smed-analyzer
SkillDev toolsSingle Minute Exchange of Die analysis skill for changeover time reduction.
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Then ask your AI: use the smed-analyzer skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/industrial-engineering/skills/smed-analyzer/SKILL.md and read by ahel’s review.
You are smed-analyzer - a specialized skill for analyzing and reducing changeover times using the Single Minute Exchange of Die (SMED) methodology.
Overview
This skill enables AI-powered SMED analysis including:
- Changeover video analysis
- Internal vs external activity separation
- Activity timing and sequencing
- Conversion opportunity identification
- Parallel work assignment
- Quick-release mechanism suggestions
- Before/after comparison reports
- Standard changeover documentation
Prerequisites
- Video recording capability
- Stopwatch or timing software
- Understanding of changeover process
Capabilities
1. Changeover Activity Recording
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional
import datetime
class ActivityType(Enum):
INTERNAL = "internal" # Machine must be stopped
EXTERNAL = "external" # Can be done while running
@dataclass
class ChangeoverActivity:
id: int
description: str
start_time: float # seconds from changeover start
end_time: float
activity_type: ActivityType
operator: str
tools_required: List[str]
notes: Optional[str] = None
@property
def duration(self):
return self.end_time - self.start_time
class ChangeoverAnalysis:
"""
Record and analyze changeover activities
"""
def __init__(self, machine_name: str, from_product: str, to_product: str):
self.machine_name = machine_name
self.from_product = from_product
self.to_product = to_product
self.activities: List[ChangeoverActivity] = []
self.timestamp = datetime.datetime.now()
def add_activity(self, description, start, end, activity_type,
operator, tools=None, notes=None):
activity = ChangeoverActivity(
id=len(self.activities) + 1,
description=description,
start_time=start,
end_time=end,
activity_type=activity_type,
operator=operator,
tools_required=tools or [],
notes=notes
)
self.activities.append(activity)
return activity
def summary(self):
internal = [a for a in self.activities if a.activity_type == ActivityType.INTERNAL]
external = [a for a in self.activities if a.activity_type == ActivityType.EXTERNAL]
return {
"total_changeover_time": max(a.end_time for a in self.activities),
"internal_time": sum(a.duration for a in internal),
"external_time": sum(a.duration for a in external),
"num_activities": len(self.activities),
"num_internal": len(internal),
"num_external": len(external)
}
2. Internal/External Separation Analysis
def analyze_internal_external(activities):
"""
Identify activities that could be converted from internal to external
"""
conversion_opportunities = []
for activity in activities:
if activity.activity_type == ActivityType.INTERNAL:
# Check for conversion potential
potential = assess_conversion_potential(activity)
if potential['can_convert']:
conversion_opportunities.append({
"activity_id": activity.id,
"description": activity.description,
"current_duration": activity.duration,
"conversion_method": potential['method'],
"estimated_savings": potential['savings'],
"investment_required": potential['investment']
})
return conversion_opportunities
def assess_conversion_potential(activity):
"""
Assess if internal activity can become external
"""
# Keywords indicating conversion potential
prep_keywords = ['get', 'find', 'look for', 'search', 'locate', 'bring']
adjustment_keywords = ['adjust', 'set', 'calibrate', 'tune']
removal_keywords = ['remove', 'take off', 'disconnect']
desc_lower = activity.description.lower()
# Preparation activities can often be done externally
if any(kw in desc_lower for kw in prep_keywords):
return {
'can_convert': True,
'method': 'Pre-stage tools and materials before stopping machine',
'savings': activity.duration * 0.9, # 90% reduction
'investment': 'Low - organization and staging area'
}
# Adjustments might be eliminated with presetting
if any(kw in desc_lower for kw in adjustment_keywords):
return {
'can_convert': True,
'method': 'Use preset tooling or jigs for instant settings',
'savings': activity.duration * 0.7,
'investment': 'Medium - preset tooling investment'
}
return {'can_convert': False}
3. Parallel Work Analysis
def analyze_parallel_opportunities(activities, available_operators):
"""
Identify activities that can be done in parallel
"""
# Group activities by time window
timeline = []
for activity in activities:
timeline.append({
'time': activity.start_time,
'type': 'start',
'activity': activity
})
timeline.append({
'time': activity.end_time,
'type': 'end',
'activity': activity
})
timeline.sort(key=lambda x: x['time'])
# Analyze operator utilization
parallel_opportunities = []
current_activities = []
for event in timeline:
if event['type'] == 'start':
current_activities.append(event['activity'])
else:
current_activities.remove(event['activity'])
# Check if operators are idle
active_operators = len(set(a.operator for a in current_activities))
idle_operators = available_operators - active_operators
if idle_operators > 0 and len(current_activities) > 0:
parallel_opportunities.append({
'time': event['time'],
'idle_operators': idle_operators,
'active_activities': [a.description for a in current_activities]
})
return parallel_opportunities
def optimize_parallel_work(activities, available_operators):
"""
Reassign activities for parallel execution
"""
# Simple greedy assignment
assignments = {i: [] for i in range(available_operators)}
operator_end_times = [0] * available_operators
# Sort by start time
sorted_activities = sorted(activities, key=lambda a: a.start_time)
for activity in sorted_activities:
# Find operator who finishes earliest
earliest_op = min(range(available_operators),
key=lambda i: operator_end_times[i])
# Assign to this operator
new_start = max(activity.start_time, operator_end_times[earliest_op])
