Scenario Cases

The following are scenario cases from manufacturing, quality, supply chain, service, and energy.
Click a chapter in the sidebar to jump to the corresponding scenario.

01 Urgent Orders & Scheduling

A large urgent order arrives from the business side (e.g., 10,000 units, 5-day delivery) while production lines are near capacity. The best scheduling decision must balance delivery, cost, waste, and stability.

User operations

Enter the War Room and select the "Smart Manufacturing Urgent Scheduling" Board Group to complete the entire urgent-order scheduling flow in the real-time multi-agent monitoring panel.

1. Submit the urgent scheduling request: type the urgent order needs (delivery date, quantity, customer info, priority, etc.) in the chat area on the right of the War Room and send to the group; the message is automatically forwarded to the "Command Center" Board Group
2. Watch the agents analyze: the sequence collaboration matrix on the left shows the analysis progress and status (online / offline / delayed / abnormal) of the "Material Management", "Capacity Planning", "Equipment Maintenance", and "Quality Management" agents in real time
3. Get solution comparisons: after the "Scheduling Optimization" agent produces candidate solutions, a solution comparison scorecard (including delivery attainment rate, cost, number of changeovers, etc.) is pushed directly in the chat area
4. Send an approval command: a supervisor sends an approval command in the chat (e.g., "Approve plan B"), and the "Coordination & Decision" agent confirms and automatically publishes it to ERP/MES
5. Track execution deviations: the dashboard continuously shows key metrics such as OTD delivery rate and line OEE; major anomalies trigger alert messages automatically

Key agent collaboration

Agent	Capability	Task description
Scheduling Optimization	Calls the APS engine to generate multiple schedules	Automatically simulates after receiving constraint parameters and delivers candidate solutions to the Coordination & Decision workflow
Coordination & Decision	Conflict mediation and multi-option comparison	Aggregates all constraints, outputs optimization recommendations, and submits them for supervisor approval
Material Management	Inventory, in-transit, and substitute material analysis	Queries WMS/MRP data, flags material gaps, and pushes procurement suggestions

Expected results

• Urgent-order response speed: from 1–2 days of manual back-and-forth → instant decisions in the meeting (90%+ faster)
• OTD delivery rate: balances urgent and existing orders; estimated 5–10 percentage point improvement
• Schedule stability: fewer unnecessary work order changes and less frequent line changeovers

Deployment reference

This scenario maps to the Smart Manufacturing Urgent Scheduling Board Group, which contains 8 Boards:

Board	Responsibility
Command Center	Receives urgent-order tasks, dispatches them to units, aggregates results, submits for supervisor approval, and publishes execution
Business Orders	Customer priority, delivery commitments, delay risks, and order adjustment suggestions
Capacity Planning	Line utilization, capacity gaps, overtime potential, line reallocation, and staffing constraint assessment
Material Management	Inventory queries, in-transit tracking, substitute material assessment, urgent purchasing, and partial-shipment suggestions
Scheduling Optimization	APS engine integration, candidate schedules, constraint scoring, and solution comparison
Equipment Maintenance	Equipment status, maintenance schedules, backup equipment, failure risks, and first-article confirmation
Quality Management	Quality risks, process qualification, inspection plans, SPC monitoring, and customer specification compliance
Coordination & Decision	Conflict detection, agent negotiation, compromise solutions, decision records, and supervisor reporting

02 AIoT Device Anomaly Monitoring

Traditional line monitoring relies on threshold alarms on dashboards; after an anomaly, staff must notify layer by layer, hunt for data, and diagnose the cause — repair takes a long time and expert experience is hard to reuse.

User operations

Enter the War Room and select the "AIoT Device Anomaly Monitoring" Board Group to monitor line equipment status and get intelligent diagnosis results in real time.

1. View the device health overview: the dashboard on the left shows equipment status across lines, with red/yellow indicators marking anomalous devices
2. Receive anomaly alerts: when the Edge Sensing agent detects sensor data outside the normal range, the War Room pushes an alert automatically with the device ID, anomalous parameter, and timestamp
3. Get root-cause diagnosis: the Anomaly Diagnosis agent pushes a root-cause analysis report directly in the chat, including likely causes, references to similar historical cases, and the affected scope
4. See adjustment suggestions: the Scheduling Coordination agent automatically produces scheduling adjustments and dispatch suggestions, including recommended maintenance engineer skill tags and estimated repair time
5. Track repair progress: the sequence collaboration matrix shows the full chain from anomaly trigger → diagnosis → dispatch → repair completion, monitoring repair time trends and more in real time

