Purpose Most of the 3D printing machines do not comply with the requirements of on-site, large-scale multi-story building construction. This paper proposes the conceptualization of a Tower Crane (TC)-based 3D Printing controlled by Artificial Intelligence (AI) as the first step toward a large 3D printing development for multi-storey buildings. It aims to overcome the most important limitation of additive manufacturing in the construction industry (the build volume) by exploiting the most important machine used in the field: tower cranes. It assesses the technology feasibility by investigating the accuracy reached in the printing process. Design/methodology/approach The research is composed of three main steps: firstly, the Tower Crane (TC)-based 3D printing concept is defined by proposing an aero-pendulum extruder stabilized by propellers to control the trajectory during the extrusion process; secondly, an Artificial Intelligence-based system is defined to control both the crane and the extruder toolpath by exploiting Deep Reinforcement Learning (DRL) control approach; thirdly the proposed framework is validated by simulating the dynamical system and analysing its performance. Findings The TC-based 3D printer can be effectively used for additive manufacturing in the construction industry. Both the TC and its extruder can be properly controlled by an AI-based control system. The paper shows the effectiveness of the aero-pendulum extruder controlled by AI demonstrated by simulations and validation. The AI-based control system allows for reaching an acceptable tolerance with respect to the ideal trajectory compared with the system tolerance without stabilization. Originality/value In related literature, scientific investigations concerning the use of crane systems for 3D printing and AI-based systems for control are completely missing. The proposed research demonstrates for the first time the effectiveness of this technology conceptualized and controlled with an intelligent DRL agent. Practical implications The results provide the first steps toward the development of a new additive manufacturing system for multi-storey constructions exploiting the TC-based 3D Printing. The demonstration of the conceptualization feasibility and the control system opens up new possibilities to activate experimental research for companies and research centres.

A new concept for large additive manufacturing in construction: Tower crane-based 3D printing controlled by deep reinforcement learning

Valentino Sangiorgio;
2023-01-01

Abstract

Purpose Most of the 3D printing machines do not comply with the requirements of on-site, large-scale multi-story building construction. This paper proposes the conceptualization of a Tower Crane (TC)-based 3D Printing controlled by Artificial Intelligence (AI) as the first step toward a large 3D printing development for multi-storey buildings. It aims to overcome the most important limitation of additive manufacturing in the construction industry (the build volume) by exploiting the most important machine used in the field: tower cranes. It assesses the technology feasibility by investigating the accuracy reached in the printing process. Design/methodology/approach The research is composed of three main steps: firstly, the Tower Crane (TC)-based 3D printing concept is defined by proposing an aero-pendulum extruder stabilized by propellers to control the trajectory during the extrusion process; secondly, an Artificial Intelligence-based system is defined to control both the crane and the extruder toolpath by exploiting Deep Reinforcement Learning (DRL) control approach; thirdly the proposed framework is validated by simulating the dynamical system and analysing its performance. Findings The TC-based 3D printer can be effectively used for additive manufacturing in the construction industry. Both the TC and its extruder can be properly controlled by an AI-based control system. The paper shows the effectiveness of the aero-pendulum extruder controlled by AI demonstrated by simulations and validation. The AI-based control system allows for reaching an acceptable tolerance with respect to the ideal trajectory compared with the system tolerance without stabilization. Originality/value In related literature, scientific investigations concerning the use of crane systems for 3D printing and AI-based systems for control are completely missing. The proposed research demonstrates for the first time the effectiveness of this technology conceptualized and controlled with an intelligent DRL agent. Practical implications The results provide the first steps toward the development of a new additive manufacturing system for multi-storey constructions exploiting the TC-based 3D Printing. The demonstration of the conceptualization feasibility and the control system opens up new possibilities to activate experimental research for companies and research centres.
File in questo prodotto:
File Dimensione Formato  
10-1108_CI-10-2022-0278.pdf

Solo gestori archivio

Tipologia: PDF editoriale
Dimensione 1.85 MB
Formato Adobe PDF
1.85 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/797551
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 3
social impact