A cyber-physical production control paradigm for site waste mitigation: Synchronizing digital twin technology and lean construction principles through nanotechnology
DOI:
https://doi.org/10.56053/10.4.1923Keywords:
Nanotechnology, Nanosensors, Digital Twin, Lean ConstructionAbstract
The construction industry continues to suffer from substantial productivity losses due to inefficient operations, wasteful use of materials, broken equipment and a lack of cohesive production management. Lean Construction is a good way to think about getting rid of waste and it remains difficult to implement because information is often delayed or not complete. Similarly, Digital Twin technology creates virtual, moving versions of construction sites, but it does not inherently offer a predictable way to reduce waste. This paper introduces a Digital Twin-Lean Management (Nano-DTLM) framework that uses nanotechnology to optimize Cyber-physical systems, Internet of Things (IoT), Digital Twin technology, Lean Construction and smart nanosensor technologies for real-time production enhancement. The proposed framework is based on edge-computing analytics, graphene-based strain sensors, nano-enabled RFID tags, nanoscale environmental sensors, and enhanced sensing for more accurate decision making, structure monitoring and foresight. To test the framework using 4D BIM, UWB positioning, RFID, telematics, and nano-enabled sensing technologies, a controlled field experiment is conducted in a 15-story commercial building project in Dubai, UAE. When tested, the experimental implementation reduced crew idle time by 29.7%, equipment downtime by 30.9%, distance that materials had to be transported by 21.9% and increased worker productivity by 21.4%. Statistics demonstrated significant improvements (p < 0.05; Cohen's d = 0.82). Nanotechnology significantly improved the sensing accuracy, reliability of data, ability to predict maintenance needs and responsiveness of cyber-physical systems. The proposed Nano-DTLM framework provides a smart, self-monitoring and predictive production management paradigm that helps to make Construction 4.0 and the next generation of smart construction sites more sustainable.
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