Key agent collaboration

Agent	Capability	Task description
Commander	Orchestrates cross-line event dispatch and agent scheduling	Receives anomaly events, dispatches them to specialist agents, and aggregates decisions
Anomaly Diagnosis	Cross-references maintenance history and signal signatures to locate root causes	Gets anomaly signals from the Edge Sensing agent and historical cases from the Knowledge Retention agent, then produces the diagnosis report
Quality Prediction	Assesses quality impact on WIP and shipping batches	Correlates production batches with inspection records and produces a quality impact assessment

Expected results

• Average repair time: down 35–50%
• Unplanned downtime hours: down 30–40%
• Equipment utilization: up 8–12%
• Knowledge reuse: standardized repair experience reduces dependence on individual experts

Deployment reference

This scenario maps to the AIoT Device Anomaly Monitoring Board Group, which contains 7 Boards (one agent each):

Board	Responsibility
Commander	Cross-line event dispatch, multi-agent scheduling, and decision aggregation
Edge Sensing	Streams PLC/sensor data in real time and detects anomalous signals
Anomaly Diagnosis	Cross-references maintenance history, process parameters, and signal signatures to locate root causes
Scheduling Coordination	Adjusts schedules and dispatch suggestions based on anomaly severity and current capacity
Quality Prediction	Assesses quality impact on WIP and shipping batches
Energy Governance	Monitors abnormal equipment energy use and correlates it with production schedules
Knowledge Retention	Records diagnosis processes and repair outcomes and writes them back to the knowledge base for reuse

03 Energy & Carbon Management

Meter, production, procurement, and carbon data are scattered across multiple systems. Anomalies are detected slowly, Scope 1/2/3 reporting is inconsistent, and carbon reports and energy optimization rely heavily on manual work.

User operations

Enter the War Room and select the "Energy & Carbon Management" Board Group to monitor energy anomalies, get optimization suggestions, and obtain carbon reports in real time.

1. View the energy dashboard: the dashboard on the left shows real-time energy data against baselines, with anomalous ranges highlighted
2. Energy anomaly alerts: the Anomaly Detection agent automatically pushes alerts for deviations in per-unit energy use, flagging root-cause candidates (e.g., idling equipment, peak-valley deviations)
3. Optimization suggestions: the Energy Optimization agent pushes peak-shifting and scheduling adjustment suggestions in the chat, showing estimated savings directly
4. Produce carbon reports: send the command "Generate this month's carbon report" in the chat, and the Compliance Reporting agent automatically produces an ISO 14064-compliant inventory report with an audit trail
5. Track carbon trends: the sequence collaboration matrix shows energy and carbon trend curves for comparison against baselines

Key agent collaboration

Agent	Capability	Task description
Task Orchestration	Breaks down energy events, schedules agents, and aggregates solutions	Receives anomaly events, assigns tasks, and aggregates optimization suggestions
Anomaly Detection	Identifies deviations of per-unit energy use from baseline ranges	Gets real-time data from the Energy Monitoring agent, triggers alerts, and flags root-cause candidates
Predictive Analytics	Forecasts future energy and carbon trends from orders and output	Combines production schedules with historical data to produce forecast reports

Expected results

• Carbon inventory cycle: down 70%
• Energy per unit of product: down 8–15%
• Abnormal power consumption: down 40%
• Three-year ROI: approximately 5.38x implementation cost (≈538%)

Deployment reference

This scenario maps to the Energy & Carbon Management Board Group, which contains 7 Boards (one same-named agent each):

Board	Responsibility
Task Orchestration	Breaks down energy events, schedules agents, and aggregates solutions
Energy Monitoring	Aggregates real-time meter, line, and equipment energy data
Anomaly Detection	Identifies per-unit energy deviations from baselines and triggers alerts
Carbon Calculation	Calculates Scope 1/2/3 emissions per the GHG Protocol
Energy Optimization	Proposes peak shifting, schedule adjustments, and load management
Compliance Reporting	Automatically produces inventory reports and audit trails
Predictive Analytics	Forecasts future energy and carbon trends from orders and output

04 Smart Service

Information from email, WeChat, phone, and chatbot channels is fragmented. Agents must query technicians and spare-parts data one by one, diagnosis queues cause delays, and repair experience is hard to standardize and retain.

User operations

Enter the War Room and select the "Smart Service" Board Group to track the full service-case flow and collaborate remotely with agents in real time.

