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A Concept for Automated Construction Progress Monitoring: Technologies Adoption for Benchmarking Project Performance Control

  • Research Article - Civil Engineering
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Abstract

Despite recent advances in technologies and equipment for automated progress monitoring, most construction companies worldwide do not utilize them for their projects. This can be due to many reasons, such as the high cost of technologies and equipment, need for skilled staff, and lack of sufficient information about the impact of automated progress monitoring on project performance control. The aim of the present research is to investigate the impact of automated progress monitoring on key project performance indicators: time, cost, and quality. This study prepared based on a survey of contracting and engineering consulting firms in North America, Europe, and the Middle East. In the first part of this study, structural equation modeling is used to identify the relations of different factors of project progress monitoring (both conventional and automated) with project performance control. In the second part of the study, a benefit analysis is evaluated based on the sixteen (16) journal and international conference papers and also twenty-four (24) international construction projects for which automated progress monitoring was employed. The research findings validate the positive impact of real-time, accurate, and cost-effective automated progress monitoring environments and reveal how automated progress monitoring affects construction project success.

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References

  1. Golparvar-Fard, M.; Bohn, J.; Teizer, J.; Savarese, S.; Peña-Mora, F.: Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques. Autom. Constr. 20(8), 1143–1155 (2011)

    Article  Google Scholar 

  2. Yang, J.; Park, M.-W.; Vela, P.A.; Golparvar-Fard, M.: Construction performance monitoring via still images, time-lapse photos, and video streams: now, tomorrow, and the future. Adv. Eng. Inf. 29(2), 211–224 (2015)

    Article  Google Scholar 

  3. Hwang, B.-G.; Zhao, X.; Ng, S.Y.: Identifying the critical factors affecting schedule performance of public housing projects. Habitat Int. 38, 214–221 (2013)

    Article  Google Scholar 

  4. Kim, C.; Son, H.; Kim, C.: Automated construction progress measurement using a 4D building information model and 3D data. Autom. Constr. 31, 75–82 (2013)

    Article  Google Scholar 

  5. Bosché, F.; Ahmed, M.; Turkan, Y.; Haas, C.T.; Haas, R.: The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: The case of cylindrical MEP components. Autom. Constr. 49, 201–213 (2015)

    Article  Google Scholar 

  6. Son, H.; Bosché, F.; Kim, C.: As-built data acquisition and its use in production monitoring and automated layout of civil infrastructure: A survey. Adv. Eng. Inf. 29(2), 172–183 (2015)

    Article  Google Scholar 

  7. Zhang, C.; Arditi, D.: Automated progress control using laser scanning technology. Autom. Constr. 36, 108–116 (2013)

    Article  Google Scholar 

  8. Kim, C.; Son, H.; Kim, C.: Fully automated registration of 3D data to a 3D CAD model for project progress monitoring. Autom. Constr. 35, 587–594 (2013)

    Article  Google Scholar 

  9. Maalek, R.; Ruwanpura, J.; Ranaweera, K.: Evaluation of the state-of-the-art automated construction progress monitoring and control systems, In: Construction Research Congress 2014: Construction in a Global Network, pp. 1023–1032 (2014)

  10. Braun, A.; Borrmann, A.; Tuttas, S.; Stilla, U.: Towards automated construction progress monitoring using BIM-based point cloud processing, eWork and eBusiness in Architecture. Engineering and Construction: ECPPM 2014, 101 (2014)

    Google Scholar 

  11. Navon, R.; Sacks, R.: Assessing research issues in automated project performance control (APPC). Autom. Constr. 16(4), 474–484 (2007)

    Article  Google Scholar 

  12. Fard, M.G.; Peña-Mora, F.: Application of visualization techniques for construction progress monitoring. Computing in Civil Engineering 2007, 216–223 (2007)

    Article  Google Scholar 

  13. Meredith, J.R.; Mantel Jr., S.J.: Project management: a managerial approach. Wiley, Hoboken (2011)

    Google Scholar 

  14. Song, K.; Pollalis, S.N.; Pena-Mora, F.: Project dashboard: Concurrent visual representation method of project metrics on 3D building models. Computing in Civil Engineering 2005, 1–12 (2005)

