feat(mfg-data-agent): 添加HTML可视化仪表盘和优化项目配置
- 新增6个HTML可视化仪表盘组件用于数据展示 * 人效产值损耗三维模型仪表盘 * 指标趋势分析与拐点预警仪表盘 * 一页式决策简报仪表盘 * 订单延迟预警分析仪表盘 * 供应链风险预警仪表盘 * 工单执行进度与异常节点仪表盘 - 添加VSCode工作区配置文件 - 更新businessQueries.json业务查询配置 - 优化api_client.py API客户端实现 - 更新pyproject.toml项目依赖版本 - 重组SQL查询文件结构 - 删除v2版本冗余文档配置 - 添加v2版本技能清单文档 - 更新日志文件记录
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lzwcai_mcpskills_mfg_data_agent/sql/供应链风险预警.sql
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416
lzwcai_mcpskills_mfg_data_agent/sql/供应链风险预警.sql
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-- =====================================================
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-- 供应链风险预警SQL
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-- Supply Chain Risk Warning
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-- 数据库: PostgreSQL
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-- =====================================================
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-- =====================================================
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-- 1. 供应商历史交期表现分析
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-- =====================================================
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WITH supplier_delivery AS (
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SELECT
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po.supplier_id,
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COUNT(*) AS order_count,
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COUNT(pr.purchase_receipt_id) AS receipt_count,
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AVG(
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CASE WHEN pr.doc_date_utc IS NOT NULL AND po.doc_date_utc IS NOT NULL
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THEN EXTRACT(DAY FROM pr.doc_date_utc::timestamp - po.doc_date_utc::timestamp)
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ELSE NULL END
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) AS avg_delivery_days,
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MAX(
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CASE WHEN pr.doc_date_utc IS NOT NULL AND po.doc_date_utc IS NOT NULL
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THEN EXTRACT(DAY FROM pr.doc_date_utc::timestamp - po.doc_date_utc::timestamp)
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ELSE NULL END
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) AS max_delivery_days,
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STDDEV(
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CASE WHEN pr.doc_date_utc IS NOT NULL AND po.doc_date_utc IS NOT NULL
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THEN EXTRACT(DAY FROM pr.doc_date_utc::timestamp - po.doc_date_utc::timestamp)
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ELSE NULL END
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) AS stddev_delivery_days
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FROM fact_purchase_order po
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LEFT JOIN fact_purchase_receipt pr ON po.supplier_id = pr.supplier_id
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GROUP BY po.supplier_id
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),
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supplier_quality AS (
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SELECT
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pr.supplier_id,
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COUNT(pr.purchase_receipt_id) AS total_receipts,
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SUM(pr.receipt_qty_total) AS total_qty,
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SUM(pr.amount) AS total_amount
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FROM fact_purchase_receipt pr
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GROUP BY pr.supplier_id
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),
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supplier_returns AS (
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SELECT
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pret.supplier_id,
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COUNT(*) AS return_count,
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SUM(CASE WHEN pret.return_reason = '损坏' THEN 1 ELSE 0 END) AS damage_count
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FROM fact_purchase_return pret
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GROUP BY pret.supplier_id
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),
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supplier_quality_rate AS (
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SELECT
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sq.supplier_id,
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sq.total_receipts,
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sq.total_qty,
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sq.total_amount,
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COALESCE(sr.return_count, 0) AS return_count,
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COALESCE(sr.damage_count, 0) AS damage_count,
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CASE WHEN sq.total_receipts > 0
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THEN (sq.total_receipts - COALESCE(sr.return_count, 0)) * 100.0 / sq.total_receipts
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ELSE 100 END AS quality_rate
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FROM supplier_quality sq
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LEFT JOIN supplier_returns sr ON sq.supplier_id = sr.supplier_id
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),
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supplier_risk AS (
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SELECT
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s.supplier_id,
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s.supplier_name,
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s.supplier_category,
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COALESCE(sd.order_count, 0) AS order_count,
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COALESCE(sd.receipt_count, 0) AS receipt_count,
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ROUND(COALESCE(sd.avg_delivery_days, 0), 1) AS avg_delivery_days,