1. Service case overview: the dashboard shows today's cases received, SLA attainment rate, and the distribution of cases by status
2. Track case processing: the sequence collaboration matrix shows each case's full flow — intake & classification → multimodal diagnosis → dispatch → QA inspection — with each agent's handling status at a glance
3. Get diagnosis results: the Multimodal Diagnosis agent pushes diagnosis conclusions in the chat, including image/video analysis results, likely faulty parts, and similar historical cases
4. Dispatch plans: the Dispatch agent pushes the engineer's on-site itinerary, while the Parts Management agent pushes spare-parts stock and stocking suggestions
5. Remote collaboration: field engineers upload fault images/videos in the chat; the Multimodal Diagnosis agent analyzes them instantly and pushes repair suggestions

Key agent collaboration

Agent	Capability	Task description
Service Desk	Breaks down service tasks and schedules agents	Oversees service cases, monitors SLA status, and aggregates resolution plans
Multimodal Diagnosis	Analyzes images/videos/IoT logs to locate root causes	Gets device data from the Device Data agent and cases from the Knowledge Retrieval agent, then produces the diagnosis conclusion
QA Inspection	Verifies safety processes and solution completeness	Reviews all proposed solutions and submits them for human approval after safety and compliance checks

Expected results

• First-response time: drastically shorter; parallel multi-agent analysis replaces queueing
• Remote-resolution rate: significantly higher, reducing unnecessary on-site dispatches
• Repair time: lower, with traceable step-by-step troubleshooting
• Knowledge assets: repair cases are retained automatically, shortening onboarding for new hires

Deployment reference

This scenario maps to the Smart Service Board Group, which contains 8 Boards (one agent each):

Board	Responsibility
Service Desk	Breaks down service tasks, assigns SLA deadlines, and schedules agents
Intake & Classification	Determines fault type and priority and checks warranty status
Multimodal Diagnosis	Analyzes images/videos/IoT logs to locate root causes
Knowledge Retrieval	Pulls manuals, historical similar-fault videos, and repair cases
Dispatch	Schedules engineers and plans on-site itineraries
Parts Management	Verifies stock, lead times, and substitute parts
Device Data	Parses IoT/PLC device operating data
QA Inspection	Verifies safety processes and solution completeness and submits for human approval

05 Supply Chain & Procurement

Demand fluctuation, shortages, RFQs, supplier risk, logistics tracking, and contract review are handled by different departments. Coordination usually takes a long time and rarely reaches the overall optimum.

User operations

Enter the War Room and select the "Supply Chain Coordination & Procurement" Board Group to monitor supply chain risks and get procurement decision support in real time.

1. View the supply chain risk dashboard: the dashboard shows stock-out alerts, supplier delivery performance, in-transit logistics status, and risk events
2. Receive risk alerts: the Risk Monitoring agent automatically pushes alerts for geopolitical/climate/raw-material price fluctuations, flagging the affected material list
3. Get procurement comparison suggestions: the Procurement Decision agent pushes multi-objective comparison results in the chat (combined price/lead-time/quality/carbon scores) so you can compare suppliers item by item
4. Review contract risk: upload a contract file or paste clauses in the chat; the Compliance Review agent automatically flags non-standard risk items and pushes its review opinion
5. Send a procurement decision: a supervisor sends "Approve supplier A" in the chat; the Control Center agent aggregates the action plan and triggers the approval flow

Key agent collaboration

Agent	Capability	Task description
Control Center	Breaks down supply chain events, schedules agents, and aggregates solutions	Receives procurement needs or risk alerts, assigns tasks, and produces feasible solutions
Procurement Decision	Multi-objective comparison (price / lead time / quality / carbon)	Gets supplier data from the Supplier Management agent and produces combined scores and recommendations
Risk Monitoring	Monitors geopolitical, climate, and raw-material price volatility	Automatically pushes risk alerts to the Control Center agent, triggering contingency options

Expected results

• Stock-out events: down 60%
• Procurement cycle: significantly shorter
• Inventory turnover: up 25%
• Contract review cycle: drastically compressed with fewer missed risks
• Three-year ROI: approximately 4–6x implementation cost

Deployment reference

This scenario maps to the Supply Chain Coordination & Procurement Board Group, which contains 7 Boards (one agent each):

Board	Responsibility
Control Center	Breaks down supply chain events, schedules agents, and aggregates solutions
Demand Forecasting	Forecasts demand from historical orders, promotions, and market signals
Procurement Decision	Multi-objective comparison (price / lead time / quality / carbon)
Supplier Management	Assesses delivery performance, financial health, and compliance
Logistics Coordination	Tracks in-transit shipments, estimates arrivals, and alerts on exceptions
Risk Monitoring	Monitors geopolitical, climate, and raw-material price volatility
Compliance Review	Uses AI to review contract clauses and identify non-standard risk items

06 AOI Quality Management

AOI, CMM, SPC, and process data from multiple factories are scattered. Humans must read images to analyze, then dispatch tasks and track improvements — and quality standards are hard to unify across sites.