    Google Scholar 

  15. Kerzner, H.; Kerzner, H.R.: Project management: a systems approach to planning, scheduling, and controlling. Wiley, Hoboken (2017)

    MATH  Google Scholar 

  16. Son, H.; Kim, C.: 3D structural component recognition and modeling method using color and 3D data for construction progress monitoring. Autom. Constr. 19(7), 844–854 (2010)

    Article  Google Scholar 

  17. Isaac, S.; Navon, R.: Can project monitoring and control be fully automated? Constr. Manag. Econ. 32(6), 495–505 (2014)

    Article  Google Scholar 

  18. Golparvar-Fard, M.; Peña-Mora, F.; Savarese, S.: D4AR-a 4-dimensional augmented reality model for automating construction progress monitoring data collection, processing and communication. J. Inf. Technol. Constr. 14(13), 129–153 (2009)

    Google Scholar 

  19. Alizadehsalehi, S.; Koseoglu, O.; Celikag, M.: Integration of building information modeling (bim) and laser scanning in construction industry. AEI 2015, 163–174 (2015)

    Google Scholar 

  20. Turkan, Y.; Bosche, F.; Haas, C.T.; Haas, R.: Automated progress tracking using 4D schedule and 3D sensing technologies. Autom. Constr. 22, 414–421 (2012)

    Article  Google Scholar 

  21. Alizadehsalehi, S.; Yitmen, I.; Celik, T.; Arditi, D.: The effectiveness of an integrated BIM/UAV model in managing safety on construction sites. Int. J. Occup. Saf. Ergon. (2018). https://doi.org/10.1080/10803548.2018.1504487

  22. Alizadehsalehi, S.; Yitmen, I.: The impact of field data capturing technologies on automated construction project progress monitoring. Proc. Eng. 161, 97–103 (2016)

    Article  Google Scholar 

  23. Pučko, Z.; Šuman, N.; Rebolj, D.: Automated continuous construction progress monitoring using multiple workplace real time 3D scans. Adv. Eng. Inf. 38, 27–40 (2018)

    Article  Google Scholar 

  24. Asadi, K.; Han, K.: Real-time image-to-BIM registration using perspective Alignment for Automated Construction Monitoring, In: Construction Research Congress. pp. 388–397 (2018)

  25. Han, K.K.; Golparvar-Fard, M.: Potential of big visual data and building information modeling for construction performance analytics: An exploratory study. Autom. Constr. 73, 184–198 (2017)

    Article  Google Scholar 

  26. Tuttas, S.; Braun, A.; Borrmann, A.; Stilla, U.: Evaluation of acquisition strategies for image-based construction site monitoring. Int. Arch. Photogr. Remote Sen. Spatial Inf. Sci. 41 (2016)

  27. Behnam, A.; Wickramasinghe, D.C.; Ghaffar, M.A.A.; Vu, T.T.; Tang, Y.H.; Isa, H.B.M.: Automated progress monitoring system for linear infrastructure projects using satellite remote sensing. Autom. Constr. 68, 114–127 (2016)

    Article  Google Scholar 

  28. Irizarry, J.; Costa, D.B.: Exploratory study of potential applications of unmanned aerial systems for construction management tasks. J. Manag. Eng. 32(3), 05016001 (2016)

    Article  Google Scholar 

  29. Teizer, J.: Status quo and open challenges in vision-based sensing and tracking of temporary resources on infrastructure construction sites. Adv. Eng. Inf. 29(2), 225–238 (2015)

    Article  MathSciNet  Google Scholar 

  30. Han, K.K.; Golparvar-Fard, M.: Appearance-based material classification for monitoring of operation-level construction progress using 4D BIM and site photologs. Autom. Constr. 53, 44–57 (2015)

