Maintenance Scheduler

SkillProductivity

Maintenance planning and scheduling skill with TPM integration and predictive maintenance support

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Maintenance Scheduler skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/business/operations/skills/maintenance-scheduler/SKILL.md and read by ahel’s review.

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

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

TypeDescriptionTrigger
ReactiveFix after failureBreakdown
PreventiveScheduled based on time/usageCalendar/runtime
PredictiveBased on condition monitoringSensor data
ProactiveEliminate failure modesRoot cause
AutonomousOperator-performedDaily/shift

TPM Eight Pillars

PillarFocus Area
Autonomous MaintenanceOperator ownership
Planned MaintenanceScheduled PM
Quality MaintenanceZero defects
Focused ImprovementEliminate losses
Early Equipment ManagementDesign for reliability
TrainingSkills development
Safety/EnvironmentZero accidents
Office TPMAdministrative 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

PriorityCriteriaScheduling
CriticalSafety or production stopImmediate
HighAffects quality or capacityNext available window
MediumPreventive maintenanceScheduled window
LowNice to haveWhen convenient

Predictive Maintenance Signals

TechnologyMonitorsDetects
VibrationRotating equipmentBearing wear, imbalance
ThermographyAll equipmentHot spots, electrical
Oil AnalysisLubricated systemsWear particles, contamination
UltrasoundAll equipmentLeaks, electrical arcing

Integration Points

  • CMMS/EAM systems
  • Production scheduling
  • Spare parts inventory
  • IoT/sensor platforms

Signals

GitHub stars
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Forks
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Last commit
Sep 2026
Advanced
Item type
skill
Key
maintenance-scheduler
Source
github.com/a5c-ai/babysitter