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cwicr-material-substitution

@datadrivenconstruction · 收录于 1 周前

Find substitute materials using CWICR data. Identify equivalent alternatives based on function, cost, and availability.

适合你,如果需要在产品设计中快速找到功能等效且成本更优的替代材料。

/ 下载安装
cwicr-material-substitution.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-material-substitution
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-material-substitution
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/cwicr-material-substitution
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

技能原文 SKILL.md作者撰写 · MIT · 34e0d78

CWICR Material Substitution

Business Case
Problem Statement

Material substitution challenges:

  • Supply chain issues
  • Cost optimization
  • Specification compliance
  • Equivalent performance
Solution

Systematic material substitution using CWICR data to find functionally equivalent alternatives with cost and performance analysis.

Business Value
  • Supply flexibility - Alternative sources
  • Cost savings - Lower-cost equivalents
  • Compliance - Specification matching
  • Quick decisions - Rapid alternative search
Technical Implementation
import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass
from enum import Enum
from difflib import SequenceMatcher


class SubstitutionType(Enum):
    """Types of substitution."""
    DIRECT = "direct"        # Drop-in replacement
    EQUIVALENT = "equivalent"  # Same function, different material
    UPGRADE = "upgrade"      # Better performance
    DOWNGRADE = "downgrade"  # Lower performance (cost saving)


class CompatibilityLevel(Enum):
    """Compatibility levels."""
    EXACT = "exact"          # Identical specs
    HIGH = "high"            # Minor differences
    MEDIUM = "medium"        # Requires review
    LOW = "low"              # Significant differences


@dataclass
class MaterialSubstitute:
    """Material substitution option."""
    original_code: str
    original_description: str
    substitute_code: str
    substitute_description: str
    substitution_type: SubstitutionType
    compatibility: CompatibilityLevel
    original_cost: float
    substitute_cost: float
    cost_difference: float
    cost_difference_pct: float
    notes: str


# Material compatibility groups
MATERIAL_GROUPS = {
    'concrete': ['cement', 'beton', 'concrete', 'C20', 'C25', 'C30', 'C35', 'C40'],
    'steel': ['steel', 'rebar', 'reinforcement', 'S235', 'S275', 'S355'],
    'lumber': ['wood', 'timber', 'lumber', 'plywood', 'OSB'],
    'masonry': ['brick', 'block', 'CMU', 'masonry'],
    'insulation': ['insulation', 'rockwool', 'glasswool', 'EPS', 'XPS', 'PIR'],
    'pipe': ['pipe', 'PVC', 'HDPE', 'copper', 'steel pipe'],
    'electrical': ['wire', 'cable', 'conduit'],
    'finishing': ['paint', 'plaster', 'drywall', 'gypsum'],
    'flooring': ['tile', 'vinyl', 'laminate', 'carpet', 'hardwood'],
    'roofing': ['shingle', 'membrane', 'metal roof', 'tile roof']
}


class CWICRMaterialSubstitution:
    """Find material substitutions using CWICR data."""

    def __init__(self, cwicr_data: pd.DataFrame):
        self.materials = cwicr_data
        self._index_data()

    def _index_data(self):
        """Index material data."""
        if 'work_item_code' in self.materials.columns:
            self._code_index = self.materials.set_index('work_item_code')
        elif 'material_code' in self.materials.columns:
            self._code_index = self.materials.set_index('material_code')
        else:
            self._code_index = None

    def _similarity(self, a: str, b: str) -> float:
        """Calculate string similarity."""
        return SequenceMatcher(None, a.lower(), b.lower()).ratio()

    def _get_material_group(self, description: str) -> Optional[str]:
        """Identify material group from description."""
        desc_lower = description.lower()

        for group, keywords in MATERIAL_GROUPS.items():
            if any(kw.lower() in desc_lower for kw in keywords):
                return group

        return None

    def _get_cost(self, code: str) -> Tuple[float, str]:
        """Get material cost."""
        if self._code_index is None or code not in self._code_index.index:
            return (0, 'unit')

        item = self._code_index.loc[code]
        cost = float(item.get('material_cost', item.get('total_cost', 0)) or 0)
        unit = str(item.get('unit', 'unit'))

        return (cost, unit)

    def find_substitutes(self,
                          material_code: str,
                          max_results: int = 10,
                          max_cost_increase: float = 0.20,
                          include_upgrades: bool = True) -> List[MaterialSubstitute]:
        """Find substitute materials."""