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ROUND(COALESCE(sd.max_delivery_days, 0), 1) AS max_delivery_days,
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ROUND(COALESCE(sd.stddev_delivery_days, 0), 1) AS delivery_volatility,
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COALESCE(sqr.total_receipts, 0) AS total_receipts,
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COALESCE(sqr.return_count, 0) AS return_count,
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ROUND(COALESCE(sqr.quality_rate, 100), 1) AS quality_rate,
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CASE
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WHEN COALESCE(sd.avg_delivery_days, 0) > 60 THEN 40
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WHEN COALESCE(sd.avg_delivery_days, 0) > 45 THEN 30
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WHEN COALESCE(sd.avg_delivery_days, 0) > 30 THEN 20
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ELSE 10
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END +
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CASE
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WHEN COALESCE(sd.stddev_delivery_days, 0) > 20 THEN 30
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WHEN COALESCE(sd.stddev_delivery_days, 0) > 10 THEN 20
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ELSE 10
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END AS delivery_risk_score,
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CASE
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WHEN COALESCE(sqr.quality_rate, 100) < 80 THEN 50
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WHEN COALESCE(sqr.quality_rate, 100) < 90 THEN 30
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WHEN COALESCE(sqr.quality_rate, 100) < 95 THEN 15
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ELSE 5
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END AS quality_risk_score
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FROM dim_supplier s
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LEFT JOIN supplier_delivery sd ON s.supplier_id = sd.supplier_id
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LEFT JOIN supplier_quality_rate sqr ON s.supplier_id = sqr.supplier_id
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WHERE s.is_current = 't'
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),
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supplier_risk_level AS (
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SELECT
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*,
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delivery_risk_score + quality_risk_score AS total_risk_score,
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CASE
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WHEN delivery_risk_score + quality_risk_score >= 80 THEN 'HIGH'
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WHEN delivery_risk_score + quality_risk_score >= 50 THEN 'MEDIUM'
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ELSE 'LOW'
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END AS risk_level,
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CASE
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WHEN delivery_risk_score >= 50 AND quality_risk_score >= 30 THEN 'DELIVERY_AND_QUALITY'
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WHEN delivery_risk_score >= 50 THEN 'DELIVERY_ISSUE'
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WHEN quality_risk_score >= 30 THEN 'QUALITY_ISSUE'
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ELSE 'NORMAL'
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END AS risk_pattern
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FROM supplier_risk
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)
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SELECT
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supplier_name,
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supplier_category,
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order_count,
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receipt_count,
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avg_delivery_days,
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max_delivery_days,
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delivery_volatility,
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total_receipts,
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return_count,
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quality_rate,
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delivery_risk_score,
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quality_risk_score,
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total_risk_score,
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risk_level,
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risk_pattern
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FROM supplier_risk_level
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ORDER BY total_risk_score DESC, supplier_name;
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-- =====================================================
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-- 补充查询1：高风险订单预警清单
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-- =====================================================
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WITH supplier_risk_info AS (
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SELECT
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s.supplier_id,
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s.supplier_name,
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s.supplier_category,
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COALESCE(
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(SELECT AVG(EXTRACT(DAY FROM pr.doc_date_utc::timestamp - po2.doc_date_utc::timestamp))
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FROM fact_purchase_order po2
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LEFT JOIN fact_purchase_receipt pr ON po2.supplier_id = pr.supplier_id
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WHERE po2.supplier_id = s.supplier_id
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AND pr.doc_date_utc IS NOT NULL), 0
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) AS avg_delivery_days,
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COALESCE(
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(SELECT COUNT(*) FROM fact_purchase_return pret WHERE pret.supplier_id = s.supplier_id), 0
