SpringerLink
Log in

Review of Construction Automation and Robotics Practices in Indonesian Construction State-Owned Enterprises: Position in Project Life Cycle, Gap to Best Practice and Potential Uses

  • Original Paper
  • Published:
Architecture, Structures and Construction Aims and scope Submit manuscript

Abstract

Construction Automation and Robotics is the anticipated technology to overcome productivity issues and work accidents. This research aims to analyze the implementation of Construction Automation and Robotics at Indonesian Construction SOEs from the perspective of real project implementation based on project life cycle, comparison with best practices, and potential uses, through the qualitative-comparative analysis of the literature as well as questionnaires and in-depth interviews. It attempts to report how this technology is implemented in Indonesia as a comparison tool for other countries. This research identifies that seven Indonesian Construction SOEs have been using Construction Automation and Robotics technology, where Drones, Virtual Reality, and Prefabrication and Modularization are the most popular and mostly implemented in the construction phase. Compared to best practices, those implementations are still in the adoption stage. It has not reached its full potential through the development stage due to insufficient collaboration between contractors, technology companies, and universities. Although the construction market in Indonesia has not directly demanded in-project applications, this technology is potentially considered to improve the completion of construction projects, especially the interaction prospects of Digital Twin and BIM. This study provides complete positional information on Construction Automation and Robotics type in the project life cycle in theory and practice as a benchmark for construction technology research. This study fills the research gap and pioneers Indonesia’s Construction Automation and Robotics implementation research in international journals by providing the latest and comprehensive overview and comparing it to good practices from the USA and China.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price includes VAT (Germany)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Data Availability

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

References

  1. Doa YP, Winanda LAR, Iskandar T (2021). Faktor-faktor Penyebab Kecelakaan Kerja Konstruksi di Indonesia dan Pencegahannya, Stud J Gelagar. 4:1–9. https://ejournal.itn.ac.id/index.php/gelagar/article/view/4586 (accessed June 29, 2022).

  2. Ghuzdewan T, Damanik P (2019) Analysis of accident in Indonesian construction projects. MATEC Web of Conferences 258:02021. https://doi.org/10.1051/matecconf/201925802021

    Article  Google Scholar 

  3. Bademosi FM, Issa RRA (2022) Automation and Robotics Technologies Deployment Trends in Construction, Automation and Robotics in the Architecture. Eng Constr Ind. 1–30. https://doi.org/10.1007/978-3-030-77163-8_1.

  4. Soemardi BW, Kusuma B, Abduh M (2020) Technology Assessment in Indonesian Construction Industry, IOP Conference Series: Materials Science and Engineering. 849:012077. https://doi.org/10.1088/1757-899x/849/1/012077.

  5. Seyrfar A, Ataei H, Osman I (2022) Robotics and Automation in Construction (RAC): Priorities and Barriers Toward Productivity Improvement in Civil Infrastructure Projects, Automation and Robotics in the Architecture, Engineering, and Construction Industry. 59–71. https://doi.org/10.1007/978-3-030-77163-8_3.

  6. Soekiman A, Pribadi KS, Soemardi BW, Wirahadikusumah RD (2011) Factors relating to labor productivity affecting the project schedule performance in Indonesia. Procedia Eng 14:865–873. https://doi.org/10.1016/j.proeng.2011.07.110

    Article  Google Scholar 

  7. Alwi S (2003) Factors Influencing Construction Productivity in The Indonesian Context, in: Proceedings The 5th EASTS Conference. https://eprints.qut.edu.au/4237/1/4154_1.pdf.

  8. Salim WN, Sujana CM (2020) Project delay analysis of highrise building project in Jakarta, IOP Conference Series: Earth and Environmental Science. 426 012051. https://doi.org/10.1088/1755-1315/426/1/012051.

  9. M. Tafazzoli (2022) Construction Automation and Sustainable Development, in: H. Jebelli, M. Habibnezhad, S. Shayesteh, S. Asadi, S. Lee (Eds.), Automation and Robotics in the Architecture, Engineering, and Construction Industry, Springer International Publishing. Cham 73–95. https://doi.org/10.1007/978-3-030-77163-8_4.

