yuanzhipeng
3ea772c3be
- 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
427 lines
16 KiB
SQL
427 lines
16 KiB
SQL
-- =====================================================
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-- 指标趋势分析与拐点预警SQL
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-- Metric Trend Analysis and Turning Point Warning
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-- 数据库: PostgreSQL
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-- =====================================================
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-- =====================================================
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-- 1. 日度指标基础数据
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-- =====================================================
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WITH daily_metrics AS (
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SELECT
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DATE(lr.event_time_utc::timestamp) AS metric_date,
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COUNT(DISTINCT lr.worker_name) AS worker_count,
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SUM(lr.duration_minutes) / 60.0 AS total_hours,
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SUM(lr.report_qty) AS total_output,
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CASE WHEN SUM(lr.duration_minutes) > 0
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THEN SUM(lr.report_qty) / (SUM(lr.duration_minutes) / 60.0)
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ELSE 0 END AS hourly_efficiency
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FROM fact_labor_report lr
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GROUP BY DATE(lr.event_time_utc::timestamp)
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),
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daily_quality AS (
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SELECT
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DATE(qi.event_time_utc::timestamp) AS metric_date,
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SUM(qi.pass_qty) AS pass_qty,
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SUM(qi.fail_qty) AS fail_qty,
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CASE WHEN SUM(qi.pass_qty) + SUM(qi.fail_qty) > 0
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THEN SUM(qi.fail_qty) * 100.0 / (SUM(qi.pass_qty) + SUM(qi.fail_qty))
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ELSE 0 END AS defect_rate
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FROM fact_quality_inspection qi
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GROUP BY DATE(qi.event_time_utc::timestamp)
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),
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daily_production AS (
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SELECT
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DATE(wo.event_time_utc::timestamp) AS metric_date,
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SUM(wo.planned_qty) AS planned_qty,
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SUM(wo.completed_qty) AS completed_qty,
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CASE WHEN SUM(wo.planned_qty) > 0
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THEN SUM(wo.completed_qty) * 100.0 / SUM(wo.planned_qty)
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ELSE 0 END AS completion_rate
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FROM fact_work_order wo
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GROUP BY DATE(wo.event_time_utc::timestamp)
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),
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combined_daily AS (
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SELECT
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COALESCE(dm.metric_date, dq.metric_date, dp.metric_date) AS metric_date,
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COALESCE(dm.worker_count, 0) AS worker_count,
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COALESCE(dm.total_hours, 0) AS total_hours,
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COALESCE(dm.total_output, 0) AS total_output,
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COALESCE(dm.hourly_efficiency, 0) AS hourly_efficiency,
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COALESCE(dq.defect_rate, 0) AS defect_rate,
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COALESCE(dp.completion_rate, 0) AS completion_rate
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FROM daily_metrics dm
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FULL OUTER JOIN daily_quality dq ON dm.metric_date = dq.metric_date
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FULL OUTER JOIN daily_production dp ON dm.metric_date = dp.metric_date
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WHERE COALESCE(dm.metric_date, dq.metric_date, dp.metric_date) IS NOT NULL
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),
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numbered_data AS (
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SELECT
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*,
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ROW_NUMBER() OVER (ORDER BY metric_date) AS day_seq
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FROM combined_daily
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),
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-- =====================================================
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-- 2. 移动平均计算 (7日移动平均)
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-- =====================================================
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moving_avg_step1 AS (
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SELECT
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metric_date,
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day_seq,
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worker_count,
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total_output,
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hourly_efficiency,
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defect_rate,
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completion_rate,
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AVG(hourly_efficiency) OVER (ORDER BY metric_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma7_efficiency,
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AVG(total_output) OVER (ORDER BY metric_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma7_output,
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AVG(defect_rate) OVER (ORDER BY metric_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma7_defect_rate,
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AVG(completion_rate) OVER (ORDER BY metric_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma7_completion_rate,
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AVG(day_seq) OVER (ORDER BY metric_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS avg_x
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FROM numbered_data
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),
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moving_avg AS (
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SELECT
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*,
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LAG(ma7_efficiency, 1) OVER (ORDER BY metric_date) AS prev_ma7_efficiency,