    Article  Google Scholar 

  31. Han, K.K.; Cline, D.; Golparvar-Fard, M.: Formalized knowledge of construction sequencing for visual monitoring of work-in-progress via incomplete point clouds and low-LoD 4D BIMs. Adv. Eng. Inf. 29(4), 889–901 (2015)

    Article  Google Scholar 

  32. Braun, A.; Tuttas, S.; Borrmann, A.; Stilla, U.: A concept for automated construction progress monitoring using BIM-based geometric constraints and photogrammetric point clouds. J. Inf. Technol. Constr. (ITcon) 20(5), 68–79 (2015)

    Google Scholar 

  33. Lin, J.J.; Han, K.K.; Golparvar-Fard, M.: A framework for model-driven acquisition and analytics of visual data using UAVs for automated construction progress monitoring. Comput. Civ. Eng. 2015, 156–164 (2015)

    Google Scholar 

  34. Shahi, A.; Safa, M.; Haas, C.T.; West, J.S.: Data fusion process management for automated construction progress estimation. J. Comput. Civ. Eng. 29(6), 04014098 (2014)

    Article  Google Scholar 

  35. Tuttas, S.; Braun, A.; Borrmann, A.; Stilla, U.: Comparision of photogrammetric point clouds with bim building elements for construction progress monitoring. Int. Arch. Photogr. Remote Sens. Spatial Inf. Sci. XL-3, 341–345 (2014)

  36. Dimitrov, A.; Golparvar-Fard, M.: Vision-based material recognition for automated monitoring of construction progress and generating building information modeling from unordered site image collections. Adv. Eng. Inf. 28(1), 37–49 (2014)

    Article  Google Scholar 

  37. Han, K.K.; Golparvar-Fard, M.: Multi-sample image-based material recognition and formalized sequencing knowledge for operation-level construction progress monitoring. Comput. Civ. Build. Eng. 2014, 364–372 (2014)

    Google Scholar 

  38. Han, K.K.; Golparvar-Fard, M.: Automated monitoring of operation-level construction progress using 4D BIM and daily site photologs. In: Construction Research Congress 2014: Construction in a Global Network, pp. 1033–1042 (2014)

  39. Bosché, F.; Guillemet, A.; Turkan, Y.; Haas, C.T.; Haas, R.: Tracking the built status of MEP works: Assessing the value of a Scan-vs-BIM system. J. Comput. Civ. Eng. 28(4), 05014004 (2013)

    Article  Google Scholar 

  40. Turkan, Y.; Bosché, F.; Haas, C.T.; Haas, R.: Tracking secondary and temporary concrete construction objects using 3D imaging technologies. Comput. Civ. Eng. 2013, 749–756 (2013)

    Article  Google Scholar 

  41. Shahi, A.; Cardona, J.M.; Haas, C.T.; West, J.S.; Caldwell, G.L.: Activity-based data fusion for automated progress tracking of construction projects. In: Construction Research Congress 2012: Construction Challenges in a Flat World, pp. 838–847 (2012)

  42. Roh, S.; Aziz, Z.; Peña-Mora, F.: An object-based 3D walk-through model for interior construction progress monitoring. Autom. Constr. 20(1), 66–75 (2011)

    Article  Google Scholar 

  43. Golparvar-Fard, M.; Savarese, S.; Peña-Mora, F.: Automated model-based recognition of progress using daily construction photographs and IFC-based 4D models. In: Construction Research Congress 2010: Innovation for Reshaping Construction Practice, pp. 51–60 (2010)

  44. Motamedi, A.; Hammad, A.: RFID-assisted lifecycle management of building components using BIM data, In: Proceedings of the 26th International Symposium on Automation and Robotics in Construction, pp. 109–116 (2009)

  45. Golparvar-Fard, M.; Peña-Mora, F.; Arboleda, C.A.; Lee, S.: Visualization of construction progress monitoring with 4D simulation model overlaid on time-lapsed photographs. J. Comput. Civ. Eng. 23(6), 391–404 (2009)