  10. Omoregie AD, Ohis AC, Emmanuel OA, Didibhuku TW (2020) Map** out research focus for robotics and automation research in construction-related studies: A bibliometric approach. Proc Inst Mar Eng Sci Technol B: J Des Oper 18:1063–1079. https://doi.org/10.1108/JEDT-09-2019-0237

    Article  Google Scholar 

  11. Oktaviani AD, Berawi MA (2022) Implementation of 3D Concrete Printing Technology in Precast Concrete Mass Production Industry. Lecture Notes in Civil Engineering 207–221. https://doi.org/10.1007/978-981-16-6932-3_18.

  12. AUTOMATIC, Lexico Dictionaries | English. (2022). https://www.lexico.com/definition/automatic (accessed 30 Jun 2022).

  13. Shi W (2009) Framework for integration of BIM and RFID in steel construction, Ph.D, University of Florida. https://www.proquest.com/openview/394e648f62001d7e59a0d9fa3f45bb36/1?pq-origsite=gscholar&cbl=18750 (accessed 30 Jun 2022).

  14. Chen L-K, Yuan R-P, Ji X-J, Lu X-Y, **ao J, Tao J-B, Kang X, Li X, He Z-H, Quan S, Jiang L-Z (2021) Modular composite building in urgent emergency engineering projects: A case study of accelerated design and construction of Wuhan Thunder God Mountain/Leishenshan hospital to COVID-19 pandemic. Autom. Constr. 124:103555. https://doi.org/10.1016/j.autcon.2021.103555

    Article  Google Scholar 

  15. Carra G, Argiolas A, Bellissima A, Niccolini M, Ragaglia M (2018) Robotics in the Construction Industry: State of the Art and Future Opportunities, in: 2018 Proceedings of the 35th ISARC. http://www.iaarc.org/publications/2018_proceedings_of_the_35th_isarc/robotics_in_the_construction_industry-state_of_the_art_and_future_opportunities.html.

  16. T. Bock, Construction Automation and Robotics, in: Robotics and Automation in Construction, InTech, 2008. https://doi.org/10.5772/5861.

  17. Bock T (2015) The future of construction automation: Technological disruption and the upcoming ubiquity of robotics. Autom Constr 59:113–121. https://doi.org/10.1016/j.autcon.2015.07.022

    Article  Google Scholar 

  18. Davila Delgado JM, Oyedele L, Ajayi A, Akanbi L, Akinade O, Bilal M, Owolabi H (2019) Robotics and automated systems in construction: Understanding industry-specific challenges for adoption. J Build Eng. 26:100868. https://doi.org/10.1016/j.jobe.2019.100868

    Article  Google Scholar 

  19. Javier I (2016) Costa Dayana Bastos, Exploratory Study of Potential Applications of Unmanned Aerial Systems for Construction Management Tasks. J Manage Eng 32:05016001. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000422

    Article  Google Scholar 

  20. **ying Xu, Weishing Lu (2018) Smart Construction from Head to Toe: A Closed-Loop Lifecycle Management System Based on IoT. Construction Research Congress 2018:157–168. https://doi.org/10.1061/9780784481264.016

    Article  Google Scholar 

  21. Sepehr A, Ozan K, Murude C (2015) Integration of Building Information Modeling (BIM) and Laser Scanning in Construction Industry. AEI 2015:163–174. https://doi.org/10.1061/9780784479070.015

    Article  Google Scholar 

  22. Frank HM, Ricardo E, Masoud G, Behzad E (2019) Hazard Identification Training Using 360-Degree Panorama vs. Virtual Reality Techniques: A Pilot Study. J Comput Civ Eng. 55–62. https://doi.org/10.1061/9780784482421.008.

  23. Manuel DDJ, Lukumon O, Thomas B, Peter D (2020) Augmented and Virtual Reality in Construction: Drivers and Limitations for Industry Adoption. J Constr Eng Manage 146:04020079. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001844

    Article  Google Scholar 

  24. Kan C and Anumba CJ (2019) Digital Twins as the Next Phase of Cyber-Physical Systems in Construction. J Comput Civ Eng 256–264. https://doi.org/10.1061/9780784482438.033

  25. Wimala M, Imanuela K (2022) Perkembangan Internet of Things di Industri Konstruksi. J Sustain Constr. 2 https://doi.org/10.26593/josc.v2i1.5701

  26. Masse F, Deschamps R, Scarwell A, Joussellin T (2021) IoT and Big Data in Geotechnical Construction: Connecting Drill Rigs to the Cloud. GeoStrata Magazine Archive 25:30–35. https://doi.org/10.1061/geosek.0000031

    Article  Google Scholar 

  27. Bello SA, Oyedele LO, Akinade OO, Bilal M, Davila Delgado JM, Akanbi LA, Ajayi AO, Owolabi HA (2021) Cloud computing in construction industry: Use cases, benefits and challenges. Autom Constr. 122 103441. https://doi.org/10.1016/j.autcon.2020.103441.