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LAG(ma7_output, 1) OVER (ORDER BY metric_date) AS prev_ma7_output,
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LAG(ma7_defect_rate, 1) OVER (ORDER BY metric_date) AS prev_ma7_defect_rate
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FROM moving_avg_step1
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),
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-- =====================================================
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-- 3. 简化的趋势斜率计算
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-- =====================================================
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slope_calc AS (
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SELECT
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*,
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(ma7_efficiency - LAG(ma7_efficiency, 3) OVER (ORDER BY metric_date)) / 3.0 AS slope_efficiency,
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(ma7_output - LAG(ma7_output, 3) OVER (ORDER BY metric_date)) / 3.0 AS slope_output,
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(ma7_defect_rate - LAG(ma7_defect_rate, 3) OVER (ORDER BY metric_date)) / 3.0 AS slope_defect
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FROM moving_avg
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),
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-- =====================================================
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-- 4. 趋势判断与异常检测
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-- =====================================================
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trend_analysis AS (
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SELECT
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metric_date,
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hourly_efficiency,
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total_output,
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defect_rate,
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completion_rate,
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ROUND(ma7_efficiency, 2) AS ma7_efficiency,
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ROUND(ma7_output, 2) AS ma7_output,
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ROUND(ma7_defect_rate, 2) AS ma7_defect_rate,
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ROUND(COALESCE(slope_efficiency, 0), 4) AS slope_efficiency,
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ROUND(COALESCE(slope_output, 0), 4) AS slope_output,
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ROUND(COALESCE(slope_defect, 0), 4) AS slope_defect,
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prev_ma7_efficiency,
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prev_ma7_output,
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prev_ma7_defect_rate,
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CASE
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WHEN COALESCE(slope_efficiency, 0) > 0.3 THEN 'RISING'
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WHEN COALESCE(slope_efficiency, 0) < -0.3 THEN 'FALLING'
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ELSE 'STABLE'
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END AS efficiency_trend,
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CASE
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WHEN COALESCE(slope_output, 0) > 3 THEN 'RISING'
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WHEN COALESCE(slope_output, 0) < -3 THEN 'FALLING'
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ELSE 'STABLE'
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END AS output_trend,
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CASE
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WHEN COALESCE(slope_defect, 0) > 0.3 THEN 'RISING'
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WHEN COALESCE(slope_defect, 0) < -0.3 THEN 'FALLING'
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ELSE 'STABLE'
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END AS defect_trend,
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CASE
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WHEN ma7_efficiency > 0 AND ABS(hourly_efficiency - ma7_efficiency) > ma7_efficiency * 0.3 THEN 'ANOMALY'
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ELSE 'NORMAL'
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END AS efficiency_status,
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CASE
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WHEN ma7_output > 0 AND ABS(total_output - ma7_output) > ma7_output * 0.3 THEN 'ANOMALY'
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ELSE 'NORMAL'
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END AS output_status,
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CASE
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WHEN defect_rate > ma7_defect_rate * 1.5 AND defect_rate > 5 THEN 'ANOMALY'
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ELSE 'NORMAL'
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END AS defect_status
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FROM slope_calc
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)
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-- =====================================================
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-- 输出：日度趋势分析明细
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-- =====================================================
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SELECT
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metric_date,
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ROUND(hourly_efficiency, 2) AS hourly_output,
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ma7_efficiency AS efficiency_ma7,
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slope_efficiency,
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efficiency_trend,
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efficiency_status,
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CASE
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WHEN prev_ma7_efficiency IS NOT NULL
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AND ma7_efficiency > prev_ma7_efficiency AND slope_efficiency < 0 THEN 'TURNING_POINT'
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WHEN prev_ma7_efficiency IS NOT NULL
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AND ma7_efficiency < prev_ma7_efficiency AND slope_efficiency > 0 THEN 'TURNING_POINT'
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ELSE 'NONE'
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END AS efficiency_turning_point,
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ROUND(total_output, 0) AS daily_output,
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ma7_output AS output_ma7,
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slope_output,
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output_trend,
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output_status,
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CASE
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WHEN prev_ma7_output IS NOT NULL
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AND ma7_output > prev_ma7_output AND slope_output < 0 THEN 'TURNING_POINT'
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WHEN prev_ma7_output IS NOT NULL
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AND ma7_output < prev_ma7_output AND slope_output > 0 THEN 'TURNING_POINT'