    Article  Google Scholar 

  46. Hajian, H.; Becerik-Gerber, B.: A research outlook for real-time project information management by integrating advanced field data acquisition systems and building information modeling. Comput. Civ. Eng. 2009, 83–94 (2009)

    Google Scholar 

  47. Ibrahim, Y.; Lukins, T.C.; Zhang, X.; Trucco, E.; Kaka, A.: Towards automated progress assessment of workpackage components in construction projects using computer vision. Adv. Eng. Inf. 23(1), 93–103 (2009)

    Article  Google Scholar 

  48. Rebolj, D.; Babič, N.Č.; Magdič, A.; Podbreznik, P.; Pšunder, M.: Automated construction activity monitoring system. Adv. Eng. Inf. 22(4), 493–503 (2008)

    Article  Google Scholar 

  49. Hammad, A.; Motamedi, A.: Framework for lifecycle status tracking and visualization of constructed facility components. In: 7th International Conference on Construction Applications of Virtual Reality, pp. 224–232 (2007)

  50. Chan, A.P.; Scott, D.; Chan, A.P.: Factors affecting the success of a construction project. J. Constr. Eng. Manag. 130(1), 153–155 (2004)

    Article  Google Scholar 

  51. Todorović, M.L.; Petrović, D.Č.; Mihić, M.M.; Obradović, V.L.; Bushuyev, S.D.: Project success analysis framework: A knowledge-based approach in project management. Int. J. Proj. Manag. 33(4), 772–783 (2015)

    Article  Google Scholar 

  52. Pinto, J.K.; Winch, G.: The unsettling of “settled science:” the past and future of the management of projects. Int. J. Proj. Manag. 34(2), 237–245 (2016)

    Article  Google Scholar 

  53. Fahri, J.; Biesenthal, C.; Pollack, J.; Sankaran, S.: Understanding megaproject success beyond the project close-out stage. Constr. Econ. Build. 15, 48–58 (2015)

    Article  Google Scholar 

  54. Sanvido, V.; Grobler, F.; Parfitt, K.; Guvenis, M.; Coyle, M.: Critical success factors for construction projects. J. Constr. Eng. Manag. 118(1), 94–111 (1992)

    Article  Google Scholar 

  55. Atkinson, R.: Project management: cost, time and quality, two best guesses and a phenomenon, its time to accept other success criteria. Int. J. Proj. Manag. 17(6), 337–342 (1999)

    Article  Google Scholar 

  56. Guide, A.: Project Management Body of Knowledge (PMBOK\({\textregistered }\) GUIDE), In: Project Management Institute (2001)

  57. Salehi, S.A.; Yitmen, İ.: Modeling and analysis of the impact of BIM-based field data capturing technologies on automated construction progress monitoring. Int. J. Civ. Eng. 16(12), 1669–1685 (2018)

    Article  Google Scholar 

  58. Navon, R.: Automated project performance control of construction projects. Autom. Constr. 14(4), 467–476 (2005)

    Article  Google Scholar 

  59. Too, E.G.; Weaver, P.: The management of project management: A conceptual framework for project governance. Int. J. Proj. Manag. 32(8), 1382–1394 (2014)

    Article  Google Scholar 

  60. Kusters, J.: The value and necessity of the project management plan: the pre-award phase of BVP projects from the vendor’s perspective. pp. 1–16 (2016)

  61. Wang, K.-C.; Wang, W.-C.; Wang, H.-H.; Hsu, P.-Y.; Wu, W.-H.; Kung, C.-J.: Applying building information modeling to integrate schedule and cost for establishing construction progress curves. Autom. Constr. 72, 397–410 (2016)

    Article  Google Scholar 

  62. Wang, X.; Yung, P.; Luo, H.; Truijens, M.: An innovative method for project control in LNG project through 5D CAD: a case study. Autom. Constr. 45, 126–135 (2014)

    Article  Google Scholar 

  63. British Standards Institution. BS 6079–1:2010—Project Management: Principles and Guidelines for the Management of Projects. British Standards Institution, London (2010)

