Agent skill

smed-analyzer

Single Minute Exchange of Die analysis skill for changeover time reduction.

Stars 514
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/industrial-engineering/skills/smed-analyzer

Metadata

Additional technical details for this skill

author
babysitter-sdk
version
1.0.0
category
lean-manufacturing
backlog id
SK-IE-011

SKILL.md

smed-analyzer

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

python
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

python
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

python
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

python
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

python
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

python
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.js
  • kaizen-event-facilitation.js
  • oee-improvement.js

Output Format

json
{
  "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

  1. Video record changeovers - Capture actual process
  2. Involve operators - They know the details
  3. Separate internal/external first - Quick wins
  4. Standardize before optimizing - Consistent baseline
  5. Measure before and after - Validate improvements
  6. Document standard work - Sustain the gains

Constraints

  • Safety cannot be compromised for speed
  • Validate quality after changeover
  • Consider operator ergonomics
  • Document all standard procedures

Expand your agent's capabilities with these related and highly-rated skills.

a5c-ai/babysitter

gsd-tools

Central utility skill for GSD operations. Provides config parsing, slug generation, timestamps, path operations, and orchestrates calls to other specialized skills. Acts as the unified entry point that the original gsd-tools.cjs provided via its lib/ modules (commands, config, core, init).

514 31
Explore
a5c-ai/babysitter

model-profile-resolution

Resolve model profile (quality/balanced/budget) at orchestration start and map agents to specific models. Enables cost/quality tradeoffs by selecting appropriate AI models for each agent role.

514 31
Explore
a5c-ai/babysitter

verification-suite

Plan structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.

514 31
Explore
a5c-ai/babysitter

state-management

STATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.

514 31
Explore
a5c-ai/babysitter

git-integration

Git commit patterns, formats, and conventions for GSD methodology. Provides atomic commits per task, structured commit messages, planning file commits, branch management, and milestone tag operations.

514 31
Explore
a5c-ai/babysitter

frontmatter-parsing

YAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.

514 31
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results