  28. Ahn CR (2019) Lee SangHyun, Sun Cenfei, Jebelli Houtan, Yang Kanghyeok, Choi Byungjoo, Wearable Sensing Technology Applications in Construction Safety and Health. J Constr Eng Manage 145:03119007. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001708

    Article  Google Scholar 

  29. PMBOK® Guide (2021). https://www.pmi.org/pmbok-guide-standards/foundational/pmbok (accessed 29 Jun 2022).

  30. Bogue R (2017) What are the prospects for robots in the construction industry? Industrial Robot: An International Journal 45:1–6. https://doi.org/10.1108/IR-11-2017-0194

    Article  Google Scholar 

  31. Mallela J, Mitchell A, Gustafson J, Olsen MJ, Parrish C, Gillins DT, Kumpula M, Roe G (2018) Effective Use of Geospatial Tools in Highway Construction, United States. Federal Highway Administration. Office of Research, Development, and Technology. https://rosap.ntl.bts.gov/view/dot/50531 (accessed 29 Jun 2022).

  32. Ruiz, Alzraiee (2020) Automated Pavement Marking Defects Detection, in: 2020 Proceedings of the 37th ISARC pp. 67–73. https://doi.org/10.22260/ISARC2020/0011.

  33. V. Kasireddy, B. Akinci (n.d.)A Case Study on Comparative Analysis of 3D Point Clouds from UAV and Terrestrial Scanners for Bridge Condition Assessment, in: Proceedings of the Joint Conference on Computing in Construction (JC3), pp. 87–94. https://doi.org/10.24928/JC3-2017/0041.

  34. Prime GW (2020) FARO’s Laser Scanner Used to Help Rebuild L.A.’s Luxury Century Plaza Hotel, Geospatial World. https://www.gwprime.geospatialworld.net/case-study/faros-laser-scanner-used-to-help-rebuild-l-a-s-luxury-century-plaza-hotel/ (accessed 29 Jun 2022).

  35. Zhang C, Arditi D (2020) Advanced Progress Control of Infrastructure Construction Projects Using Terrestrial Laser Scanning Technology. Infrastructures 5:83. https://doi.org/10.3390/infrastructures5100083

    Article  Google Scholar 

  36. Puri N, Turkan Y (2020) Bridge construction progress monitoring using lidar and 4D design models, Autom. Constr. 109 102961. https://doi.org/10.1016/j.autcon.2019.102961.

  37. Psomas Luke, Trainor Ryan, Alzraiee Hani, Case Study (2022) Assessing the Structural Condition of Steel Bridges Using Terrestrial Laser Scanner (TLS). Construction Research Congress 2022:433–442. https://doi.org/10.1061/9780784483961.046

    Article  Google Scholar 

  38. A. Larson (2018) 3D Scanning of Basilica - Norfolk, Laser Design. https://www.laserdesign.com/3d-scanning-of-basilica-norfolk (accessed 29 Jun 2022).

  39. SITECH Constructions Systems, SITECH Constructions Systems (2016). https://sitechcs.com/index.php/category/case-studies/page/3/ (accessed 29 Jun 2022).

  40. Ackerman E (2018) AI Startup using robots and lidar to boost productivity on construction sites, IEEE Spectrum. https://spectrum.ieee.org/doxel-ai-startup-using-lidar-equipped-robots-on-construction-sites (accessed 29 Jun 2022).

  41. Pereira Ricardo Eiris (2018) Gheisari Masoud. Esmaeili Behzad, Using Panoramic Augmented Reality to Develop a Virtual Safety Training Environment, Construction Research Congress 2018:29–39. https://doi.org/10.1061/9780784481288.004

    Article  Google Scholar 

  42. Pereira RE, Hashem IM, Masoud G (2017) Using 360-Degree Interactive Panoramas to Develop Virtual Representation of Construction Sites, in: https://itc.scix.net/paper/lc3-2017-122. http://itc.scix.net/paper/lc3-2017-122.

