Deeply Rooted in Industrial Scenarios — AI-Driven Data Acquisition & Nucleus Intelligent Decision-Making
深耕工业场景，AI 驱动的数据采集系统与核枢 Nucleus 智能决策
Welcome. Today we present StarCore, a technology company focused on AI-powered industrial data acquisition and intelligent decision-making solutions.
Section · 01
Company Introduction
Deep industry expertise, future-oriented innovation
Section one covers who we are, our team, and our strategic position in the AI+Industrial landscape.
About · Our Foundation
Company Overview
StarCore Technology Co., Ltd. was founded at a pivotal stage of the AI era. With years of deep roots in industry, we have forged a hybrid team fluent in both shop-floor processes and frontier AI — balancing theory and practice to ensure reliable delivery of demanding industrial deployment projects, from R&D design through on-site deployment.
18Core team members
4Postgraduate talents · 1 PhD · 3 Master's
6+Cross-disciplinary fields
DisciplinesArtificial IntelligenceMotion ControlSoftware EngineeringAlgorithm EngineeringMechanical DesignElectrical Control
StarCore has deep industrial roots; an 18-person multidisciplinary team (1 PhD, 3 Master's) spanning AI, motion control, software engineering, algorithms, mechanical design and electrical control.
Vision · AI + Industry
StarCore Technology: Strategic Positioning in AI + Industry
01
Strategic Background
StarCore was born during the global industrial-intelligence transformation. With deep roots in industry, we made an early, forward-looking commitment to the "AI + Industry" frontier — applying artificial intelligence to reshape data and process in high-end manufacturing.
02
Technology Engine
StarCore leverages AI large models as its technology engine, focusing on high-end manufacturing and high-demand scenarios. We deeply integrate academic frontiers with industry pain points, committed to "replacing experience with algorithms, reshaping processes with data," driving production efficiency and quality control to leap forward.
03
Core Business
Our core business is organized around two pillars: Data Acquisition Systems, connecting shop-floor equipment and NC programs through edge capture and real-time data infrastructure; and Nucleus, an AI process-control platform delivering production visualization, OEE analytics, digital-twin dashboards and AI process optimization — turning data into decisions.
04
Capability Advantage
StarCore possesses a multidisciplinary professional technical team covering mechanical design, electrical control, software development, and algorithm modeling. Backed by solid engineering depth and rich hands-on field experience, we have full-process capabilities from R&D design and prototype verification to on-site implementation and continuous optimization.
Four pillars: forward-looking AI + Industry positioning, an AI-driven technology engine, two core business pillars — Data Acquisition Systems and Nucleus — and end-to-end execution capability.
Section · 02
Product Portfolio
Data Acquisition Systems · Nucleus
This section covers our two core pillars — Data Acquisition Systems (edge infrastructure) and Nucleus (AI process-control platform) — one product per slide.
Products · Data to Decisions
From Data Acquisition to AI Decisions, One Native Platform
Data Acquisition · Edge Infrastructure
Full-Chain Digital Data Acquisition System
Full-chain data capture and connectivity from shop-floor equipment to edge gateways — the unified data foundation for every AI decision Nucleus makes.
Digital shop-floor production & NC program management (eMDC Plus / eDNC Plus)
Edge data acquisition & device connectivity (eAdapter / eMagicBox)
Out-of-the-box connectivity for 100+ machine-tool brands
AI-Native · Nucleus
Nucleus AI Process-Control Platform
Built on the unified data foundation, Nucleus lets AI move from visualization to closed-loop decisions — data isn't just seen, it drives action.
Production visualization, analytics reports & OEE performance analytics
Factory digital-twin AI dashboard
AI process optimization, smart scheduling & knowledge copilot
Two core pillars: Data Acquisition Systems (edge infrastructure) and Nucleus (AI process-control platform). The following slides cover one product per page, starting with Data Acquisition Systems.
Flagship Platform · AI Process Control
Nucleus 核枢
The AI control core for manufacturing
What we build goes beyond data analysis. Nucleus unifies the factory's full-spectrum data — equipment · process · quality · scheduling — into a single intelligent core, using AI to reach into the production process itself and drive real decisions from design to the shop floor.
Nucleus is built for smart manufacturing: a unified data core connects equipment, process, quality and scheduling, letting AI move from visibility to closed-loop decisions across every process step.
DesignSchedulingProcess ParametersFeedback Loop
Nucleus is our flagship AI process-control platform: beyond data analysis, it uses AI to reach into design, scheduling, process-parameter optimization and feedback loops, moving from data visibility to process-level decisions.
Nucleus, three layers: the bottom eAdapter edge gateway connects every device (CNC/PLC/metrology); the middle time-series DB with live monitoring/OEE/DNC/LIMS captures the data; the top AI decision layer reaches into design, scheduling, parameter tuning and feedback loops. Data up, decisions down.
