Abstract
Construction productivity issues in the Liquefied Natural Gas (LNG) construction industry can lead to project cost blowouts. Time wasted by construction personnel getting the right information on megaprojects can be a substantial contributing factor. It appears that the communication on site is not cost effective, judging by the number of large project that have experienced budget overruns in the past. More importantly, as-built design documentation often fails the quality test, resulting in operational inefficiencies once the plant has been handed over from Construction to Operation Phase. Common errors during the static prefabrication, dispatch and installation processes can result in serious rework as a significant amount of construction time and budget is wasted. To minimise these problems, this paper recommends to better control the dynamic natures of construction. This study propagates a conceptual framework for assuring quality of modular construction in LNG plants by introducing a Situation Awareness construction environment with well-defined sensing and tracking technologies. While encountering situations inconsistent with plans during construction, such as time delay, fabrication errors, conflicts in terms of accessibility and constructability issues and so forth, sensors mounted in situ can discover such situations and recursively fed back to field personnel. Automation and robotics technologies, such as real-time path planning, collision detection and deviation examination utilizing as-planned building information model, can assist engineers to rapidly react with inconsistent situations and make acceptable decisions instead of partially or entirely suspending the workforce through massive reworks. In this study, we conduct a preliminary study in demonstrating the feasibility of utilizing sensory devices and automatic planning technologies. The expected results of adopting the framework are the quality-assured modular construction and execution plans during construction stages to save rework construction time and budget.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Wang, X., Truijens, M., Hou, L., Wang, Y.: Application of collaborative mobile system in ar-based visualization, data storage and manipulation. In: Luo, Y. (ed.) Cooperative Design, Visualization, and Engineering, vol. 8091. Lecture Notes in Computer Science, pp. 221–226. Springer, Berlin Heidelberg (2013)
Ellis, M., Heyning, C., Legrand, O.: Extending the LNG boom: Improving Australian LNG productivity and competitiveness. In: McKinsey Global Institute. New York (2013)
Taylor, C., Bradley, C., Dobbs, R., Thompson, F.D.C.: Beyond the boom: Australia’s productivity imperative. In: McKinsey Global Institute. New York (2012)
Wang, X., Love, P.E.D., Kim, M.J., Park, C.-S., Sing, C.-P., Hou, L.: A conceptual framework for integrating building information modeling with augmented reality. Autom. Constr. 34, 37–44 (2013)
Lin, W., Zhang, N., Gu, A.: LNG (liquefied natural gas): A necessary part in China’s future energy infrastructure. Energy 35(11), 4383–4391 (2010)
Wakamatsu, Y., Matsui, S., Yatsuhashi, Y.: Off-the-shelf mid-small-mini-scale LNG plant - case study for application. In: 17th International Conference and Exhibition on Liquefied Natural Gas. Houston (2013)
Babič, N.Č., Podbreznik, P., Rebolj, D.: Integrating resource production and construction using BIM. Autom. Constr. 19(5), 539–543 (2010)
Vähä, P., Heikkilä, T., Kilpeläinen, P., Järviluoma, M., Gambao, E.: Extending automation of building construction — survey on potential sensor technologies and robotic applications. Autom. Constr. 36, 168–178 (2013)
Akinci, B., Boukamp, F., Gordon, C., Huber, D., Lyons, C., Park, K.: A formalism for utilization of sensor systems and integrated project models for active construction quality control. Autom. Constr. 15(2), 124–138 (2006)
Josephson, P.E., Hammarlund, Y.: The causes and costs of defects in construction: A study of seven building projects. Autom. Constr. 8(6), 681–687 (1999)
Park, C.-S., Lee, D.-Y., Kwon, O.-S., Wang, X.: A framework for proactive construction defect management using BIM, augmented reality and ontology-based data collection template. Autom. Constr. 33, 61–71 (2013)
Dong, A., Maher, M.L., Kim, M.J., Gu, N., Wang, X.: Construction defect management using a telematic digital workbench. Autom. Constr. 18(6), 814–824 (2009)
Mell, P., Grance, T.: The NIST definition of cloud computing. Technical Report SP 800-145. National Institute for Standard and Technology (2011)
Redmond, A., Hore, A., Alshawi, M., West, R.: Exploring how information exchanges can be enhanced through cloud BIM. Autom. Constr. 24, 175–183 (2012)
Jiao, Y., Wang, Y., Zhang, S., Li, Y., Yang, B., Yuan, L.: A cloud approach to unified lifecycle data management in architecture, engineering, construction and facilities management: Integrating BIMs and SNS. Adv. Eng. Inf. 27(2), 173–188 (2013)
Curry, E., O’Donnell, J., Corry, E., Hasan, S., Keane, M., O’Riain, S.: Linking building data in the cloud: Integrating cross-domain building data using linked data. Adv. Eng. Inf. 27(2), 206–219 (2013)
Venters, W., Whitley, E.A.: A critical review of cloud computing: researching desires and realities. J. Inf. Technol. 27, 179–197 (2012)