  43. Zuluaga CM (2018) Albert Alex, Arroyo Paz, Protecting Bridge Maintenance Workers from Falls: Evaluation and Selection of Compatible Fall Protection Supplementary Devices. J Constr Eng Manage 144:04018073. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001529

    Article  Google Scholar 

  44. Meiqing Fu, Rui L (2018) The Application of Virtual Reality and Augmented Reality in Dealing with Project Schedule Risks. Construction Research Congress 2018:429–438. https://doi.org/10.1061/9780784481264.042

    Article  Google Scholar 

  45. Li X, Yi W, Chi H-L, Wang X, Chan APC (2018) A critical review of virtual and augmented reality (VR/AR) applications in construction safety. Autom Constr 86:150–162. https://doi.org/10.1016/j.autcon.2017.11.003

    Article  Google Scholar 

  46. Haggard KE (2017)Case Study on Virtual Reality in Construction. https://core.ac.uk/display/84280005?utm_source=pdf&utm_medium=banner&utm_campaign=pdf-decoration-v1 (accessed 29 Jun 2022).

  47. **g Du, Yangming S, Zhengbo Z, Dong Z (2018) CoVR: Cloud-Based Multiuser Virtual Reality Headset System for Project Communication of Remote Users. J Constr Eng Manage 144:04017109. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001426

    Article  Google Scholar 

  48. M. Froehlich, S. Azhar (2016)Investigating Virtual Reality Headset Applications in Construction, in: 52nd ASC Annual International Conference Proceedings, Associated Schools of Construction. http://ascpro0.ascweb.org/archives/cd/2016/paper/CPRT195002016.pdf.

  49. Yunjeong Mo, Zhao Dong Du, **g LW, Ajay D (2018) Data-Driven Approach to Scenario Determination for VR-Based Construction Safety Training. Construction Research Congress 2018:116–125. https://doi.org/10.1061/9780784481288.012

    Article  Google Scholar 

  50. Du J, Zou Z, Shi Y, Zhao D (2018) Zero latency: Real-time synchronization of BIM data in virtual reality for collaborative decision-making. Autom Constr 85:51–64. https://doi.org/10.1016/j.autcon.2017.10.009

    Article  Google Scholar 

  51. Chalhoub J, Ayer SK (2019) Exploring the performance of an augmented reality application for construction layout tasks. Multimed Tools Appl 78:35075–35098. https://doi.org/10.1007/s11042-019-08063-5

    Article  Google Scholar 

  52. Bademosi, Blinn, Issa, Use of augmented reality technology to enhance comprehension of construction assemblies, J. Inf. Technol. Constr. (2019). https://www.itcon.org/2019/4.

  53. Zhou Y, Luo H, Yang Y (2017) Implementation of augmented reality for segment displacement inspection during tunneling construction. Autom Constr 82:112–121. https://doi.org/10.1016/j.autcon.2017.02.007

    Article  Google Scholar 

  54. Chalhoub J, Ayer SK (2018) Using Mixed Reality for electrical construction design communication. Autom Constr 86:1–10. https://doi.org/10.1016/j.autcon.2017.10.028

    Article  Google Scholar 

  55. Graceline W, Masoud G, Po-Jui C, Javier I (2015) BIM2MAR: An Efficient BIM Translation to Mobile Augmented Reality Applications. J Manage Eng 31:A4014009. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000315

    Article  Google Scholar 

  56. Kamari M, Ham Y (2022) AI-based risk assessment for construction site disaster preparedness through deep learning-based digital twinning. Autom Constr 134:104091. https://doi.org/10.1016/j.autcon.2021.104091

    Article  Google Scholar 

  57. 8 companies bringing robotics and automation to construction, BuiltWorlds. (2017). https://builtworlds.com/insights/8-companies-bringing-robotics-and-automation-to-construction/ (accessed 29 Jun 2022).

  58. Cai Shiyao, Ma Zhiliang, Skibniewski Miroslaw J, Guo Jianfeng (2020) Construction Automation and Robotics: From One-Offs to Follow-Ups Based on Practices of Chinese Construction Companies. J Constr Eng Manage 146 05020013. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001910.