        if self._code_index is None or material_code not in self._code_index.index:
            return []

        original = self._code_index.loc[material_code]
        original_desc = str(original.get('description', material_code))
        original_cost, original_unit = self._get_cost(material_code)

        group = self._get_material_group(original_desc)

        substitutes = []

        for code, row in self._code_index.iterrows():
            if code == material_code:
                continue

            sub_desc = str(row.get('description', code))
            sub_group = self._get_material_group(sub_desc)

            # Check if same group or similar description
            if group and sub_group == group:
                similarity = 0.7
            else:
                similarity = self._similarity(original_desc, sub_desc)

            if similarity < 0.3:
                continue

            sub_cost, sub_unit = self._get_cost(code)

            if sub_unit != original_unit:
                continue

            cost_diff = sub_cost - original_cost
            cost_diff_pct = (cost_diff / original_cost * 100) if original_cost > 0 else 0

            # Filter by cost increase limit
            if not include_upgrades and cost_diff_pct > max_cost_increase * 100:
                continue

            # Determine substitution type
            if cost_diff_pct < -10:
                sub_type = SubstitutionType.DOWNGRADE
            elif cost_diff_pct > 10:
                sub_type = SubstitutionType.UPGRADE
            elif similarity > 0.8:
                sub_type = SubstitutionType.DIRECT
            else:
                sub_type = SubstitutionType.EQUIVALENT

            # Determine compatibility
            if similarity > 0.9:
                compat = CompatibilityLevel.EXACT
            elif similarity > 0.7:
                compat = CompatibilityLevel.HIGH
            elif similarity > 0.5:
                compat = CompatibilityLevel.MEDIUM
            else:
                compat = CompatibilityLevel.LOW

            substitutes.append(MaterialSubstitute(
                original_code=material_code,
                original_description=original_desc,
                substitute_code=code,
                substitute_description=sub_desc,
                substitution_type=sub_type,
                compatibility=compat,
                original_cost=round(original_cost, 2),
                substitute_cost=round(sub_cost, 2),
                cost_difference=round(cost_diff, 2),
                cost_difference_pct=round(cost_diff_pct, 1),
                notes=f"Similarity: {similarity:.0%}"
            ))

        # Sort by compatibility then cost
        substitutes.sort(key=lambda x: (
            list(CompatibilityLevel).index(x.compatibility),
            x.cost_difference
        ))

        return substitutes[:max_results]

    def find_cost_saving_alternatives(self,
                                       material_code: str,
                                       min_savings_pct: float = 5.0) -> List[MaterialSubstitute]:
        """Find lower-cost alternatives."""

        subs = self.find_substitutes(material_code, max_results=20)

        cost_saving = [
            s for s in subs
            if s.cost_difference_pct <= -min_savings_pct
        ]

        return sorted(cost_saving, key=lambda x: x.cost_difference)

    def find_by_group(self,
                       group_name: str,
                       max_results: int = 20) -> List[Dict[str, Any]]:
        """Find all materials in a group."""

        if self._code_index is None:
            return []

        results = []

        for code, row in self._code_index.iterrows():
            desc = str(row.get('description', code))
            item_group = self._get_material_group(desc)

            if item_group == group_name.lower():
                cost, unit = self._get_cost(code)
                results.append({
                    'code': code,
                    'description': desc,
                    'cost': cost,
                    'unit': unit,
                    'group': item_group
                })

        return sorted(results, key=lambda x: x['cost'])[:max_results]

    def substitution_impact(self,
                            original_code: str,
                            substitute_code: str,
                            quantity: float) -> Dict[str, Any]:
        """Calculate impact of substitution."""