new_end = new_start + activity.duration
assignments[earliest_op].append({
'activity': activity.description,
'original_start': activity.start_time,
'new_start': new_start,
'end': new_end
})
operator_end_times[earliest_op] = new_end
new_total_time = max(operator_end_times)
original_total_time = max(a.end_time for a in activities)
return {
'assignments': assignments,
'original_time': original_total_time,
'optimized_time': new_total_time,
'time_savings': original_total_time - new_total_time,
'reduction_percent': (1 - new_total_time/original_total_time) * 100
}
4. Quick-Release Mechanism Suggestions
def suggest_quick_release_mechanisms(activities):
"""
Suggest engineering improvements for faster changeovers
"""
suggestions = []
for activity in activities:
desc_lower = activity.description.lower()
# Fastener improvements
if any(word in desc_lower for word in ['bolt', 'screw', 'nut', 'fasten']):
suggestions.append({
'activity': activity.description,
'current_method': 'Threaded fasteners',
'improvement': 'Quick-release clamps, cam locks, or quarter-turn fasteners',
'typical_reduction': '70-90%',
'investment_level': 'Medium'
})
# Tool changes
if 'tool' in desc_lower and 'change' in desc_lower:
suggestions.append({
'activity': activity.description,
'current_method': 'Manual tool change',
'improvement': 'Quick-change tool holders with preset tooling',
'typical_reduction': '80-95%',
'investment_level': 'Medium-High'
})
# Positioning/alignment
if any(word in desc_lower for word in ['align', 'position', 'center']):
suggestions.append({
'activity': activity.description,
'current_method': 'Manual alignment',
'improvement': 'Locating pins, guides, or self-centering fixtures',
'typical_reduction': '60-80%',
'investment_level': 'Low-Medium'
})
# Settings/adjustments
if any(word in desc_lower for word in ['adjust', 'set', 'calibrate']):
suggestions.append({
'activity': activity.description,
'current_method': 'Trial and error adjustment',
'improvement': 'Digital presets, scales, or stops',
'typical_reduction': '50-70%',
'investment_level': 'Medium'
})
return suggestions
5. Before/After Comparison
def generate_comparison_report(before_analysis, after_analysis):
"""
Generate before/after SMED comparison report
"""
before_summary = before_analysis.summary()
after_summary = after_analysis.summary()
return {
'changeover': {
'machine': before_analysis.machine_name,
'product_change': f"{before_analysis.from_product} -> {before_analysis.to_product}"
},
'time_comparison': {
'before': {
'total_minutes': before_summary['total_changeover_time'] / 60,
'internal_minutes': before_summary['internal_time'] / 60,
'external_minutes': before_summary['external_time'] / 60
},
'after': {
'total_minutes': after_summary['total_changeover_time'] / 60,
'internal_minutes': after_summary['internal_time'] / 60,
'external_minutes': after_summary['external_time'] / 60
}
},
'improvement': {
'time_reduction_minutes': (before_summary['total_changeover_time'] -
after_summary['total_changeover_time']) / 60,
'percent_reduction': (1 - after_summary['total_changeover_time'] /
before_summary['total_changeover_time']) * 100,
'internal_reduction_percent': (1 - after_summary['internal_time'] /
before_summary['internal_time']) * 100
},
'activities_comparison': {
'before_count': before_summary['num_activities'],
'after_count': after_summary['num_activities'],
'eliminated': before_summary['num_activities'] - after_summary['num_activities']
}
}
6. Standard Changeover Documentation
def generate_standard_changeover(optimized_analysis):
"""
Create standard work document for changeover
"""
document = {
'title': f"Standard Changeover: {optimized_analysis.machine_name}",
'revision': '1.0',
'date': datetime.datetime.now().isoformat(),
'target_time_minutes': optimized_analysis.summary()['total_changeover_time'] / 60,
'preparation_phase': {
'description': 'Activities to complete BEFORE stopping machine',
'activities': []
},
'changeover_phase': {
'description': 'Activities performed while machine is stopped',
'activities': []
},
'startup_phase': {
'description': 'Activities to complete after starting machine',
'activities': []
}
}
for activity in optimized_analysis.activities:
entry = {
'step': activity.id,
'description': activity.description,
'time_seconds': activity.duration,
'operator': activity.operator,
'tools': activity.tools_required,
'notes': activity.notes
}
if activity.activity_type == ActivityType.EXTERNAL:
if activity.start_time < 0: # Prep phase
document['preparation_phase']['activities'].append(entry)
else:
document['startup_phase']['activities'].append(entry)
else:
document['changeover_phase']['activities'].append(entry)
return document
Process Integration
This skill integrates with the following processes:
setup-time-reduction-smed.jskaizen-event-facilitation.jsoee-improvement.js
Output Format
{
"current_state": {
"total_changeover_minutes": 45,
"internal_minutes": 38,
"external_minutes": 7
},
"opportunities": {
"convert_to_external": 5,
"parallel_execution": 3,
"quick_release": 4,
"eliminate": 2
},
"projected_future_state": {
"total_changeover_minutes": 12,
"reduction_percent": 73
},
"implementation_plan": {
"phase_1": "Convert preparation to external",
"phase_2": "Implement parallel work",
"phase_3": "Install quick-release mechanisms"
}
}
Best Practices
- Video record changeovers - Capture actual process
- Involve operators - They know the details
- Separate internal/external first - Quick wins
- Standardize before optimizing - Consistent baseline
- Measure before and after - Validate improvements
- Document standard work - Sustain the gains
Constraints
- Safety cannot be compromised for speed
- Validate quality after changeover
- Consider operator ergonomics
- Document all standard procedures
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
smed-analyzer- Source
- github.com/a5c-ai/babysitter
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