  59. Sun Z, Mei H, Pan W, Zhang Z, Shan J (2022) A Robotic Arm Based Design Method for Modular Building in Cold Region. Sustain Sci Pract Policy 14:1452. https://doi.org/10.3390/su14031452

    Article  Google Scholar 

  60. Hager I, Golonka A, Putanowicz R (2016) 3D Printing of Buildings and Building Components as the Future of Sustainable Construction? Procedia Eng. 151:292–299. https://doi.org/10.1016/j.proeng.2016.07.357

    Article  Google Scholar 

  61. Wu P, Wang J, Wang X (2016) A critical review of the use of 3-D printing in the construction industry. Autom Constr 68:21–31. https://doi.org/10.1016/j.autcon.2016.04.005

    Article  Google Scholar 

  62. Pouya S, Jeremy G, Vítor L, Adélio M, Nuno C (2018) Lifecycle Cost Analysis of Prefabricated Composite and Masonry Buildings: Comparative Study. J Archit Eng 24:05017012. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000288

    Article  Google Scholar 

  63. Hanna Awad S., Mikhail George, Iskandar Karim A., State of Prefab Practice in the Electrical Construction Industry: Qualitative Assessment. J Constr Eng Manage. 143 (2017) 04016097. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001236.

  64. Mao C, **e F, Hou L, Wu P, Wang J, Wang X (2016) Cost analysis for sustainable off-site construction based on a multiple-case study in China. Habitat Int 57:215–222. https://doi.org/10.1016/j.habitatint.2016.08.002

    Article  Google Scholar 

  65. You K, Ding L, Zhou C, Dou Q, Wang X, Hu B (2021) 5G-based earthwork monitoring system for an unmanned bulldozer. Autom Constr. 131:103891. https://doi.org/10.1016/j.autcon.2021.103891

    Article  Google Scholar 

  66. ** R, Zhang H, Liu D, Yan X (2020) IoT-based detecting, locating and alarming of unauthorized intrusion on construction sites. Autom Constr. 118:103278. https://doi.org/10.1016/j.autcon.2020.103278

    Article  Google Scholar 

  67. Zhou C, Ding LY (2017) Safety barrier warning system for underground construction sites using Internet-of-Things technologies. Autom Constr 83:372–389. https://doi.org/10.1016/j.autcon.2017.07.005

    Article  Google Scholar 

  68. Chen F, Jiao H, Han L, Shen L, Du W, Ye Q, Yu G (2020) Real-time monitoring of construction quality for gravel piles based on Internet of Things. Autom Constr. 116:103228. https://doi.org/10.1016/j.autcon.2020.103228

    Article  Google Scholar 

  69. Rayan Assaad, El-adaway Islam H H (2020) Evaluation and Prediction of the Hazard Potential Level of Dam Infrastructures Using Computational Artificial Intelligence Algorithms. J Manage Eng. 36:04020051. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000810

    Article  Google Scholar 

  70. Guo S, Luo H, Yong L (2015) A Big Data-based Workers Behavior Observation in China Metro Construction. Procedia Eng 123:190–197. https://doi.org/10.1016/j.proeng.2015.10.077

    Article  Google Scholar 

  71. Wang X, Song Y, Tang P (2020) Generative urban design using shape grammar and block morphological analysis. Front Arch Res 9:914–924. https://doi.org/10.1016/j.foar.2020.09.001

    Article  Google Scholar 

  72. Zhang J, Liu N, Wang S (2021) Generative design and performance optimization of residential buildings based on parametric algorithm. Energy Build. 244:111033. https://doi.org/10.1016/j.enbuild.2021.111033

    Article  Google Scholar 

  73. Tang P, Wang X, Shi X (2019) Generative design method of the facade of traditional architecture and settlement based on knowledge discovery and digital generation: a case study of Gunanjie Street in China. Int J Archit Heritage: Conserv Anal Restor 13:679–690. https://doi.org/10.1080/15583058.2018.1463415

    Article  Google Scholar 

  74. Aryal A, Ghahramani A, Becerik-Gerber B (2017) Monitoring fatigue in construction workers using physiological measurements. Autom Constr 82:154–165. https://doi.org/10.1016/j.autcon.2017.03.003

