, facility manager of TAMHSC, for sharing data used in this study. Additionally, the researchers are thankful to Mr. Hyde Griffith and Mr. Matt Moore, Broaddus & Associates, for their support in this study.

Industry Response (By Mr. Hyde Griffith, Broaddus and Associates, personal communication 05/13/2015): These observations will move the industry forward with improved processes, standards, and outcomes.

The findings of this research do not show positive results. That is not disputed. However, many factors and forced assumptions contribute to these negative results. We must mitigate these factors by continue to work toward solutions. Early Adopters are challenged to produce return on investment (ROI) and justifications. This work must show us what adjustments are warranted, as this research demonstrates that metrics must be established in advance for outcome quantification.

Preventive vs. corrective maintenance analysis: Previously, we concluded and advised that these should be classified separately. In the current study, that could not be done, and therefore, impacted the results. A more true analysis could have been done with normalized work order (WO) classification. FM system improvement is needed in using the CMMS. It is not enough to specify, capture, organize, validate, and transfer data. Operational use must be aligned to measure the value of the process itself. WO duration is the prime data element in this research. Better process controls at the work order level are needed. Even with mobile technology, this boils down to human factors of time recording.

References Beatty, R., Eastman, C., Kim, K., & Fang, Y. (2013). Case Study 2: Texas A&M Health Science Center-A Case Study of BIM and COBie for Facility Management. In Teicholz. P.

(Eds.), BIM for Facility Managers, 164-184. John Wiley & Sons, International Facility Management Association.

Becerik-Gerber, B., Jazizadeh, F., Li, N., & Calis, G. (2011). Application areas and data requirements for BIM-enabled facilities management. Journal of construction engineering and management, 138(3), 431-442.

Becerik-Gerber, B., & Rice, S. (2010). The perceived value of building information modeling in the US building industry. Journal of information technology in Construction, 15(2), 185Giel, B., & Issa, R. R. (2014) A Framework for Evaluating the BIM Competencies of Building Owners. In Issa, R. R., & Flood. I. (Eds.) Computing in Civil and Building Engineering, Edition 1(3), (pp. 552-559). Orlando, Florida, U.S.A.

Jawadekar, S. P. (2012). A Case Study of the Use of BIM and Construction Operations Building Information Exchange (COBie) for Facility Management (Master’s Thesis). Texas A&M University, College Station, Texas, U.S.A.

Kasprzak, C., & Dubler, C. (2012). Aligning BIM with FM: streamlining the process for future projects. Australasian Journal of Construction Economics and Building, 12(4), 68-77.

Lavy, S., & Jawadekar, S. (2014). A Case Study of Using BIM and COBie for Facility Management. International Journal of Facility Management, 5(2).

Lucas, J., Bulbul, T., Thabet, W., & Anumba, C. (2012). Case Analysis to Identify Information Links between Facility Management and Healthcare Delivery Information in a Hospital Setting. Journal of Architectural Engineering, 19(2), 134-145.

Lucas, J., Bulbul, T., & Thabet, W. (2013). An object-oriented model to support healthcare facility information management. Automation in Construction, 31, 281-291.

Shen, W., Hao, Q., Mak, H., Neelamkavil, J., Xie, H. Dickinson, J., Thomas, R., Pardasani, A., & Xue, H. (2010). Systems integration and collaboration in architecture, engineering, construction, and facilities management: A review. Advanced Engineering Informatics, 24(2), 196-207.

U.S. Army Corps of Engineers, Engineer Research and Development Center (ERDC). (2006).

Building Information Modeling (BIM): A Road Map for Implementation To Support MILCON Transformation and Civil Works Projects within the U.S. Army Corps of Engineers (ERDC TR-06-10). U.S. Army Engineer Research and Development Center, Construction Engineering Research Laboratory and Information Technology Laboratory, U.S Department of Commerce Technology Administration, National Institute of Standards and Technology (NIST). (2004). Cost analysis of inadequate interoperability in the US capital

facilities industry (NIST Publication GCR 04-867). Retrieved from:

http://fire.nist.gov/bfrlpubs/build04/PDF/b04022.pdf.

U.S Department of Commerce, National Institute of Standards and Technology (NIST). (2007).

General Buildings Information Handover Guide. Principles, Methodology and Case Studies (NISTIR 7417). Retrieved from: http://www.wbdg.org/pdfs/nistir_7417.pdf.

U.S. General Services Administration (2011). “GSA Building Information Modeling Guide Series:

08 – GSA BIM Guide for Facility Management.” Report Series 08 V.1, Office of Design and Construction, Public Buildings Service, U.S. General Services Administration,

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