Cantier CMMS X.0

Cantier CMMS X.0 provides end-to-end maintenance and asset reliability management for discrete, semiconductor, electronics, automotive, aerospace, precision engineering, and other asset-intensive manufacturing environments.

The platform manages equipment and asset records, corrective and preventive maintenance, work orders, maintenance schedules, spare parts, calibration, equipment history, downtime, utilization, and maintenance performance while creating a trusted real-time foundation for asset reliability.

CMMS X.0 connects maintenance execution and equipment intelligence across three layers: CMMS for maintenance execution, AIoT for equipment intelligence, and Cantier.ai for agentic operations.

Maintenance records, equipment history, and real-time machine data provide context for reliability and maintenance insights, while copilots and specialized agents help maintenance teams investigate equipment issues, prioritize work, and act on findings.

Industrial IoT, a Unified Namespace, a Knowledge Graph, and a Manufacturing Ontology connect equipment and operational data with maintenance context. An MCP server provides a permissioned interface for Cantier agents and approved enterprise agents.

CMMS X.0 is designed around a unified asset reliability architecture spanning maintenance execution, equipment connectivity, Industrial AIoT, Digital Twins, predictive intelligence, and Agentic AI - reducing integration complexity and helping manufacturers move from reactive maintenance toward condition-based and predictive maintenance.

1. Corrective Maintenance: Manage equipment failures, breakdowns, maintenance requests, and corrective work through controlled maintenance workflows.

2. Preventive Maintenance: Define and schedule recurring maintenance activities based on time, usage, and maintenance policies to reduce unplanned downtime.

3. Maintenance Work Order Management: Create, assign, prioritize, execute, and track maintenance work orders with task lists, technician activities, and equipment history.

4. Asset & Equipment Management: Maintain centralized equipment and asset records, including hierarchy, status, parameters, maintenance history, and operational context.

5. Maintenance Planning & Scheduling: Plan maintenance activities, resources, and schedules while coordinating maintenance requirements with equipment availability.

6. Equipment Activity & Maintenance History: Maintain traceable records of equipment events, maintenance activities, failures, repairs, and service history.

7. Downtime & Failure Management: Capture downtime, failure events, problem codes, error codes, and maintenance causes to support reliability analysis.

8. Maintenance KPIs & Reliability Analytics: Monitor maintenance and equipment performance using KPIs such as MTBF, MTTR, equipment availability, utilization, downtime, and maintenance performance.

9. Condition Monitoring: Use connected equipment and sensor data to monitor asset condition and identify abnormal operating behavior.

10. Predictive Maintenance: Combine historical maintenance information, equipment condition, and machine data with predictive models to identify potential failures and maintenance requirements earlier.

11. AI Copilots & Specialized Maintenance Agents: Support maintenance teams with AI assistance for equipment investigation, work-order analysis, failure analysis, maintenance planning, and reliability insights.

12. Maintenance Knowledge & Root Cause Context: Connect historical failures, maintenance actions, equipment conditions, and operational information to support faster troubleshooting and root-cause investigation.

CMMS X.0 combines historical maintenance records with equipment and IIoT data to help identify patterns associated with equipment degradation and potential failures.

Condition monitoring and predictive models can support earlier identification of abnormal equipment behavior, enabling maintenance teams to investigate risks, prioritize maintenance activities, and reduce unexpected equipment downtime.

Equipment Digital Twins provide additional operational context by connecting current equipment conditions with maintenance history, performance, and asset information.