        original_cost, _ = self._get_cost(original_code)
        substitute_cost, _ = self._get_cost(substitute_code)

        original_total = original_cost * quantity
        substitute_total = substitute_cost * quantity
        impact = substitute_total - original_total

        return {
            'original_code': original_code,
            'substitute_code': substitute_code,
            'quantity': quantity,
            'original_unit_cost': original_cost,
            'substitute_unit_cost': substitute_cost,
            'original_total': round(original_total, 2),
            'substitute_total': round(substitute_total, 2),
            'cost_impact': round(impact, 2),
            'impact_percent': round(impact / original_total * 100, 1) if original_total > 0 else 0
        }

    def batch_substitution(self,
                            materials: List[Dict[str, Any]]) -> Dict[str, Any]:
        """Find substitutions for multiple materials."""

        results = []
        total_original = 0
        total_potential_savings = 0

        for mat in materials:
            code = mat.get('material_code', mat.get('code'))
            qty = mat.get('quantity', 1)

            subs = self.find_cost_saving_alternatives(code)

            original_cost, _ = self._get_cost(code)
            original_total = original_cost * qty
            total_original += original_total

            best_sub = subs[0] if subs else None
            potential_savings = 0

            if best_sub:
                impact = self.substitution_impact(code, best_sub.substitute_code, qty)
                potential_savings = abs(impact['cost_impact']) if impact['cost_impact'] < 0 else 0
                total_potential_savings += potential_savings

            results.append({
                'code': code,
                'quantity': qty,
                'original_total': round(original_total, 2),
                'best_substitute': best_sub.substitute_code if best_sub else None,
                'potential_savings': round(potential_savings, 2),
                'alternatives_count': len(subs)
            })

        return {
            'materials': results,
            'total_original_cost': round(total_original, 2),
            'total_potential_savings': round(total_potential_savings, 2),
            'savings_percent': round(total_potential_savings / total_original * 100, 1) if total_original > 0 else 0
        }

    def export_substitution_report(self,
                                    substitutes: List[MaterialSubstitute],
                                    output_path: str) -> str:
        """Export substitution report to Excel."""

        with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
            df = pd.DataFrame([
                {
                    'Original Code': s.original_code,
                    'Original Description': s.original_description,
                    'Substitute Code': s.substitute_code,
                    'Substitute Description': s.substitute_description,
                    'Type': s.substitution_type.value,
                    'Compatibility': s.compatibility.value,
                    'Original Cost': s.original_cost,
                    'Substitute Cost': s.substitute_cost,
                    'Cost Difference': s.cost_difference,
                    'Difference %': s.cost_difference_pct,
                    'Notes': s.notes
                }
                for s in substitutes
            ])
            df.to_excel(writer, sheet_name='Substitutes', index=False)

        return output_path
Quick Start
# Load CWICR data
cwicr = pd.read_parquet("ddc_cwicr_en.parquet")

# Initialize substitution finder
sub_finder = CWICRMaterialSubstitution(cwicr)

# Find substitutes
substitutes = sub_finder.find_substitutes("CONC-C30-001")

for sub in substitutes[:5]:
    print(f"{sub.substitute_code}: ${sub.cost_difference:+.2f} ({sub.cost_difference_pct:+.1f}%)")
Common Use Cases
1. Cost Saving Alternatives
savings = sub_finder.find_cost_saving_alternatives("STEEL-S355", min_savings_pct=10)
for s in savings:
    print(f"{s.substitute_code}: Save ${abs(s.cost_difference):.2f}/unit")
2. Batch Analysis
materials = [
    {'code': 'CONC-001', 'quantity': 200},
    {'code': 'STEEL-002', 'quantity': 5000},
    {'code': 'BRICK-003', 'quantity': 10000}
]

batch = sub_finder.batch_substitution(materials)
print(f"Potential Savings: ${batch['total_potential_savings']:,.2f}")
3. Material Group Search
concrete_options = sub_finder.find_by_group('concrete')
for opt in concrete_options[:5]:
    print(f"{opt['code']}: ${opt['cost']:.2f}/{opt['unit']}")
Resources
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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