A Simulation Model to Analyze Different Automation Scenarios in a Mixed-Assembly Manufacturing Line: Timber-Frame Prefabrication Industry
Publication: Journal of Construction Engineering and Management
Volume 149, Issue 10
Abstract
As prefabrication of timber structures in the construction sector becomes part of the solution to overcome the housing and environmental crisis, the lack of efficiency of this industry needs to be addressed. This inefficiency, characterized by low production capacity, high costs, and large workforce, are in part due to the low adoption of automation and robotic technologies, caused by insufficient knowledge and research measuring the impact of these technologies. This paper aims to measure the efficiency of introducing automation in a prefabrication environment of timber-frame structures, through a decision analysis tool. Four layout types with varying automation levels are explored using simulation modeling, while KPIs are exploited to measure the efficiency of each production environment. A sensitivity analysis is conducted to assess the most performing layout if a new type of wall, requiring fewer tasks, is introduced in the product mix. A design of experiments (DOE) is also performed on the fourth layout, a fixed robotic cell with the highest level of automation, to assess the most influential variables. Results show a positive increase in worker, space, and production efficiency as the level of automation increase. This research contributes to the body of knowledge by providing a decision analysis tool supporting the choice of an optimized layout for the prefabrication of timber-frame walls (TFW). The findings and the decision analysis tool should provide solid grounds for future exploration of automation and practice in the field.
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Data Availability Statement
Some or all data, layouts, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions.
Acknowledgments
The authors are grateful to Natural Sciences and Engineering Research Council of Canada for the financial support through its CRD program (RDCPJ 533629-18) and IRC program (IRCPJ 461745-18). The authors are also grateful for the support from the industrial partner in this research as well as the funding from Mitacs through its Mitacs Acceleration Program (IT27102).
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 149 • Issue 10 • October 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Nov 2, 2022
Accepted: May 8, 2023
Published online: Jul 17, 2023
Published in print: Oct 1, 2023
Discussion open until: Dec 17, 2023
ASCE Technical Topics:
- Analysis (by type)
- Automation and robotics
- Building materials
- Buildings
- Construction engineering
- Construction industry
- Construction management
- Engineering fundamentals
- Engineering materials (by type)
- Facilities (by type)
- Industrial facilities
- Materials engineering
- Models (by type)
- Offsite construction
- Sensitivity analysis
- Simulation models
- Structural analysis
- Structural engineering
- Structures (by type)
- Systems engineering
- Wood and wood products
- Wood structures
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