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ELSE 'NONE'
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END AS output_turning_point,
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ROUND(defect_rate, 2) AS defect_rate,
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ma7_defect_rate AS defect_rate_ma7,
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slope_defect,
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defect_trend,
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defect_status,
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CASE
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WHEN prev_ma7_defect_rate IS NOT NULL
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AND ma7_defect_rate > prev_ma7_defect_rate AND slope_defect < 0 THEN 'TURNING_POINT'
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WHEN prev_ma7_defect_rate IS NOT NULL
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AND ma7_defect_rate < prev_ma7_defect_rate AND slope_defect > 0 THEN 'TURNING_POINT'
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ELSE 'NONE'
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END AS defect_turning_point
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FROM trend_analysis
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ORDER BY metric_date DESC;
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-- =====================================================
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-- 补充查询1：周度趋势汇总
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-- =====================================================
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WITH weekly_metrics AS (
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SELECT
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DATE_TRUNC('week', lr.event_time_utc::timestamp)::date AS week_start,
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COUNT(DISTINCT lr.worker_name) AS worker_count,
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SUM(lr.duration_minutes) / 60.0 AS total_hours,
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SUM(lr.report_qty) AS total_output,
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CASE WHEN SUM(lr.duration_minutes) > 0
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THEN SUM(lr.report_qty) / (SUM(lr.duration_minutes) / 60.0)
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ELSE 0 END AS hourly_efficiency
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FROM fact_labor_report lr
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GROUP BY DATE_TRUNC('week', lr.event_time_utc::timestamp)
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),
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weekly_quality AS (
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SELECT
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DATE_TRUNC('week', qi.event_time_utc::timestamp)::date AS week_start,
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SUM(qi.fail_qty) * 100.0 / NULLIF(SUM(qi.pass_qty) + SUM(qi.fail_qty), 0) AS defect_rate
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FROM fact_quality_inspection qi
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GROUP BY DATE_TRUNC('week', qi.event_time_utc::timestamp)
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),
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weekly_combined AS (
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SELECT
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wm.week_start,
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wm.worker_count,
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wm.total_hours,
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wm.total_output,
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wm.hourly_efficiency,
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COALESCE(wq.defect_rate, 0) AS defect_rate
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FROM weekly_metrics wm
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LEFT JOIN weekly_quality wq ON wm.week_start = wq.week_start
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),
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weekly_with_lag AS (
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SELECT
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*,
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LAG(hourly_efficiency, 1) OVER (ORDER BY week_start) AS prev_efficiency,
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LAG(total_output, 1) OVER (ORDER BY week_start) AS prev_output,
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LAG(defect_rate, 1) OVER (ORDER BY week_start) AS prev_defect_rate
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FROM weekly_combined
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)
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SELECT
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week_start,
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worker_count,
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ROUND(total_hours, 1) AS total_hours,
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ROUND(total_output, 0) AS total_output,
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ROUND(hourly_efficiency, 2) AS hourly_output,
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ROUND(defect_rate, 2) AS defect_rate,
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CASE
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WHEN prev_efficiency IS NULL THEN 'NONE'
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WHEN hourly_efficiency > prev_efficiency * 1.1 THEN 'RISING'
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WHEN hourly_efficiency < prev_efficiency * 0.9 THEN 'FALLING'
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ELSE 'STABLE'
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END AS efficiency_trend,
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CASE
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WHEN prev_output IS NULL THEN 'NONE'
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WHEN total_output > prev_output * 1.1 THEN 'RISING'
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WHEN total_output < prev_output * 0.9 THEN 'FALLING'
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ELSE 'STABLE'
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END AS output_trend,
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CASE
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WHEN prev_defect_rate IS NULL THEN 'NONE'
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WHEN defect_rate > prev_defect_rate * 1.2 THEN 'RISING'
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WHEN defect_rate < prev_defect_rate * 0.8 THEN 'FALLING'
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ELSE 'STABLE'
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END AS defect_trend,
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ROUND((hourly_efficiency - COALESCE(prev_efficiency, hourly_efficiency)) / NULLIF(prev_efficiency, 0) * 100, 1) AS efficiency_wow_pct
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FROM weekly_with_lag
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ORDER BY week_start DESC;
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-- =====================================================
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-- 补充查询2：指标趋势汇总报告
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-- =====================================================
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WITH
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recent_data AS (
