Universal AI-Driven Manufacturing Facility
Version: 1.0
License: MIT
Status: Concept Design Document
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Overview This system is a general-purpose manufacturing platform that allows users to express their product requests in natural language (e.g., “I want a product like this”), which are then interpreted by a reception Large Language Model (LLM). The system automatically executes the entire process from product design to prototyping and mass production. The goal is to enable users without specialized skills to realize high-quality products in a short period of time.
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End-to-End Workflow Step 1 – Requirements Intake The user inputs product requirements in natural language to the Reception LLM.
The LLM organizes the requirements, asks clarifying questions, and finalizes a requirements summary.
Output: requirements.json (machine-readable format)
Step 2 – Specification Normalization The Spec Parser LLM converts the requirements into a standard schema.
All numerical values, units, and constraints are clearly defined, removing ambiguity.
Output: normalized_spec.json
Step 3 – Design Generation The CAD Generator creates 2D drawings and 3D models from the normalized specification.
The Simulation Engine performs structural, thermal, and functional verification.
Output: design_files/ (STEP, STL, DWG, etc.)
Step 4 – Compliance & Safety Check The Compliance LLM maps the design to relevant market regulations (e.g., electrical safety, EMC, food safety).
If non-compliance is detected, the system proposes corrective actions.
Output: compliance_report.pdf
Step 5 – Manufacturing Planning The BOM Planner generates a Bill of Materials (BOM).
Suppliers, lead times, and cost estimates are identified.
Output: manufacturing_plan.xlsx
Step 6 – Prototyping & Testing The Prototyping Engine issues fabrication instructions for initial prototypes via factory lines or 3D printing.
The Test LLM generates test procedures and executes automated or semi-automated testing.
Output: test_report.pdf
Step 7 – Approval Gate Human reviewers (or committees) verify prototypes and test results.
If needed, feedback is sent back to the design stage.
Output: approval_log.json
Step 8 – Mass Production The production line receives manufacturing orders.
Production status is displayed in real time on a dashboard.
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System Architecture Core Modules Module Name Function Reception LLM Accepts user requests, organizes requirements, generates clarifying questions Spec Parser LLM Converts natural language to standardized schema CAD Generator Produces drawings and 3D models Simulation Engine Validates structural, thermal, and operational properties Compliance LLM Checks compliance with regulations and standards BOM Planner Creates bill of materials and procurement plan Prototyping Engine Issues prototyping instructions and line control Test LLM Generates validation plans and pass/fail criteria Approval System Human approval gate Production Controller Controls mass production and monitors progress
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Data Flow Diagram (Overview) [User Input] ↓ [Reception LLM] ↓ requirements.json [Spec Parser LLM] ↓ normalized_spec.json [CAD Generator + Simulation Engine] ↓ design_files/ [Compliance LLM] ↓ compliance_report.pdf [BOM Planner] ↓ manufacturing_plan.xlsx [Prototyping Engine + Test LLM] ↓ test_report.pdf [Approval System] ↓ approval_log.json [Production Controller] → Mass Production
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APIs and Interfaces REST API: For specification input, status retrieval, and results fetching
Web UI: Chat-based requirement intake with design previews
CLI: Direct specification input for advanced users
- Future Extensions AI-to-AI automated ordering and collaborative manufacturing
Full digital twin integration for production optimization
Decentralized manufacturing networks by region