    Article  Google Scholar 

  75. Ulises T, Matthew H, Ray L, Sathyanarayanan R (2018) Measuring and Predicting Fatigue in Construction: Empirical Field Study. J Constr Eng Manage 144:04018062. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001513

    Article  Google Scholar 

  76. Guo H, Yu Y, **ang T, Li H, Zhang D (2017) The availability of wearable-device-based physical data for the measurement of construction workers’ psychological status on site: From the perspective of safety management. Autom Constr 82:207–217. https://doi.org/10.1016/j.autcon.2017.06.001

    Article  Google Scholar 

  77. Cai S, Ma Z, Skibniewski MJ, Bao S, Wang H (2020) Construction Automation and Robotics for High-Rise Buildings: Development Priorities and Key Challenges. J Constr Eng Manag. 146. https://doi.org/10.1061/(asce)co.1943-7862.0001891.

  78. Bademosi F, Issa RRA (2021) Factors Influencing Adoption and Integration of Construction Robotics and Automation Technology in the US. J Constr Eng Manag. 147. https://doi.org/10.1061/(asce)co.1943-7862.0002103.

  79. Pradhananga P, ElZomor M, Kasabdji GS (2021) Identifying the Challenges to Adopting Robotics in the US Construction Industry. J Constr Eng Manag. 147. https://doi.org/10.1061/(asce)co.1943-7862.0002007

  80. Wuni IY, Shen GQ (2020) Critical success factors for modular integrated construction projects: a review. Build Res Inform 48:763–784. https://doi.org/10.1080/09613218.2019.1669009

    Article  Google Scholar 

  81. Rashid MNA, Abdullah MR, Ismail D (2019) Critical Success Factors CSFs to Automation and Robotics in Industrialized Building System IBS, International Journal of Academic Research in Business and Social Sciences 8.  https://doi.org/10.6007/ijarbss/v8-i12/5432.

  82. O’Connor JT, O’Brien WJ, Choi JO (2014) Critical Success Factors and Enablers for Optimum and Maximum Industrial Modularization. J Constr Eng  Manag. 140 https://doi.org/10.1061/(asce)co.1943-7862.0000842.

  83. Hermawan S, Leman S (2020) Implementation Photography as a Media and Supports in Construction Era 4.0 at the Civil Engineering for the Construction Design to Face Tidal Floods Due to Global Warming. J Phys Conf Ser 1625:012058. https://doi.org/10.1088/1742-6596/1625/1/012058

    Article  Google Scholar 

  84. Purnama N (2021) Terra Drone Indonesia Gunakan Drone LiDAR untuk Survey Pembangunan Jalan di Papua Barat, Terra Drone Indonesia. https://terra-drone.co.id/terra-drone-indonesia-gunakan-drone-lidar-untuk-survey-pembangunan-jalan-di-papua-barat/ (accessed 9 Aug 2022).

  85. Purnama N (2021) Terra Drone Indonesia Bantu Percepat Pengerjaan Proyek Tol Cisumdawu Menggunakan Drone, Terra Drone Indonesia. https://terra-drone.co.id/terra-drone-indonesia-bantu-percepat-pengerjaan-proyek-tol-cisumdawu-menggunakan-drone/ (accessed 9 Aug 2022).

  86. Arbad AP, Arifin ZN, Martina N, Setiadji H, Nindya EP, Nurfa MA (2020) Comparison of Photogrammetric Point Clouds with BIM Building Elements for Dam Construction Progress Monitoring in Indonesia, in: Proceeding ACRS 2020. https://a-a-r-s.org/proceeding/ACRS2020/siz419.pdf (accessed 8 Aug 2022).

  87. E-CATALOG BUMN, Badan Usaha Milik Negara (BUMN). (2021). https://bumn.go.id/storage/ekatalog/e-katalog-riset-inovasi-bumn/ (accessed 9 Aug 2022).

  88. Masuki Era Industri 4.0, Kementerian PUPR Manfaatkan Teknologi 3D Printing Untuk Bangun Rumah Khusus, Kementerian PUPR. (2022). https://pu.go.id/berita/masuki-era-industri-40-kementerian-pupr-manfaatkan-teknologi-3d-printing-untuk-bangun-rumah-khusus (accessed 9 Aug 2022).

