Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install a5c-ai-babysitter-library-specializations-domains-business-operations-skills-maintgit clone https://github.com/a5c-ai/babysitter.gitcp babysitter/SKILL.MD ~/.claude/skills/a5c-ai-babysitter-library-specializations-domains-business-operations-skills-maint/SKILL.md---
name: maintenance-scheduler
description: Maintenance planning and scheduling skill with TPM integration and predictive maintenance support
allowed-tools:
- Read
- Write
- Glob
- Grep
- Edit
metadata:
specialization: operations
domain: business
category: workflow-automation
---
# Maintenance Scheduler
## Overview
The Maintenance Scheduler skill provides comprehensive capabilities for planning and scheduling maintenance activities. It supports preventive maintenance scheduling, autonomous maintenance checklists, predictive maintenance integration, and TPM pillar support.
## Capabilities
- Preventive maintenance scheduling
- Autonomous maintenance checklists
- Predictive maintenance integration
- Spare parts planning
- Work order management
- MTBF/MTTR tracking
- Maintenance backlog management
- TPM pillar support
## Used By Processes
- LEAN-005: Standard Work Documentation
- CAP-002: Production Scheduling Optimization
- QMS-001: ISO 9001 Implementation
## Tools and Libraries
- CMMS systems (Maximo, SAP PM, Fiix)
- IoT sensors
- Predictive analytics platforms
- Mobile maintenance apps
## Usage
```yaml
skill: maintenance-scheduler
inputs:
equipment_list:
- equipment_id: "CNC-001"
name: "CNC Machine 1"
criticality: "high"
current_runtime: 4500 # hours
last_pm: "2025-12-15"
- equipment_id: "CONV-002"
name: "Conveyor System 2"
criticality: "medium"
current_runtime: 8000
last_pm: "2025-11-30"
maintenance_tasks:
- task_id: "PM-001"
description: "Lubrication"
frequency: "weekly"
duration: 30 # minutes
skills: ["mechanic"]
- task_id: "PM-002"
description: "Filter replacement"
frequency: "monthly"
duration: 60
skills: ["mechanic"]
production_schedule:
- date: "2026-01-25"
available_window: 2 # hours
technicians:
- name: "Tech A"
skills: ["mechanic", "electrical"]
availability: "day_shift"
outputs:
- maintenance_schedule
- work_orders
- parts_requirements
- resource_allocation
- backlog_report
- reliability_metrics
```
## Maintenance Types
| Type | Description | Trigger |
|------|-------------|---------|
| Reactive | Fix after failure | Breakdown |
| Preventive | Scheduled based on time/usage | Calendar/runtime |
| Predictive | Based on condition monitoring | Sensor data |
| Proactive | Eliminate failure modes | Root cause |
| Autonomous | Operator-performed | Daily/shift |
## TPM Eight Pillars
| Pillar | Focus Area |
|--------|------------|
| Autonomous Maintenance | Operator ownership |
| Planned Maintenance | Scheduled PM |
| Quality Maintenance | Zero defects |
| Focused Improvement | Eliminate losses |
| Early Equipment Management | Design for reliability |
| Training | Skills development |
| Safety/Environment | Zero accidents |
| Office TPM | Administrative efficiency |
## Reliability Metrics
### MTBF (Mean Time Between Failures)
```
MTBF = Total Operating Time / Number of Failures
Example: 1000 hours / 5 failures = 200 hours
```
### MTTR (Mean Time To Repair)
```
MTTR = Total Repair Time / Number of Repairs
Example: 25 hours / 5 repairs = 5 hours
```
### Availability
```
Availability = MTBF / (MTBF + MTTR)
Example: 200 / (200 + 5) = 97.6%
```
## Maintenance Scheduling Rules
| Priority | Criteria | Scheduling |
|----------|----------|------------|
| Critical | Safety or production stop | Immediate |
| High | Affects quality or capacity | Next available window |
| Medium | Preventive maintenance | Scheduled window |
| Low | Nice to have | When convenient |
## Predictive Maintenance Signals
| Technology | Monitors | Detects |
|------------|----------|---------|
| Vibration | Rotating equipment | Bearing wear, imbalance |
| Thermography | All equipment | Hot spots, electrical |
| Oil Analysis | Lubricated systems | Wear particles, contamination |
| Ultrasound | All equipment | Leaks, electrical arcing |
## Integration Points
- CMMS/EAM systems
- Production scheduling
- Spare parts inventory
- IoT/sensor platforms