  64. Alotaibi, N.O.; Sutrisna, M.; Chong, H.Y.: Guidelines of using project management tools and techniques to mitigate factors causing delays in public construction projects in kingdom of Saudi Arabia. J. Eng. Proj. Prod. Manag. 6(2), 90–103 (2016)

    Google Scholar 

  65. Hazır, Ö.: A review of analytical models, approaches and decision support tools in project monitoring and control. Int. J. Proj. Manag. 33(4), 808–815 (2015)

    Article  Google Scholar 

  66. Aliverdi, R.; Naeni, L.M.; Salehipour, A.: Monitoring project duration and cost in a construction project by applying statistical quality control charts. Int. J. Proj. Manag. 31(3), 411–423 (2013)

    Article  Google Scholar 

  67. Issa, R.R.; Olbina, S.: Building Information Modeling: Applications and Practices. American Society of Civil Engineers, Reston (2015)

    Book  Google Scholar 

  68. Ham, Y.; Han, K.K.; Lin, J.J.; Golparvar-Fard, M.: Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works. Vis. Eng. 4(1), 1 (2016)

    Article  Google Scholar 

  69. Ahsan, K.; Gunawan, I.: Analysis of cost and schedule performance of international development projects. Int J. Proj. Manag. 28(1), 68–78 (2010)

    Article  Google Scholar 

  70. Kim, M.-K.; Cheng, J.C.; Sohn, H.; Chang, C.-C.: A framework for dimensional and surface quality assessment of precast concrete elements using BIM and 3D laser scanning. Autom. Constr. 49, 225–238 (2015)

    Article  Google Scholar 

  71. Zhang, X.; et al.: Automating progress measurement of construction projects. Autom. Constr. 18(3), 294–301 (2009)

    Article  Google Scholar 

  72. Azhar, S.; Nadeem, A.; Mok, J.Y.; Leung, B.H.: Building information modeling (BIM): a new paradigm for visual interactive modeling and simulation for construction projects. In: Proceedings of First International Conference on Construction in Developing Countries vol. 1, pp. 435–446 (2008)

  73. Park, J.; Cai, H.: WBS-based dynamic multi-dimensional BIM database for total construction as-built documentation. Autom. Constr. 77, 15–23 (2017)

    Article  Google Scholar 

  74. Golparvar-Fard, M.; Peña-Mora, F.; Savarese, S.: Automated progress monitoring using unordered daily construction photographs and IFC-based building information models. J. Comput. Civ. Eng. 29(1), 04014025 (2012)

    Article  Google Scholar 

  75. Son, H.; Kim, C.; Kwon Cho, Y.: Automated schedule updates using as-built data and a 4D building information model. J. Manag. Eng. 33(4), 04017012 (2017)

    Article  Google Scholar 

  76. He, Q.; Wang, G.; Luo, L.; Shi, Q.; Xie, J.; Meng, X.: Mapping the managerial areas of Building Information Modeling (BIM) using scientometric analysis. Int. J. Proj. Manag. 35(4), 670–685 (2017)

    Article  Google Scholar 

  77. Heagney, J.: Fundamentals of Project Management. Amacom, New York (2016)

    Google Scholar 

  78. Wang, S.; Tang, W.; Li, Y.: Relationship between owners’ capabilities and project performance on development of hydropower projects in China. J. Constr. Eng. Manag. 139(9), 1168–1178 (2013)

    Article  Google Scholar 

  79. Matthews, J.; Love, P.E.; Heinemann, S.; Chandler, R.; Rumsey, C.; Olatunj, O.: Real time progress management: Re-engineering processes for cloud-based BIM in construction. Autom. Constr. 58, 38–47 (2015)

    Article  Google Scholar 

  80. Duffield, S.; Whitty, S.J.: Developing a systemic lessons learned knowledge model for organisational learning through projects. Int. J. Proj. Manag. 33(2), 311–324 (2015)

    Article  Google Scholar 

  81. Martinelli, R.J.; Milosevic, D.Z.: Project Management Toolbox: Tools and Techniques for the Practicing Project Manager. Wiley, Hoboken (2016)