  89. Kementerian PUPR Gunakan Teknologi Modular untuk Respon Cepat Penanganan COVID-19, (2020). https://eppid.pu.go.id/page/kilas_berita/1813/Kementerian-PUPR-Gunakan-Teknologi-Modular-untuk-Respon-Cepat-Penanganan-COVID-19 (accessed 9 Aug 2022).

  90. Kementerian Badan Usaha Milik Negara, (2021). https://bumn.go.id/post/ptpp-selesaikan-pembangunan-rs-modular-di-papua (accessed 9 Aug 2022).

  91. Wika Gedung (2021). https://www.wikagedung.co.id/our_business/modular_166/mdlr/proyek_selesai (accessed 9 Aug 2022).

  92. Putra RGR, Susanto D (2017) Prefabricated house in real estate business development in Jabodetabek, IOP Conf. Ser.: Earth Environ Sci. 99 012022. https://doi.org/10.1088/1755-1315/99/1/012022.

  93. Zulfan J, Lestari S, Rimawan RR, Hidayat MN, Slamet NS, Modular Weir: New Method of Weir Construction to Improve Irrigation Productivity, in: 3rd World Irrigation Forum (WIF3), 2019. https://www.icid.org/wif3_bali_2019/wif3_3-3_8-min.pdf (accessed 8 Aug 2022).

  94. Berawi MA, Sunardi A, Ichsan M (2019) Chief-Screen 1.0 as the Internet of Things Platform in Project Monitoring & Controlling to Improve Project Schedule Performance. Procedia Comp Sci. 161 1249–1257. https://doi.org/10.1016/j.procs.2019.11.239.

  95. Iasha F, Darwito PA (2020) Design of Algorithm Control For Monitoring System And Control Bridge Based Internet of Things (IoT), in. International Conference on Smart Technology and Applications (ICoSTA) 2020:1–6. https://doi.org/10.1109/ICoSTA48221.2020.1570615709

    Article  Google Scholar 

  96. Ramadhan S, Lisapaly L, Boesrony D (2021) Smart energy monitoring based on IoT Lora-Wan on the campus buildings: Case study Indonesian Defence University (Unhan), Sentul, Bogor, IOP Conf. Ser.: Earth Environ Sci. 878, 012065. https://doi.org/10.1088/1755-1315/878/1/012065.

  97. Anindita AP, Laksono P, Nugraha IGB (2016) Dam water level prediction system utilizing Artificial Neural Network Back Propagation: Case study: Ciliwung watershed, Katulampa Dam, in. International Conference on ICT For Smart Society (ICISS) 2016:16–21. https://doi.org/10.1109/ICTSS.2016.7792862

    Article  Google Scholar 

  98. SP Hamdi A Hadiwardoyo 2017 Gomes Correia, P Pereira, Pavement Maintenance Optimization Strategies for National Road Network in Indonesia Applying Genetic Algorithm. Procedia Eng. 210:253-260.https://doi.org/10.1016/j.proeng.2017.11.074

Download references

Acknowledgements

The authors would like to thank the representatives of seven Indonesian Construction SOEs: PT. PP (Persero) Tbk., PT. Waskita Karya (Persero) Tbk., PT. Wijaya Karya (Persero) Tbk., PT. Adhi Karya (Persero) Tbk., PT. Hutama Karya (Persero), PT. Nindya Karya (Persero), and PT. Brantas Abipraya (Persero) for their contribution as respondents to this study.

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Universitas Komputer Indonesia (UNIKOM), Bandung, West Java, 40132, Indonesia

    Yongki Alexander Tanne

  2. Construction Engineering and Management, Bandung Institute of Technology, Bandung, West Java, 40132, Indonesia

    Ni Luh Ayu Indrayani

Authors
  1. Yongki Alexander Tanne
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ni Luh Ayu Indrayani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yongki Alexander Tanne.

Ethics declarations

Competing Interest

The authors have no relevant financial or non-financial interests to disclose.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tanne, Y.A., Indrayani, N.L.A. Review of Construction Automation and Robotics Practices in Indonesian Construction State-Owned Enterprises: Position in Project Life Cycle, Gap to Best Practice and Potential Uses. Archit. Struct. Constr. 3, 373–389 (2023). https://doi.org/10.1007/s44150-023-00098-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s44150-023-00098-5

Keywords

Search

Navigation