Kelm, A., Laußat, L., Meins-Becker, A., Platz, D., Khazaee, M.J., Costin, A.M., Helmus, M., Teizer, J.: Mobile passive Radio Frequency Identification (RFID) portal for automated and rapid control of Personal Protective Equipment (PPE) on construction sites. Autom. Constr. 36, 38–52 (2013)
Zhang, C., Hammad, A., Bahnassi, H.: Collaborative multi-agent systems for construction equipment based on real-time field data capturing. J. Inf. Technol. Constr. 14, 204–228 (2009)
Behzadan, A.H., Timm, B.W., Kamat, V.R.: General-purpose modular hardware and software framework for mobile outdoor augmented reality applications in engineering. Adv. Eng. Inf. 22(1), 90–105 (2008)
Anil, E.B., Tang, P., Akinci, B., Huber, D.: Deviation analysis method for the assessment of the quality of the as-is building information models generated from point cloud data. Autom. Constr. 35, 507–516 (2013)
Chi, H.-L., Chen, Y.-C., Kang, S.-C., Hsieh, S.-H.: Development of user interface for tele-operated cranes. Adv. Eng. Inf. 26 (3), 641–652 (2012)
Chen, H.-T., Wu, S.-W., Hsieh, S.-H.: Visualization of CCTV coverage in public building space using BIM technology. Vis. Eng. 1(1), 5 (2013)
Kim, D., Kim, J., Lee, K., Park, C., Song, J., Kang, D.: Excavator tele-operation system using a human arm. Autom. Constr. 18(2), 173–182 (2009)
Shapira, A., Rosenfeld, Y., Mizrahi, I.: Vision system for tower cranes. J. Constr. Eng. Manag. 134(5), 320–332 (2008)
Teizer, J.: 3D range imaging camera sensing for active safety in construction. J. Inf. Technol. Constr. 13, 103–117 (2008)
Wang, X., Schnabel, M.A.: Mixed reality in architecture, design, and construction. Springer (2009)
Wang, X., Gu, N., Marchant, D.: An empirical case study on designer’s perceptions of augmented reality within an architectural firm. J. Inf. Technol. Constr. 13, 536–552 (2008)
Wang, X.: Augmented reality in architecture and design: Potentials and challenges for application. Int. J. Archit. Comput. 7(2), 309–326 (2009)
Wang, X.: Using augmented reality to plan virtual construction worksite. Int. J. Adv. Robot. Syst. 4(4), 501–512 (2007)
Shin, D.H., Dunston, P.S., Wang, X.: View changes in mixed reality-based collaborative virtual environments. ACM Trans. Appl. Percept. 2(1), 1–14 (2005)
Wang, X., Dunston, P.S.: Design, strategies, and issues towards an augmented reality-based construction training platform. J. Inf. Technol. Constr. 12, 363–380 (2007)
Golparvar-Fard, M., Peña-Mora, F., Savarese, S.: Application of D 4AR - A 4-dimensional augmented reality model for automating construction progress monitoring data collection, processing and communication. J. Inf. Technol. Constr. 14, 129–153 (2009)
Schall, G., Mendez, E., Kruijff, E., Veas, E., Junghanns, S., Reitinger, B., Schmalstieg, D.: Handheld augmented reality for underground infrastructure visualization. Pers. Ubiquit. Comput. 13(4), 281–291 (2009)
Comport, A.I., Marchand, E., Pressigout, M., Chaumette, F.: Real-time markerless tracking for augmented reality: The virtual visual servoing framework. IEEE Trans. Vis. Comput. Graph. 12(4), 615–628 (2006)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)
Kavraki, L.E., Svestka, P., Latombe, J.C., Overmars, M.H.: Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans. Robot. Autom. 12(4), 566–580 (1996)
Lai, K.-C., Kang, S.-C.: Collision detection strategies for virtual construction simulation. Autom. Constr. 18(6), 724–736 (2009)
Yang, C.-E., Lin, J.J.-C., Hung, W.-H., Kang, S.-C.: Accessibility evaluation system for site layout planning - A tractor trailer example. Vis. Eng. 1(1), 12 (2013)
Zhang, C., Hammad, A.: Improving lifting motion planning and re-planning of cranes with consideration for safety and efficiency. Adv. Eng. Inf. 26(2), 396–410 (2012)
Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. Math. 1(1), 269–271 (1959)
Hart, P.E., Nilsson, N.J., Raphael, B.: Correction to a formal basis for the heuristic determination of minimum cost paths. SIGART Newsl. 37, 28–29 (1972)
Kang, S., Miranda, E.: Planning and visualization for automated robotic crane erection processes in construction. Autom. Constr. 15(4), 398–414 (2006)
Chang, Y.-C., Hung, W.-H., Kang, S.-C.: A fast path planning method for single and dual crane erections. Autom. Constr. 22, 468–480 (2012)
Son, S., Park, H., Lee, K.H.: Automated laser scanning system for reverse engineering and inspection. Int. J. Mach. Tools Manuf. 42(8), 889–897 (2002)
Kovacic, I., Oberwinter, L., Muller, C., Achammer, C.: The BIM-sustain experiment - simulation of BIM-supported multi-disciplinary design. Vis. Eng. 1(1), 13 (2013)
Hou, L., Wang, X., Bernold, L., Love, P.: Using animated augmented reality to cognitively guide assembly. J. Comput. Civil Eng. 27(5), 439–451 (2013)
Geoforce: Geoforce: Hardware. http://www.geoforce.com/Technologies/Hardware/ (2013). Accessed 31 Dec 2013
LaValle, S.M.: Motion planning: The essentials. IEEE Robot. Autom. Mag. 18(1), 79–89 (2011)
Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chi, HL., Wang, J., Wang, X. et al. A Conceptual Framework of Quality-Assured Fabrication, Delivery and Installation Processes for Liquefied Natural Gas (LNG) Plant Construction. J Intell Robot Syst 79, 433–448 (2015). https://doi.org/10.1007/s10846-014-0123-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-014-0123-9