KDG Workspace

IoT sensors (vibration, temperature, current, pressure, etc.) installed on manufacturing and plant equipment continuously generate data 24/7, but distinguishing 'anomalies requiring immediate action' from 'normal-range fluctuations' requires the judgment of veteran engineers who understand each equipment's characteristics and operating conditions.

This solution leverages the existing sensor monitoring infrastructure as-is. Sensor data is automatically collected 24/7 and stored in the system. After data collection, automated checks are performed based on thresholds configured for each piece of equipment.

KDG systematizes the diagnostic knowledge cultivated by veteran equipment maintenance engineers, including knowledge for estimating failure modes from vibration frequency characteristics, predicting degradation rates from temperature trends, and identifying root causes of anomalies from multi-sensor correlations.

Automate the process from sensor anomaly detection to diagnostic report generation, supporting continuous CBM monitoring.

CBM (Condition-Based Maintenance) systems are essential tools for equipment condition monitoring and diagnostics, but conventional systems were only available in office PC environments, preventing field engineers from checking equipment status in real time during rounds.

Field engineers simply open the Mobile CBM app on their mobile device (smartphone or tablet) and scan the QR code attached to the equipment to access that equipment's sensor data, diagnostic results, and maintenance history.

The knowledge referenced by Mobile CBM is the same KDG knowledge base as the CBM dashboard. Vibration diagnostic standards, failure mode DB, maintenance decision criteria, and trend analysis knowledge are all accessible from mobile devices.

Complete equipment status checks, diagnostic reference, and data entry during field rounds with a single mobile device, improving patrol efficiency and initial response speed.

Manufacturing and plant equipment maintenance plans are required to transition from conventional TBM (Time-Based Maintenance) to CBM (Condition-Based Maintenance), but this transition decision requires advanced knowledge that comprehensively considers equipment failure mechanisms, operating conditions, maintenance costs, and risks.

Simply submit existing maintenance plans (Excel or maintenance management system data) to the system to start diagnostics. No changes to existing maintenance workflows are required.

KDG systematizes the knowledge needed to optimize equipment maintenance plans, including failure modes and degradation mechanisms for each equipment type, TBM-to-CBM transition criteria, maintenance interval optimization logic, parts selection criteria, and cost optimization approaches.

Objectively and quantitatively evaluate maintenance plan validity, preventing both over-maintenance and under-maintenance.

In supply chains for food and other goods, various disruption risks occur regularly, including supplier shutdowns, port closures, quality issues, sudden demand changes, raw material price surges, and geopolitical risks.

This solution does not change existing procurement and logistics workflows. It can be used simply by opening the SCM monitoring screen when disruption events are detected through supplier notifications, news alerts, or internal reports.

KDG systematizes veteran knowledge for disruption response across six categories. When an event occurs, KDG receives a 'Situation Context' combining impact propagation results with current facts, and searches for the most relevant knowledge to respond.

Help shorten the time from event occurrence to having the information needed for decisions.

When IT infrastructure failures occur, initial triage (identifying failure points and determining escalation targets) is the operations team's most critical and time-sensitive task. However, in environments where servers, networks, storage, and batch processes are complexly interdependent, identifying the true failure point from logs and alerts requires expert knowledge.

Upon receiving logs and alerts from monitoring systems, the system automatically begins impact propagation analysis on the dependency graph. It integrates with existing monitoring infrastructure (Zabbix, Datadog, CloudWatch, etc.) through alert integration, requiring no changes to the monitoring setup.

KDG systematizes the incident response knowledge cultivated by veteran IT infrastructure engineers across six categories, including runbooks, escalation criteria, past incident cases, message code meanings, configuration standards, and batch dependencies.

Shorten the time from failure occurrence to initial triage completion, contributing to MTTR improvement.