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) AS return_count,
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COALESCE(
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(SELECT COUNT(*) FROM fact_purchase_receipt pr WHERE pr.supplier_id = s.supplier_id), 0
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) AS receipt_count
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FROM dim_supplier s
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WHERE s.is_current = 't'
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),
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order_risk AS (
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SELECT
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po.purchase_order_number,
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po.doc_date_utc::date AS order_date,
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sri.supplier_name,
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sri.supplier_category,
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ROUND(sri.avg_delivery_days, 1) AS supplier_avg_days,
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sri.return_count,
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sri.receipt_count,
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CASE WHEN sri.receipt_count > 0
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THEN ROUND((sri.receipt_count - sri.return_count) * 100.0 / sri.receipt_count, 1)
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ELSE 100 END AS quality_rate,
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EXTRACT(DAY FROM CURRENT_TIMESTAMP - po.doc_date_utc::timestamp) AS days_since_order,
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CASE
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WHEN sri.avg_delivery_days > 45 AND sri.return_count > 0 THEN 'HIGH'
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WHEN sri.avg_delivery_days > 45 OR sri.return_count > 0 THEN 'MEDIUM'
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ELSE 'LOW'
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END AS risk_level
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FROM fact_purchase_order po
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JOIN supplier_risk_info sri ON po.supplier_id = sri.supplier_id
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)
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SELECT
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purchase_order_number,
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order_date,
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supplier_name,
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supplier_category,
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supplier_avg_days,
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quality_rate,
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days_since_order,
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risk_level,
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CASE
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WHEN risk_level = 'HIGH' THEN 'IMMEDIATE_FOLLOWUP'
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WHEN risk_level = 'MEDIUM' THEN 'MONITOR'
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ELSE 'NORMAL'
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END AS action_required
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FROM order_risk
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WHERE risk_level IN ('HIGH', 'MEDIUM')
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ORDER BY
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CASE risk_level WHEN 'HIGH' THEN 1 WHEN 'MEDIUM' THEN 2 ELSE 3 END,
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days_since_order DESC;
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-- =====================================================
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-- 补充查询2：供应商类别风险分布
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-- =====================================================
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WITH supplier_stats AS (
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SELECT
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s.supplier_category,
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COUNT(DISTINCT s.supplier_id) AS supplier_count,
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COUNT(DISTINCT po.purchase_order_id) AS order_count,
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COUNT(DISTINCT pr.purchase_receipt_id) AS receipt_count,
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COUNT(DISTINCT pret.purchase_return_id) AS return_count,
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SUM(pr.amount) AS total_amount
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FROM dim_supplier s
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LEFT JOIN fact_purchase_order po ON s.supplier_id = po.supplier_id
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LEFT JOIN fact_purchase_receipt pr ON s.supplier_id = pr.supplier_id
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LEFT JOIN fact_purchase_return pret ON s.supplier_id = pret.supplier_id
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WHERE s.is_current = 't'
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GROUP BY s.supplier_category
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)
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SELECT
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supplier_category,
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supplier_count,
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order_count,
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receipt_count,
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return_count,
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CASE WHEN receipt_count > 0
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THEN ROUND((receipt_count - return_count) * 100.0 / receipt_count, 1)
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ELSE 100 END AS quality_rate,
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ROUND(COALESCE(total_amount, 0), 2) AS purchase_amount,
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CASE
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WHEN receipt_count > 0 AND return_count * 100.0 / receipt_count > 10 THEN 'HIGH'