Nucleus · AI in the Production Process
Four points where AI enters the process
🎯
Design · Manufacturability upfront
AI-assisted design & process planning — analyze manufacturability and process risk straight from CAD / drawings, surfacing issues at the design stage to cut downstream rework.
🗓️
Smart Scheduling · Dynamic optimization
Combining real-time equipment status, capacity and due dates, AI generates and dynamically adjusts workshop-level schedules — practical and executable, lifting utilization and on-time delivery.
⚙️
Process Parameters · Algorithms over experience
From historical process and quality data, recommend and continuously self-optimize key machining parameters — turning veteran know-how into reusable, iterable algorithms.
🔄
Feedback Loop · Continuous learning
Production and quality data flow back in real time, forming an "inspect → analyze → tune → re-inspect" loop that drives alerts, traceability and continuous process improvement.
What sets Nucleus apart from "just analytics": (1) design-stage manufacturability; (2) dynamic smart scheduling; (3) parameters by algorithm, not experience; (4) a production-quality feedback loop that keeps learning.
AI Intelligent Systems · eMDC Plus / eDNC Plus
Shop-Floor Production & NC Program Management
Real-Time Machine Status (MDC)
Continuously tracks CNC, injection-molding, and robot status — running, idle, alarm, and down — across the entire shop floor.
Distributed NC Program Management (DNC)
Centralizes NC program version control, remote program calls, and upload/download to cut setup time and eliminate machine-side program errors.
Automated Reporting & Traceability
Auto reporting and paperless production replace manual logs, giving every part a full production traceability record.
Utilization & OEE Roll-Up
Rolls up machine utilization and OEE for every workstation, feeding the eViewSuit visualization layer in real time.
eKanban — live shop-floor production board
eMDC Plus and eDNC Plus form the shop-floor management layer: real-time machine status, distributed NC program control, automated reporting, and OEE roll-up.
AI Intelligent Systems · eAdapter / eMagicBox / eRealTsDB
Universal Edge Acquisition & Real-Time Data Infrastructure
eAdapter — Acquisition Adapter
High-performance, high-concurrency drivers across CNCs, PLCs, robots, and smart instruments, with cross-platform deployment.
eMagicBox — Edge Gateway
On-premise edge hardware that normalizes field-bus and industrial-network signals before they ever reach the enterprise network.
eRealTsDB — Time-Series Database
Distributed, clustered, high-availability storage built for million-point-scale industrial time series.
Broad, out-of-the-box connectivity — 100+ machine brands and controllers, standard protocols (OPC UA/DA, Modbus, MQTT, REST API, MTConnect), plus custom third-party drivers on request.
eAdapter and eMagicBox handle universal edge acquisition; eRealTsDB stores it at scale. Broad connectivity covers 100+ machine brands via standard industrial protocols.
AI Intelligent Systems · eViewSuit / Nucleus Analytics
Production Visualization · Analytics Reports · OEE
Secmachine-state refresh
Multishift / line / station
Loopalerts to improvement
Production Visualization
Maps takt, status, WIP and alarms into one live view across shop-floor screens, office and mobile.
Analytics Reports
Summarizes output, downtime, quality trends and anomaly clusters into daily reports and cockpits.
OEE Analytics
Breaks capacity loss into availability, performance and quality, with AI root-cause hints and priorities.
This page upgrades the former visualization/OEE slide into three capabilities: live production visualization, analytics reporting, and OEE loss attribution. The two new charts show a production report and an AI-assisted OEE analysis.
AI Intelligent Systems · Factory Digital Twin
Factory Digital Twin AI Dashboard
AI Agent Orchestration
Streams shop-floor data into a simulatable digital twin.
96%AI scheduling confidence
Evaluates rush orders, bottlenecks and due-date risk, then recommends minute-level schedules.
Anomaly AlertQuality ForecastEnergy Opt
From Dashboard to Decision
Pushes root causes and actions to supervisors and process engineers.
The next page becomes a more futuristic factory digital twin dashboard: real-time acquisition, AI prediction, scheduling optimization and shop-floor feedback are connected into one decision loop.
AI Intelligent Systems · AI-Driven
AI Process Optimization & Manufacturing Knowledge Assistant
Recipe & Parameter Optimization
From Trial-and-Error to Data-Driven Tuning
Improves recipe and tool-setting parameters with AI, turning experience-based adjustment into closed-loop optimization for yield, consistency, and cycle time.
Learns from historical process and quality data
Continuously narrows parameter windows as new data arrives
Recommends, rather than dictates — engineers stay in control
Manufacturing Knowledge Assistant
AI Agent + RAG Over Your Own Documentation
Stores process manuals, SOPs, and troubleshooting records as searchable knowledge, so engineers get a sourced answer instead of hunting through documents.
Docs
→
Vectors
→
AI Agent
→
Answer
Two complementary AI capabilities: closed-loop recipe/parameter optimization, and a RAG-based knowledge assistant that searches manufacturing documentation.
