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/人效产值损耗三维模型仪表盘.sql
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lzwcai_mcpskills_mfg_data_agent/sql/人效产值损耗三维模型仪表盘.sql
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-- =====================================================
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-- 人效-产值-损耗三维模型仪表盘SQL
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-- Efficiency-Output-Loss 3D Model Dashboard
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-- 数据库: PostgreSQL
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-- 维度: 产品类别(化工/机械/电子)作为部门维度
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-- =====================================================
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-- 1. 部门级综合仪表盘（主查询）
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WITH
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labor_stats AS (
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SELECT
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p.product_category AS department,
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COUNT(DISTINCT lr.worker_name) AS worker_count,
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SUM(lr.duration_minutes) AS total_work_minutes,
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SUM(lr.report_qty) AS total_output_qty,
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COUNT(DISTINCT lr.work_order_number) AS work_order_count
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FROM fact_labor_report lr
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INNER JOIN dim_product p ON lr.product_id = p.product_id AND p.is_current = 't'
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GROUP BY p.product_category
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),
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work_order_stats AS (
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SELECT
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p.product_category AS department,
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COUNT(*) AS total_work_orders,
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SUM(wo.planned_qty) AS total_planned_qty,
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SUM(wo.completed_qty) AS total_completed_qty,
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SUM(CASE WHEN wo.status = 'CLOSED' THEN 1 ELSE 0 END) AS closed_orders,
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SUM(CASE WHEN wo.status = 'STARTED' THEN 1 ELSE 0 END) AS started_orders,
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SUM(CASE WHEN wo.status = 'OPEN' THEN 1 ELSE 0 END) AS open_orders
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FROM fact_work_order wo
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INNER JOIN dim_product p ON wo.product_id = p.product_id AND p.is_current = 't'
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GROUP BY p.product_category
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),
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quality_stats AS (
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SELECT
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p.product_category AS department,
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SUM(qi.pass_qty) AS total_pass_qty,
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SUM(qi.fail_qty) AS total_fail_qty,
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COUNT(*) AS inspection_count
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FROM fact_quality_inspection qi
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INNER JOIN dim_product p ON qi.product_id = p.product_id AND p.is_current = 't'
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GROUP BY p.product_category
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),
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sales_stats AS (
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SELECT
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AVG(deal_amount) AS avg_order_amount,
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SUM(deal_amount) AS total_sales_amount,
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COUNT(*) AS order_count
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FROM fact_sales_order
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),
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scrap_stats AS (
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SELECT COUNT(*) AS total_scrap_count
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FROM fact_scrap
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)
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SELECT
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ls.department,
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-- 人效维度
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ls.worker_count,
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ROUND(ls.total_work_minutes / 60.0, 2) AS total_work_hours,
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ls.total_output_qty,
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ROUND(ls.total_output_qty / NULLIF(ls.worker_count, 0), 2) AS output_per_worker,
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ROUND(ls.total_output_qty / NULLIF(ls.total_work_minutes / 60.0, 0), 2) AS output_per_hour,
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ROUND(
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ls.total_output_qty / NULLIF(ls.worker_count, 0) / NULLIF(ls.total_work_minutes / 60.0 / ls.worker_count, 0),
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2
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) AS efficiency_index,
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-- 产值维度
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ws.total_planned_qty AS planned_qty,
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ws.total_completed_qty AS completed_qty,
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ROUND(ws.total_completed_qty / NULLIF(ws.total_planned_qty, 0) * 100, 2) AS plan_completion_rate,
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ROUND(ws.total_completed_qty * ss.avg_order_amount / 100, 2) AS estimated_output_value,
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ROUND(ws.total_completed_qty * ss.avg_order_amount / 100 / NULLIF(ls.worker_count, 0), 2) AS output_value_per_worker,
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-- 损耗维度
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qs.total_pass_qty AS qc_pass_qty,
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qs.total_fail_qty AS qc_fail_qty,
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ROUND(qs.total_fail_qty / NULLIF(qs.total_pass_qty + qs.total_fail_qty, 0) * 100, 2) AS defect_rate,
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ROUND((ws.total_planned_qty - ws.total_completed_qty) / NULLIF(ws.total_planned_qty, 0) * 100, 2) AS production_loss_rate,
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-- 综合评分
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ROUND(
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(ls.total_output_qty / NULLIF(ls.worker_count, 0) / NULLIF(ls.total_work_minutes / 60.0 / ls.worker_count, 0)) * 0.4 +
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(ws.total_completed_qty / NULLIF(ws.total_planned_qty, 0) * 100) * 0.35 +
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(qs.total_pass_qty / NULLIF(qs.total_pass_qty + qs.total_fail_qty, 0) * 100) * 0.25,
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2
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) AS performance_score,
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-- 预警等级
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CASE
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WHEN (qs.total_fail_qty / NULLIF(qs.total_pass_qty + qs.total_fail_qty, 0) * 100) >= 10
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OR (ws.total_completed_qty / NULLIF(ws.total_planned_qty, 0) * 100) < 50
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THEN 'RED'