User operations

Enter the War Room and select the "AOI Quality Management" Board Group to monitor cross-site quality data and get anomaly analysis and re-inspection support in real time.

1. View the quality monitoring overview: the dashboard shows each site's Cpk trends, defect distribution, re-inspection pass rate, and first-pass yield
2. Receive quality anomaly alerts: the SPC Analysis agent automatically pushes an alert when Cpk drops below grade D, flagging the anomalous batch number, process parameters, and current Cpk value
3. Get root-cause analysis: the Root-Cause Analysis agent pushes a report in the chat, tracing the anomaly to process parameters, material lot numbers, or equipment status
4. Handle re-inspection tasks: the Trace & Re-inspection agent pushes low-confidence cases to the chat; quality engineers can view the defect images and submit results, which the system writes back to the training set automatically
5. Track the improvement loop: the sequence collaboration matrix shows the full chain from anomaly trigger → root-cause analysis → corrective action → effectiveness verification

Key agent collaboration

Agent	Capability	Task description
Inspection Command	Orchestrates cross-site inspection events and task dispatch	Receives inspection anomalies, assigns subtasks, and aggregates quality reports
SPC Analysis	Monitors control charts in real time and alerts on trend shifts	Gets Cpk data from the Dimensional Measurement agent and triggers tiered alerts automatically
Trace & Re-inspection	Routes low-confidence cases to human re-inspection	Receives low-confidence results from the Defect Recognition agent, schedules re-inspectors, and writes back training data

Expected results

• Missed defect rate: down 60%
• Anomaly response time: from hours to minutes
• Prediction accuracy: 90%+
• Cross-site quality consistency: standardized inspection processes eliminate human judgment differences

Deployment reference

This scenario maps to the AOI Smart Quality Management Board Group, which contains 7 Boards (one agent each):

Board	Responsibility
Inspection Command	Orchestrates cross-site inspection events and task dispatch
Defect Recognition	Uses AI models to identify and classify appearance defects and keeps learning new defect types
Dimensional Measurement	Parses CMM data and compares against tolerances and Cp/Cpk
Equipment Communication	Unifies communication protocols across factory AOI/CMM/PLC systems
SPC Analysis	Monitors control charts in real time and alerts on trend shifts
Root-Cause Analysis	Traces anomalies to process parameters, material lots, or equipment status
Trace & Re-inspection	Routes low-confidence cases to human re-inspection and writes results back to the training set

07 Sales & Operations Planning

Take a consumer goods manufacturer as an example — spanning LED lighting, appliances, furniture, and storage, sold through Japanese and domestic e-commerce and offline stores. Every S&OP meeting requires long hours of manual Excel preparation, making it hard to compare overtime, line-change, and outsourcing options on the spot.

User operations

Enter the War Room and select the "Sales & Operations Planning" Board Group to review S&OP data in real time during meetings and run What-if simulations and resolution management.

1. Review pre-meeting results: the dashboard on the left shows order demand aggregated by the Order Demand Analysis agent, capacity load analyzed by the Capacity Planning agent, and the material readiness table compiled by the Material Readiness agent, with abnormal items flagged by red/yellow/green indicators
2. Review meeting topics: the S&OP Lead agent automatically pushes meeting topics in the chat, sorted by anomaly priority
3. Run What-if simulations: send a simulation command in the chat (e.g., "If we insert an urgent order of 10,000 units, what's the impact on existing orders?"), and agents produce candidate solutions with impact assessments within 30 seconds
4. Record meeting resolutions: @mention the Meeting Collaboration agent in the chat and send a resolution (e.g., "Complete the B-line mold change by Friday; owner: Manager Zhang"); the system archives it automatically with a due date
5. Track resolution execution: the dashboard shows each resolution's progress, and overdue items escalate automatically

Key agent collaboration

Agent	Capability	Task description
S&OP Lead	Aggregates agent results, organizes the agenda, and monitors anomalies	Orchestrates the S&OP overview, pushes alert lights, and coordinates agents
Demand Analysis	Aggregates order demand and identifies urgent orders and conflicts	Gets order data from ERP/CRM, flags inserted orders, and identifies risks
Capacity Planning	Capacity load analysis and What-if simulation	Gets utilization from MES/APS and produces scenario comparisons instantly

