A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Learning Factory for Construction to Provide Future Engineering Skills beyond Technical Education and Training
This paper describes the design of a learning factory for construction that addresses the growing demand for future skills of production engineers and staff. Existing learning factories often focus on the technical skills whereas the presented learning factory also trains decision making, group work, and project performance monitoring skills. This paper refers to the existing categories of learning factories and unveils its numerous features relevant for construction. The design of our learning factory includes theoretical and practical parts, which prove to be successful when realized by the authors. The layout consists of multiple stages of a production system, from manual to automatized off-site manufacturing, in-time delivery, and robotic assembly. The practical tasks cover the introduction of smart devices, connection of information flows as well as monitoring of performance and control. The didactical design of the training program provides a sustainable approach that includes preparation utilizing lean construction principles, mid-term coaching, and success monitoring after the training. Here, the emphasis of the presented work focuses on closing the feedback loop of lean construction planning, progress tracking, and status control using cloud-based information modeling as well as Internet-of-Things (IoT) technology for reporting actual progress in the production system. As such, learning factories are envisioned to become part of a research and teaching environment where one of the underlying goals is to enable production engineers and staff for change management, decision making, and innovation in construction. Future work on learning factories in construction include a detailed study of the learning outcomes.
Learning Factory for Construction to Provide Future Engineering Skills beyond Technical Education and Training
This paper describes the design of a learning factory for construction that addresses the growing demand for future skills of production engineers and staff. Existing learning factories often focus on the technical skills whereas the presented learning factory also trains decision making, group work, and project performance monitoring skills. This paper refers to the existing categories of learning factories and unveils its numerous features relevant for construction. The design of our learning factory includes theoretical and practical parts, which prove to be successful when realized by the authors. The layout consists of multiple stages of a production system, from manual to automatized off-site manufacturing, in-time delivery, and robotic assembly. The practical tasks cover the introduction of smart devices, connection of information flows as well as monitoring of performance and control. The didactical design of the training program provides a sustainable approach that includes preparation utilizing lean construction principles, mid-term coaching, and success monitoring after the training. Here, the emphasis of the presented work focuses on closing the feedback loop of lean construction planning, progress tracking, and status control using cloud-based information modeling as well as Internet-of-Things (IoT) technology for reporting actual progress in the production system. As such, learning factories are envisioned to become part of a research and teaching environment where one of the underlying goals is to enable production engineers and staff for change management, decision making, and innovation in construction. Future work on learning factories in construction include a detailed study of the learning outcomes.
Learning Factory for Construction to Provide Future Engineering Skills beyond Technical Education and Training
Teizer, Jochen (author) / Chronopoulos, Christos (author)
Construction Research Congress 2022 ; 2022 ; Arlington, Virginia
Construction Research Congress 2022 ; 224-233
2022-03-07
Conference paper
Electronic Resource
English
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