Section · 03
Technology Implementation Case Studies
Real-world deployments across industries
Section three showcases representative case studies, including the Volkswagen transmission plant traceability system, FAW Xichai Smart Factory, and the Igor automated dispatch system.
Automotive Manufacturing · Transmission Line Traceability
Volkswagen Transmission Plant Data Traceability System
Production Equipment Data Capture
Connects critical machining equipment and captures machine status, cycle, alarms and operating parameters as the line data foundation.
Process & Batch Traceability
Links part, station, machine and time records with feeding speed, spindle speed, temperature, load and other key process parameters.
MDC Data CenterMachine ParametersBatch Trace
Faster Quality Root Cause
Traces machines, process steps and parameter changes from the data center to support quality analysis, audits and continuous improvement.
Added as the first case in the deployment section: a Volkswagen transmission manufacturing data traceability system. MDC Data Center captures equipment status and process parameters, connecting line, machine, station, batch and quality data into a traceable loop.
Engine Manufacturing · Smart Factory Digital Line
FAW Xichai Smart Factory Case
Transparent Automated Line
Connects machining equipment, material movement, station takt and shop-floor status into one data view for line-level visibility.
Equipment Connectivity & Process Monitoring
Captures machine status, cycle, process parameters and exceptions around critical equipment for workshop monitoring and process tracking.
Smart LineEquipment IoTProcess Monitor
Quality & Efficiency Loop
Links production data with quality outcomes to support takt optimization, exception localization and continuous improvement.
Added after the Volkswagen case: FAW Xichai Smart Factory. The page focuses on automated line transparency, equipment connectivity, process monitoring, and the production-quality feedback loop.
Automated Line · MES Dispatch and Logistics Orchestration
Igor Automated Dispatch System Case
MES Work Order Triggering
MES releases work orders and process requests, then the system evaluates station state, buffer status and the next routing step.
AGV / Conveyor Orchestration
Conveyors, fixtures, AGVs and process equipment are coordinated from loading and transfer through process completion.
MESAGV DispatchRouting
Exception Recovery & State Trace
Equipment state, WIP location and process completion feedback support exception handling, route rollback and traceability.
Added after the FAW Xichai case: Igor automated dispatch system. The page highlights MES triggering, AGV/conveyor orchestration, equipment-process linkage, exception rollback and state traceability.
Section · 04
Service Delivery Full-Process Assurance
From R&D to deployment, training to continuous optimization
Section four outlines our comprehensive service delivery model covering design, verification, deployment, training, and ongoing support.
Delivery · Comprehensive Support
End-to-End Service Delivery Model
Deep Requirements Analysis & Scenario Adaptation
For clients' specific needs and pain points across device connectivity, data acquisition, and production management, we conduct in-depth research and requirement decomposition. Combined with client production line environment, system architecture, and data scale, we develop personalized implementation pathways ensuring solutions align tightly with actual working conditions.
Multidisciplinary Custom Technical Architecture
Integrating device connectivity, edge computing, software development, and AI algorithm modeling capabilities to build clients' own data acquisition and intelligent decision systems. For example, in a large-scale production-line traceability project, we combined edge gateways with a real-time database to achieve second-level data synchronization across an entire factory's equipment.
Providing services from solution design, system integration testing, on-site implementation to continuous optimization. Relying on our proprietary AI agent system and multidisciplinary technical team, we rapidly respond to changing client needs, achieving quick implementation and iterative upgrades in complex production environments, such as dedicated traceability and auto-dispatch algorithms developed for large-scale assembly lines that automatically adjust scheduling logic for different line configurations.
Successful Case Validation: Multi-Domain Custom Needs
Successfully delivered the Volkswagen transmission plant data traceability system, the FAW Xichai Smart Factory digital platform, the Igor automated dispatch system, and other customized cases covering automotive components and equipment manufacturing, proving outstanding advantages in complex production environments and large-scale data integration projects, achieving dual improvements in production efficiency and decision quality for clients.
Our service model emphasizes deep requirements analysis, multidisciplinary custom architecture, rapid iteration, and proven multi-domain success.
Process · Five-Stage Lifecycle
Full Lifecycle Service Process
📐
R&D Design & Solution Customization
Requirements analysis, solution design, custom algorithm development
🔬
Prototype Verification & Testing Optimization
System integration testing, data validation, iterative refinement
⚙️
On-Site Implementation & Integration Deployment
Equipment installation, system integration, production line interfacing
We provide 7×24 technical support through remote monitoring and regular on-site inspections, collecting operational data and continuously optimizing algorithm models and equipment performance to ensure long-term efficient and reliable system operation.
Five-stage service lifecycle: R&D design, prototype verification, on-site deployment, training and technology transfer, plus continuous optimization with 7×24 support.
Thank You
StarCore Technology Co., Ltd.
Data AcquisitionNucleusAI Process ControlFull-Process Delivery
Thank you for your attention. We look forward to collaborating with you to deliver AI-driven digitalization and intelligent decision-making solutions.