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WHEN receipt_count > 0 AND return_count * 100.0 / receipt_count > 5 THEN 'MEDIUM'
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ELSE 'LOW'
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END AS category_risk_level
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FROM supplier_stats
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ORDER BY return_count DESC;
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-- =====================================================
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-- 补充查询3：近期交期异常趋势
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-- =====================================================
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WITH monthly_delivery AS (
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SELECT
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DATE_TRUNC('month', pr.doc_date_utc::timestamp)::date AS month_start,
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COUNT(*) AS receipt_count,
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AVG(EXTRACT(DAY FROM pr.doc_date_utc::timestamp - po.doc_date_utc::timestamp)) AS avg_delivery_days
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FROM fact_purchase_receipt pr
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JOIN fact_purchase_order po ON pr.supplier_id = po.supplier_id
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WHERE pr.doc_date_utc IS NOT NULL AND po.doc_date_utc IS NOT NULL
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GROUP BY DATE_TRUNC('month', pr.doc_date_utc::timestamp)
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),
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monthly_returns AS (
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SELECT
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DATE_TRUNC('month', pret.doc_date_utc::timestamp)::date AS month_start,
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COUNT(*) AS return_count
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FROM fact_purchase_return pret
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GROUP BY DATE_TRUNC('month', pret.doc_date_utc::timestamp)
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),
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monthly_combined AS (
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SELECT
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md.month_start,
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md.receipt_count,
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ROUND(md.avg_delivery_days, 1) AS avg_delivery_days,
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COALESCE(mr.return_count, 0) AS return_count
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FROM monthly_delivery md
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LEFT JOIN monthly_returns mr ON md.month_start = mr.month_start
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),
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with_trend AS (
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SELECT
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*,
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LAG(avg_delivery_days, 1) OVER (ORDER BY month_start) AS prev_avg_days,
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LAG(return_count, 1) OVER (ORDER BY month_start) AS prev_return_count
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FROM monthly_combined
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)
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SELECT
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month_start,
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receipt_count,
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avg_delivery_days,
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return_count,
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CASE WHEN receipt_count > 0
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THEN ROUND(return_count * 100.0 / receipt_count, 1)
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ELSE 0 END AS return_rate,
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CASE
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WHEN prev_avg_days IS NULL THEN 'NONE'
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WHEN avg_delivery_days > prev_avg_days * 1.1 THEN 'INCREASING'
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WHEN avg_delivery_days < prev_avg_days * 0.9 THEN 'DECREASING'
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ELSE 'STABLE'
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END AS delivery_trend,
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CASE
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WHEN prev_return_count IS NULL THEN 'NONE'
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WHEN return_count > prev_return_count THEN 'INCREASING'
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WHEN return_count < prev_return_count THEN 'DECREASING'
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ELSE 'STABLE'
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END AS return_trend
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FROM with_trend
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ORDER BY month_start DESC;
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-- =====================================================
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-- 补充查询4：风险预警汇总看板
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-- =====================================================
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WITH risk_summary AS (
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SELECT
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s.supplier_id,
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s.supplier_name,
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COALESCE(
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(SELECT COUNT(*) FROM fact_purchase_return pret WHERE pret.supplier_id = s.supplier_id), 0
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) AS return_count,
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COALESCE(
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(SELECT COUNT(*) FROM fact_purchase_receipt pr WHERE pr.supplier_id = s.supplier_id), 0
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) AS receipt_count
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FROM dim_supplier s
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WHERE s.is_current = 't'