    Google Scholar 

  82. Patanakul, P.; Iewwongcharoen, B.; Milosevic, D.: An empirical study on the use of project management tools and techniques across project life-cycle and their impact on project success. J. Gen. Manag. 35(3), 41–66 (2010)

    Google Scholar 

  83. Jayaraman, R.: Project cost control: a new method to plan and control costs in large projects. Bus. Process Manag. J. 22(6), 1247–1268 (2016)

    Article  Google Scholar 

  84. Aibinu, A.; Jagboro, G.: The effects of construction delays on project delivery in Nigerian construction industry. Int. J. Proj. Manag. 20(8), 593–599 (2002)

    Article  Google Scholar 

  85. Narbaev, T.; De Marco, A.: An earned schedule-based regression model to improve cost estimate at completion. Int. J. Proj. Manag. 32(6), 1007–1018 (2014)

    Article  Google Scholar 

  86. Ding, L.; Li, K.; Zhou, Y.; Love, P.E.: An IFC-inspection process model for infrastructure projects: Enabling real-time quality monitoring and control. Autom. Constr. 84, 96–110 (2017)

    Article  Google Scholar 

  87. Perrenoud, A.; Lines, B.C.; Savicky, J.; Sullivan, K.T.: Using best-value procurement to measure the impact of initial risk-management capability on qualitative construction performance. J. Manag. Eng. 33(5), 04017019 (2017)

    Article  Google Scholar 

  88. Alzahrani, J.I.; Emsley, M.W.: The impact of contractors’ attributes on construction project success: A post construction evaluation. Int. J. Proj. Manag. 31(2), 313–322 (2013)

    Article  Google Scholar 

  89. Brace, I.: Questionnaire Design: How to Plan, Structure and Write Survey Material for Effective Market Research. Kogan Page Publishers, London (2018)

    Google Scholar 

  90. Xiong, B.; Skitmore, M.; Xia, B.: A critical review of structural equation modeling applications in construction research. Autom. Constr. 49, 59–70 (2015)

    Article  Google Scholar 

  91. Shih, N.-J.; Wang, P.-H.: Point-cloud-based comparison between construction schedule and as-built progress: long-range three-dimensional laser scanner’s approach. J. Arch. Eng. 10(3), 98–102 (2004)

    Article  Google Scholar 

  92. Beringer, C.; Jonas, D.; Kock, A.: Behavior of internal stakeholders in project portfolio management and its impact on success. Int. J. Proj. Manag. 31(6), 830–846 (2013)

    Article  Google Scholar 

  93. Ahlemann, F.: Towards a conceptual reference model for project management information systems. Int. J. Proj. Manag. 27(1), 19–30 (2009)

    Article  Google Scholar 

  94. Caniëls, M.C.; Bakens, R.J.: The effects of Project Management Information Systems on decision making in a multi project environment. Int. J. Proj. Manag. 30(2), 162–175 (2012)

    Article  Google Scholar 

  95. Raymond, L.; Bergeron, F.: Project management information systems: An empirical study of their impact on project managers and project success. Int. J. Proj. Manag. 26(2), 213–220 (2008)

    Article  Google Scholar 

  96. Crawford, P.; Bryce, P.: Project monitoring and evaluation: a method for enhancing the efficiency and effectiveness of aid project implementation. Int. J. Proj. Manag. 21(5), 363–373 (2003)

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank all the participating firms, construction managers, project managers, civil engineers, and respondents who participated in this study.

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  1. Department of Civil Engineering, Eastern Mediterranean University, Gazimagusa, Kibris, Mersin 10, Turkey

    Sepehr Alizadehsalehi & Ibrahim Yitmen

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  1. Sepehr Alizadehsalehi
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Alizadehsalehi, S., Yitmen, I. A Concept for Automated Construction Progress Monitoring: Technologies Adoption for Benchmarking Project Performance Control. Arab J Sci Eng 44, 4993–5008 (2019). https://doi.org/10.1007/s13369-018-3669-1

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