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WHEN (qs.total_fail_qty / NULLIF(qs.total_pass_qty + qs.total_fail_qty, 0) * 100) >= 5
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OR (ws.total_completed_qty / NULLIF(ws.total_planned_qty, 0) * 100) < 70
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THEN 'YELLOW'
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ELSE 'GREEN'
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END AS warning_level
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FROM labor_stats ls
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LEFT JOIN work_order_stats ws ON ls.department = ws.department
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LEFT JOIN quality_stats qs ON ls.department = qs.department
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CROSS JOIN sales_stats ss
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CROSS JOIN scrap_stats scr
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ORDER BY performance_score DESC;
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-- =====================================================
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-- 2. 人员级明细报表
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-- =====================================================
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SELECT
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lr.worker_name,
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p.product_category AS department,
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COUNT(DISTINCT lr.work_order_number) AS work_order_count,
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SUM(lr.duration_minutes) AS total_work_minutes,
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ROUND(SUM(lr.duration_minutes) / 60.0, 2) AS total_work_hours,
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SUM(lr.report_qty) AS total_output,
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ROUND(SUM(lr.report_qty) / NULLIF(SUM(lr.duration_minutes) / 60.0, 0), 2) AS output_per_hour,
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RANK() OVER (PARTITION BY p.product_category ORDER BY SUM(lr.report_qty) DESC) AS dept_output_rank
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FROM fact_labor_report lr
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INNER JOIN dim_product p ON lr.product_id = p.product_id AND p.is_current = 't'
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GROUP BY lr.worker_name, p.product_category
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ORDER BY p.product_category, total_output DESC;
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-- =====================================================
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-- 3. 月度趋势分析
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-- =====================================================
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SELECT
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TO_CHAR(DATE_TRUNC('month', lr.event_time_utc::timestamp), 'YYYY-MM') AS month,
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p.product_category AS department,
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COUNT(DISTINCT lr.worker_name) AS active_worker_count,
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SUM(lr.duration_minutes) AS total_work_minutes,
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SUM(lr.report_qty) AS total_output,
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ROUND(SUM(lr.report_qty) / NULLIF(COUNT(DISTINCT lr.worker_name), 0), 2) AS output_per_worker,
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ROUND(SUM(lr.report_qty) / NULLIF(SUM(lr.duration_minutes) / 60.0, 0), 2) AS output_per_hour
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FROM fact_labor_report lr
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INNER JOIN dim_product p ON lr.product_id = p.product_id AND p.is_current = 't'
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GROUP BY DATE_TRUNC('month', lr.event_time_utc::timestamp), p.product_category
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ORDER BY month DESC, p.product_category;
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-- =====================================================
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-- 4. 产品级损耗分析
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-- =====================================================
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SELECT
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p.product_category AS department,
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p.product_name,
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p.product_code,
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COALESCE(SUM(qi.pass_qty), 0) AS pass_qty,
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COALESCE(SUM(qi.fail_qty), 0) AS fail_qty,
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ROUND(
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COALESCE(SUM(qi.fail_qty), 0) /
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NULLIF(COALESCE(SUM(qi.pass_qty), 0) + COALESCE(SUM(qi.fail_qty), 0), 0) * 100,
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2
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) AS defect_rate,
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CASE
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WHEN COALESCE(SUM(qi.fail_qty), 0) /
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NULLIF(COALESCE(SUM(qi.pass_qty), 0) + COALESCE(SUM(qi.fail_qty), 0), 0) * 100 >= 10
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THEN 'HIGH'
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WHEN COALESCE(SUM(qi.fail_qty), 0) /
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NULLIF(COALESCE(SUM(qi.pass_qty), 0) + COALESCE(SUM(qi.fail_qty), 0), 0) * 100 >= 5
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THEN 'MEDIUM'
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ELSE 'LOW'
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END AS loss_level
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FROM dim_product p
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LEFT JOIN fact_quality_inspection qi ON p.product_id = qi.product_id
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WHERE p.is_current = 't'
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GROUP BY p.product_category, p.product_name, p.product_code
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ORDER BY defect_rate DESC NULLS LAST;
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-- =====================================================
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-- 5. 工单完成率分析
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-- =====================================================
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SELECT
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p.product_category AS department,
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wo.status,
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COUNT(*) AS order_count,
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SUM(wo.planned_qty) AS total_planned,
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SUM(wo.completed_qty) AS total_completed,
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ROUND(SUM(wo.completed_qty) / NULLIF(SUM(wo.planned_qty), 0) * 100, 2) AS completion_rate,
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ROUND(AVG(wo.completed_qty / NULLIF(wo.planned_qty, 0) * 100), 2) AS avg_completion_rate
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FROM fact_work_order wo
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INNER JOIN dim_product p ON wo.product_id = p.product_id AND p.is_current = 't'
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GROUP BY p.product_category, wo.status
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ORDER BY p.product_category, wo.status;
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