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),
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risk_counts AS (
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SELECT
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SUM(CASE WHEN receipt_count > 0 AND return_count * 100.0 / receipt_count > 10 THEN 1 ELSE 0 END) AS high_risk_suppliers,
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SUM(CASE WHEN receipt_count > 0 AND return_count * 100.0 / receipt_count BETWEEN 5 AND 10 THEN 1 ELSE 0 END) AS medium_risk_suppliers,
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SUM(CASE WHEN receipt_count = 0 OR return_count * 100.0 / receipt_count < 5 THEN 1 ELSE 0 END) AS low_risk_suppliers,
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COUNT(*) AS total_suppliers
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FROM risk_summary
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),
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order_stats AS (
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SELECT
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COUNT(*) AS pending_orders,
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COUNT(CASE WHEN EXTRACT(DAY FROM CURRENT_TIMESTAMP - doc_date_utc::timestamp) > 30 THEN 1 END) AS overdue_orders
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FROM fact_purchase_order
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),
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return_stats AS (
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SELECT
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COUNT(*) AS total_returns,
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COUNT(CASE WHEN doc_date_utc::timestamp >= CURRENT_DATE - INTERVAL '30 days' THEN 1 END) AS recent_returns
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FROM fact_purchase_return
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)
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SELECT
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'high_risk_suppliers' AS metric_name,
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rc.high_risk_suppliers::text AS metric_value,
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CASE WHEN rc.high_risk_suppliers > 0 THEN 'ATTENTION_NEEDED' ELSE 'NORMAL' END AS status
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FROM risk_counts rc
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UNION ALL
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SELECT 'medium_risk_suppliers', rc.medium_risk_suppliers::text,
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CASE WHEN rc.medium_risk_suppliers > 2 THEN 'MONITOR' ELSE 'NORMAL' END
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FROM risk_counts rc
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UNION ALL
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SELECT 'low_risk_suppliers', rc.low_risk_suppliers::text, 'NORMAL'
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FROM risk_counts rc
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UNION ALL
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SELECT 'pending_orders', os.pending_orders::text,
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CASE WHEN os.pending_orders > 20 THEN 'BACKLOG' ELSE 'NORMAL' END
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FROM order_stats os
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UNION ALL
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SELECT 'overdue_orders_30d', os.overdue_orders::text,
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CASE WHEN os.overdue_orders > 5 THEN 'DELIVERY_WARNING' ELSE 'NORMAL' END
|
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FROM order_stats os
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UNION ALL
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SELECT 'recent_returns_30d', rs.recent_returns::text,
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CASE WHEN rs.recent_returns > 3 THEN 'QUALITY_WARNING' ELSE 'NORMAL' END
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FROM return_stats rs;
|
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|
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-- =====================================================
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-- 补充查询5：供应商风险排行榜
|
||||
-- =====================================================
|
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WITH supplier_metrics AS (
|
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SELECT
|
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s.supplier_id,
|
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s.supplier_name,
|
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s.supplier_category,
|
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COUNT(DISTINCT po.purchase_order_id) AS order_count,
|
||||
COUNT(DISTINCT pr.purchase_receipt_id) AS receipt_count,
|
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COUNT(DISTINCT pret.purchase_return_id) AS return_count,
|
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SUM(pr.amount) AS total_amount
|
||||
FROM dim_supplier s
|
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LEFT JOIN fact_purchase_order po ON s.supplier_id = po.supplier_id
|
||||
LEFT JOIN fact_purchase_receipt pr ON s.supplier_id = pr.supplier_id
|
||||
LEFT JOIN fact_purchase_return pret ON s.supplier_id = pret.supplier_id
|
||||
WHERE s.is_current = 't'
|
||||
GROUP BY s.supplier_id, s.supplier_name, s.supplier_category
|
||||
),
|
||||
ranked_suppliers AS (
|
||||
SELECT
|
||||
*,
|
||||
CASE WHEN receipt_count > 0
|
||||
THEN ROUND(return_count * 100.0 / receipt_count, 1)
|
||||
ELSE 0 END AS return_rate,
|
||||
ROW_NUMBER() OVER (ORDER BY
|
||||
CASE WHEN receipt_count > 0 THEN return_count * 1.0 / receipt_count ELSE 0 END DESC,
|
||||
return_count DESC
|
||||
) AS risk_rank
|
||||
FROM supplier_metrics
|
||||
)
|
||||
SELECT
|
||||
risk_rank,
|
||||
supplier_name,
|
||||
supplier_category,
|
||||
order_count,
|
||||
receipt_count,
|
||||
return_count,
|
||||
return_rate,
|
||||
ROUND(COALESCE(total_amount, 0), 2) AS purchase_amount,
|
||||
CASE
|
||||
WHEN return_rate > 10 THEN 'HIGH_RISK'
|
||||
WHEN return_rate > 5 THEN 'MEDIUM_RISK'
|
||||
WHEN return_count > 0 THEN 'LOW_RISK'
|
||||
ELSE 'EXCELLENT'
|
||||
END AS risk_assessment
|
||||
FROM ranked_suppliers
|
||||
ORDER BY risk_rank
|
||||
LIMIT 20;
|
||||
Reference in New Issue
Block a user