Expected results

• Meeting-prep hours: from 4+ hours → under 30 minutes (85% saved)
• Meeting duration: from 90+ minutes → 45–60 minutes (35–50% shorter)
• Stock-out alert lead time: from after-the-fact notification → automatic alerts 2–4 weeks in advance
• Resolution overdue rate: approaching zero (systematized archiving + automatic escalation)

Deployment reference

This scenario maps to the Sales & Operations Planning Board Group, which contains 7 Boards:

Board	Responsibility
S&OP Lead	Orchestrates S&OP decisions and coordinates the order, capacity, material, and quality agent clusters
Order Demand Analysis	Parses order demand and shipping priorities and monitors order risk and delivery status
Capacity Planning	Plans line capacity and schedules and monitors bottlenecks and takt time
Material Readiness	Tracks material readiness and purchasing progress and identifies shortage risks and alternatives
Quality Risk	Assesses quality risks and exception handling, mapping to quality events and corrective actions
Meeting Collaboration	Organizes S&OP meetings and records agenda, resolutions, and action items
Resolution Tracking	Tracks resolution progress and monitors action-item closure and delays

08 Order-to-Delivery OTD

Take an electronics factory doing SMT assembly as an example: inquiry → delivery commitment (ATP/CTP) → order entry → MRP → procurement → production → shipping are handled in silos. Delivery quotes are slow, and critical material shortages and capacity conflicts often surface only at execution time.

User operations

Enter the War Room and select the "Order-to-Delivery" Board Group to track orders end-to-end from inquiry to shipment and get real-time decision support.

1. View the dashboard: the dashboard shows today's delivery attainment rate, delay-cause breakdown, bottleneck analysis per stage, and a list of at-risk orders
2. Submit an inquiry for calculation: send the inquiry needs (product model, quantity, desired delivery date) in the chat; the Delivery Calculation agent pushes the committed quantity and delivery date within 10 minutes
3. Get stock-out alerts: the Material & Capacity Planning agent automatically pushes the material gap list, flagging critical materials, substitute suggestions, and expected arrival times
4. Track the full order flow: the sequence collaboration matrix shows each order's status across inquiry → ATP calculation → order entry → MRP → procurement → production → shipping, with delayed stages highlighted
5. Get decision suggestions: the Performance & Decision agent pushes a daily decision-suggestion list, flagging at-risk orders, action priorities, and recommended approaches

Key agent collaboration

Agent	Capability	Task description
Delivery Calculation	Calculates committed quantity and delivery date in real time	Gets inventory and capacity data from the Material & Capacity Planning agent and produces calculation results
Material & Capacity Planning	Runs MRP explosion and compares APS capacity against material gaps	Automatically triggers calculation after receiving an SO and pushes stock-out alerts to the Procurement Collaboration workflow
Performance & Decision	Aggregates the order risk dashboard and produces action recommendations	Aggregates end-to-end data from all workflows and produces a daily decision-suggestion list

Expected results

• OTD delivery rate: from ~82% → 95%+ (+13%+)
• Inquiry response time: from 4–6 hours → under 30 minutes (90%+ faster)
• Stock-out alert lead time: from after-the-fact → automatic alerts 2–4 weeks in advance
• Decision support cadence: from weekly aggregation → daily real-time updates

Deployment reference

This scenario maps to the Order-to-Delivery Board Group, which contains 8 Boards:

Board	Responsibility
Business Lead	Customer inquiry/QA window; receives inquiries, replies with quotes and delivery dates, and sends shipping notices
Delivery Calculation	Back-office support for business; queries available inventory and capacity in real time and calculates committed delivery dates and quantities
Order Conversion	Verifies customer orders against quotes — part number / price / delivery date / credit limit comparison
Material & Capacity Planning	The process hub; automatically triggers MRP/APS calculation after a sales order is created
Procurement Collaboration	Runs supplier RFQ/negotiation, sends purchase orders, and chases delivery; alerts on critical material gaps
Production Execution & Quality	Executes line work orders with quality monitoring, integrating SPI/AOI/X-Ray data for instant alerts
Shipping & After-Sales	After readiness is confirmed, coordinates picking, packing, and shipping, processes documents, and handles after-sales complaints
Performance & Decision	Manager-level decision support; aggregates end-to-end data into a decision-suggestion list