基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/MikeTreml/MissionControl --skill smed-analyzer命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
Expert Electron application architecture skill for IPC design, main/renderer/preload boundaries, security hardening, performance optimization, packaging strategy, native integration, and cross-platform desktop development. Use when reviewing or designing Electron apps, planning migrations, auditing architecture risks, choosing IPC patterns, diagnosing startup or memory issues, or coordinating related Electron skills.
Generates DrawIO XML diagrams for Amazon Web Services architectures from text descriptions or images. Analyzes existing .drawio files to extract AWS components. Use for AWS architecture diagrams, cloud infrastructure documentation, or when converting AWS diagram images to editable DrawIO format.
Generates DrawIO XML diagrams for Google Cloud Platform architectures from text descriptions or images. Analyzes existing .drawio files to extract GCP components. Use for GCP architecture diagrams, cloud infrastructure documentation, or when converting GCP diagram images to editable DrawIO format.
| name | smed-analyzer |
| description | Single Minute Exchange of Die analysis skill for changeover time reduction. |
| allowed-tools | Bash(*) Read Write Edit Glob Grep WebFetch |
| metadata | {"author":"babysitter-sdk","version":"1.0.0","category":"lean-manufacturing","backlog-id":"SK-IE-011"} |
You are smed-analyzer - a specialized skill for analyzing and reducing changeover times using the Single Minute Exchange of Die (SMED) methodology.
This skill enables AI-powered SMED analysis including:
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)
}
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
(kw desc_lower kw prep_keywords):
{
: ,
: ,
: activity.duration * ,
:
}
(kw desc_lower kw adjustment_keywords):
{
: ,
: ,
: activity.duration * ,
:
}
{: }
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 a current_activities]
})
parallel_opportunities
():
assignments = {i: [] i (available_operators)}
operator_end_times = [] * available_operators
sorted_activities = (activities, key= a: a.start_time)
activity sorted_activities:
earliest_op = ((available_operators),
key= i: operator_end_times[i])
new_start = (activity.start_time, operator_end_times[earliest_op])
new_end = new_start + activity.duration
assignments[earliest_op].append({
: activity.description,
: activity.start_time,
: new_start,
: new_end
})
operator_end_times[earliest_op] = new_end
new_total_time = (operator_end_times)
original_total_time = (a.end_time a activities)
{
: assignments,
: original_total_time,
: new_total_time,
: original_total_time - new_total_time,
: ( - new_total_time/original_total_time) *
}
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 (word desc_lower word [, , ]):
suggestions.append({
: activity.description,
: ,
: ,
: ,
:
})
(word desc_lower word [, , ]):
suggestions.append({
: activity.description,
: ,
: ,
: ,
:
})
suggestions
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[]) * ,
: ( - after_summary[] /
before_summary[]) *
},
: {
: before_summary[],
: after_summary[],
: before_summary[] - after_summary[]
}
}
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'][].append(entry)
:
document[][].append(entry)
:
document[][].append(entry)
document
This skill integrates with the following processes:
setup-time-reduction-smed.jskaizen-event-facilitation.jsoee-improvement.js{
"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"