---
name: production-scheduler-73728cf84ad7
description: Production scheduling optimization skill with constraint handling, changeover minimization, and due date management
allowed-tools:
  - Read
  - Write
  - Glob
  - Grep
  - Edit
metadata:
  specialization: operations
  domain: business
  category: capacity-planning
graph:
  domains: [domain:operations]
  skillAreas: [skill-area:capacity-planning-ops, skill-area:quantitative-modeling, skill-area:data-analytics]
  workflows: [workflow:vendor-onboarding, workflow:vendor-evaluation]
  roles: [role:operations-analyst, role:procurement-manager, role:business-analyst]
---

# Production Scheduler

## Overview

The Production Scheduler skill provides comprehensive capabilities for optimizing production schedules. It supports finite capacity scheduling, changeover optimization, due date prioritization, and real-time rescheduling to maximize throughput and on-time delivery.

## Capabilities

- Finite capacity scheduling
- Changeover sequence optimization
- Due date prioritization
- Machine assignment optimization
- Setup time reduction
- Order splitting strategies
- Schedule compression techniques
- Real-time rescheduling

## Used By Processes

- CAP-002: Production Scheduling Optimization
- TOC-002: Drum-Buffer-Rope Scheduling
- LEAN-004: Kanban System Design

## Tools and Libraries

- Scheduling algorithms
- Optimization solvers (Gurobi, CPLEX, OR-Tools)
- ERP scheduling modules
- APS systems

## Usage

```yaml
skill: production-scheduler
inputs:
  orders:
    - order_id: "ORD001"
      product: "Widget A"
      quantity: 500
      due_date: "2026-02-10"
      priority: "high"
    - order_id: "ORD002"
      product: "Widget B"
      quantity: 300
      due_date: "2026-02-12"
      priority: "normal"
  resources:
    - machine: "Press 1"
      available_hours: 16
      products: ["Widget A", "Widget B", "Widget C"]
    - machine: "Press 2"
      available_hours: 16
      products: ["Widget A", "Widget C"]
  changeover_matrix:
    "Widget A -> Widget B": 30  # minutes
    "Widget A -> Widget C": 45
    "Widget B -> Widget A": 25
  scheduling_rules:
    - "minimize_lateness"
    - "minimize_changeovers"
outputs:
  - production_schedule
  - machine_assignments
  - changeover_sequence
  - on_time_performance
  - utilization_metrics
```

## Scheduling Objectives

| Objective | Description | Metric |
|-----------|-------------|--------|
| On-time delivery | Meet customer due dates | % on-time |
| Throughput | Maximize output | Units/day |
| Utilization | Efficient resource use | % utilized |
| Changeover | Minimize setup time | Total setup hours |
| WIP | Minimize work in process | $ WIP value |

## Scheduling Rules

### Priority Rules
- **EDD** (Earliest Due Date) - Schedule by due date
- **SPT** (Shortest Processing Time) - Shortest jobs first
- **FCFS** (First Come First Served) - Order received
- **CR** (Critical Ratio) - Time remaining / work remaining

### Sequencing Rules
- **Grouping** - Similar products together
- **Optimal changeover** - Minimize total setup time
- **Color wheel** - Light to dark, small to large

## Schedule Optimization

```
Minimize: Total Lateness + (Changeover Time x Weight)

Subject to:
- Capacity constraints
- Due date requirements
- Material availability
- Resource skills
```

## Real-Time Rescheduling Triggers

1. Machine breakdown
2. Rush order arrival
3. Material shortage
4. Quality issue
5. Labor absence

## Integration Points

- ERP/MRP systems
- Manufacturing Execution Systems
- Order management systems
- Shop floor data collection


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Operations, Product Management, Project & Program Management
Roles: Business Process Analyst, Operations Manager, Product Manager, Project Manager, Supply Chain Manager
Specialties: Backend
Tools: Cplex, Gurobi, Or Tools
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: f8e3a16d18d0cb40fd1936076f43277924960c28b8c9355fb40b04fc8fd0c1ce