Construction Design Data Vetting for Automated Build Sequencing
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Solution Overview
Problem
The construction industry lacks a comprehensive digitalized system that can convert design component data from outside sources into a unified format for use by multiple software-based modules to automate the construction process from design concept to final build, requiring a common communicator and organizer to facilitate communication and organization among various process parts, and built-in automated analytics to ensure accuracy, safety, and competence in automated construction.
Innovation Solution
A data conversion, data entry, and analytics system that receives electronic project design data, vets its competency, and communicates with downstream components to automate construction processes, using self-evolving intellect and AI to ensure compliance, safety, and optimal assembly sequencing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a comprehensive digitalized system is implemented to convert design component data into unified format for automated construction, then automation extent and productivity are improved, but device complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: a data conversion module that transforms design component data into unified format, a communication module that facilitates data exchange between upstream design sources and downstream construction modules, and an analytics module that provides automated analysis. This segmentation allows each module to handle specific tasks independently, reducing overall system complexity while maintaining high automation capability.
Solution Approach 2:
The patent introduces a centralized data conversion and communication system that acts as an intermediary between upstream design component data sources and downstream construction modules. This intermediary translates various design data formats into a unified standard format, enabling seamless communication without requiring direct integration between all system components, thereby simplifying the overall architecture.
2Reliability
If data vetting and analytics are performed to ensure design accuracy and safety, then reliability is improved, but loss of time increases
Solution Approach 1:
The system performs data vetting and competency analysis as preliminary actions during the data conversion phase, before the data is passed to downstream construction modules. By validating design accuracy, safety requirements, and competency standards upfront, the system ensures reliability without requiring repeated checks during subsequent construction phases, thereby minimizing time loss.
Solution Approach 2:
The analytics module provides automated feedback on data quality, identifying issues with design accuracy or safety compliance and suggesting corrections. This feedback mechanism enables rapid iteration and validation, ensuring high reliability while minimizing time loss through efficient, automated analysis rather than manual review processes.
Data Source
AI summary
A data entry and analytics system is configured to receive and vet digital project design data and support construction automation processes. The overall system includes a centralized data entry and analytics component configured to receive digital project design data for a project design from at least one upstream source; analyze the digital project design data to determine whether the data competently supports a complete construction of the project design in an automated manner; provide a mechanism for updating the digital project design data so as to ensure the data competently supports the project design and an automated complete construction thereof; and communicate the digital project design data as vetted to downstream components for enabling and competently supporting completion of the project design and the automated complete construction thereof. Certain analogous methodology is further disclosed.