A Decision Support System for the Integration of Robotics in Offsite Construction
Publication: Construction Research Congress 2022
ABSTRACT
The integration of robotic systems into the manufacturing sector has greatly helped in the improvement of manufacturing quality, safety, and productivity. This prompted construction professionals to incorporate robotics into various construction activities ranging from onsite activities to offsite construction. However, a lack of understanding of the financial and technical benefits of robotics, as well as identical features of each construction project, have been barriers to utilizing the full potential of robotics in the construction industry. This study develops a decision support system for the selection of robotics in offsite construction to address the existing technical issues and cost uncertainties. The proposed study employs simulation techniques to assess the performance of multi robots in an offsite manufacturing plant. Five robotic characteristics (i.e., reach, payload, axis speed, degrees of freedom, and position repeatability) are chosen as criteria, and a scoring system is developed to rank the best-performing robots. The results show a 52% increase in annual production rate and a 21.56% overall cost reduction when multi robots were used. The proposed decision support system is intended to support construction automation and enable construction professionals to make accurate decisions when implementing robotic systems.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Anandan, T. M. (2015). “Calculating Your ROI for Robotic Automation: Cost vs. Cash Flow.” <https://www.automate.org/industry-insights/calculating-your-roi-for-robotic-automation-cost-vs-cash-flow>.
Barosz, P., Gołda, G., and Kampa, A. (2020). “Efficiency analysis of manufacturing line with industrial robots and human operators.” Appl. Sci., 10(8).
Bock, T. (2015). “The future of construction automation: Technological disruption and the upcoming ubiquity of robotics.” Autom. Constr., Elsevier, 59, 113–121.
Brosque, C., Skeie, G., and Fischer, M. (2021). “Comparative Analysis of Manual and Robotic Concrete Drilling for Installation Hangers.” J. Constr. Eng. Manag., American Society of Civil Engineers (ASCE), 147(3), 05021001.
Davila Delgado, J. M., Oyedele, L., Ajayi, A., Akanbi, L., Akinade, O., Bilal, M., and Owolabi, H. (2019). “Robotics and automated systems in construction: Understanding industry-specific challenges for adoption.” J. Build. Eng., Elsevier Ltd, 26, 100868.
Ferreras-Higuero, E., Leal-Muñoz, E., García de Jalón, J., Chacón, E., and Vizán, A. (2020). “Robot-process precision modelling for the improvement of productivity in flexible manufacturing cells.” Robot. Comput. Integr. Manuf., Elsevier Ltd, 65, 101966.
García de Soto, B., Agustí-Juan, I., Hunhevicz, J., Joss, S., Graser, K., Habert, G., and Adey, B. T. (2018). “Productivity of digital fabrication in construction: Cost and time analysis of a robotically built wall.” Autom. Constr., Elsevier B.V., 92, 297–311.
Manyika, J., Chui, M., Miremadi, M., Bughin, J., George, K., Willmott, P., and Dewhurst, M. (2017). A Future That Works: Automation, Employment, and Productivity. McKinsey Co.
Modular Building Institute. (2010). Improving Construction Efficiency & Productivity with Modular Construction. Modul. Build. Inst.
Pan, M., and Pan, W. (2019). “Determinants of Adoption of Robotics in Precast Concrete Production for Buildings.” J. Manag. Eng., American Society of Civil Engineers (ASCE), 35(5), 05019007.
Pellegrinelli, S., Pedrocchi, N., Tosatti, L. M., Fischer, A., and Tolio, T. (2017). “Multi-robot spot-welding cells for car-body assembly: Design and motion planning.” Robot. Comput. Integr. Manuf., Elsevier Ltd, 44, 97–116.
Syverson, C. (2004). “Product substitutability and productivity dispersion.” Rev. Econ. Stat., 86(2), 534–550.
Wagner, H. J., Alvarez, M., Kyjanek, O., Bhiri, Z., Buck, M., and Menges, A. (2020). “Flexible and transportable robotic timber construction platform – TIM.” Autom. Constr., Elsevier, 120, 103400.
World Bank. (2021a). “Inflation, consumer prices (annual %) - United States.” <https://data.worldbank.org/indicator/FP.CPI.TOTL.ZG?end=2020&locations=US&start=2010>(Sep. 1, 2021).
World Bank. (2021b). “Real interest rate (%) - United States.” <https://data.worldbank.org/indicator/FR.INR.RINR?locations=US>(Sep. 1, 2021).
Information & Authors
Information
Published In
Construction Research Congress 2022
Pages: 849 - 858
History
Published online: Mar 7, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.