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SELECT
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DATE(lr.event_time_utc::timestamp) AS metric_date,
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SUM(lr.report_qty) / NULLIF(SUM(lr.duration_minutes) / 60.0, 0) AS hourly_efficiency,
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SUM(lr.report_qty) AS total_output
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FROM fact_labor_report lr
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WHERE lr.event_time_utc::timestamp >= CURRENT_DATE - INTERVAL '14 days'
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GROUP BY DATE(lr.event_time_utc::timestamp)
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),
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recent_quality AS (
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SELECT
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DATE(qi.event_time_utc::timestamp) AS metric_date,
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SUM(qi.fail_qty) * 100.0 / NULLIF(SUM(qi.pass_qty) + SUM(qi.fail_qty), 0) AS defect_rate
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FROM fact_quality_inspection qi
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WHERE qi.event_time_utc::timestamp >= CURRENT_DATE - INTERVAL '14 days'
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GROUP BY DATE(qi.event_time_utc::timestamp)
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),
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period_stats AS (
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SELECT
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AVG(CASE WHEN rd.metric_date >= CURRENT_DATE - INTERVAL '7 days' THEN rd.hourly_efficiency END) AS avg_eff_7d,
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AVG(CASE WHEN rd.metric_date >= CURRENT_DATE - INTERVAL '7 days' THEN rd.total_output END) AS avg_output_7d,
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AVG(CASE WHEN rd.metric_date < CURRENT_DATE - INTERVAL '7 days' THEN rd.hourly_efficiency END) AS avg_eff_prev7d,
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AVG(CASE WHEN rd.metric_date < CURRENT_DATE - INTERVAL '7 days' THEN rd.total_output END) AS avg_output_prev7d
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FROM recent_data rd
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),
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quality_stats AS (
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SELECT
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AVG(CASE WHEN rq.metric_date >= CURRENT_DATE - INTERVAL '7 days' THEN rq.defect_rate END) AS avg_defect_7d,
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AVG(CASE WHEN rq.metric_date < CURRENT_DATE - INTERVAL '7 days' THEN rq.defect_rate END) AS avg_defect_prev7d
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FROM recent_quality rq
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)
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SELECT
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'efficiency_per_hour' AS metric_name,
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ROUND(ps.avg_eff_7d, 2) AS last_7d_avg,
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ROUND(ps.avg_eff_prev7d, 2) AS prev_7d_avg,
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ROUND((ps.avg_eff_7d - ps.avg_eff_prev7d) / NULLIF(ps.avg_eff_prev7d, 0) * 100, 1) AS change_rate_pct,
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CASE
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WHEN ps.avg_eff_7d > ps.avg_eff_prev7d * 1.05 THEN 'RISING'
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WHEN ps.avg_eff_7d < ps.avg_eff_prev7d * 0.95 THEN 'FALLING'
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ELSE 'STABLE'
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END AS trend,
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CASE
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WHEN ABS(ps.avg_eff_7d - ps.avg_eff_prev7d) / NULLIF(ps.avg_eff_prev7d, 0) > 0.2 THEN 'ANOMALY'
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ELSE 'NORMAL'
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END AS warning
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FROM period_stats ps
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UNION ALL
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SELECT
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'daily_output',
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ROUND(ps.avg_output_7d, 0),
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ROUND(ps.avg_output_prev7d, 0),
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ROUND((ps.avg_output_7d - ps.avg_output_prev7d) / NULLIF(ps.avg_output_prev7d, 0) * 100, 1),
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CASE
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WHEN ps.avg_output_7d > ps.avg_output_prev7d * 1.05 THEN 'RISING'
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WHEN ps.avg_output_7d < ps.avg_output_prev7d * 0.95 THEN 'FALLING'
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ELSE 'STABLE'
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END,
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CASE
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WHEN ABS(ps.avg_output_7d - ps.avg_output_prev7d) / NULLIF(ps.avg_output_prev7d, 0) > 0.2 THEN 'ANOMALY'
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ELSE 'NORMAL'
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END
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FROM period_stats ps
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UNION ALL
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SELECT
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'defect_rate_pct',
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ROUND(qs.avg_defect_7d, 2),
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ROUND(qs.avg_defect_prev7d, 2),
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ROUND((qs.avg_defect_7d - qs.avg_defect_prev7d) / NULLIF(qs.avg_defect_prev7d, 0) * 100, 1),
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CASE
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WHEN qs.avg_defect_7d > qs.avg_defect_prev7d * 1.1 THEN 'RISING'
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WHEN qs.avg_defect_7d < qs.avg_defect_prev7d * 0.9 THEN 'FALLING'
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ELSE 'STABLE'
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END,
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CASE
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WHEN qs.avg_defect_7d > 8 THEN 'THRESHOLD_EXCEEDED'
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WHEN qs.avg_defect_7d > qs.avg_defect_prev7d * 1.3 THEN 'ANOMALY_RISING'
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ELSE 'NORMAL'
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END
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FROM quality_stats qs;
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-- =====================================================
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-- 补充查询3：拐点预警汇总
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-- =====================================================
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WITH daily_eff AS (
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SELECT
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DATE(lr.event_time_utc::timestamp) AS metric_date,
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SUM(lr.report_qty) / NULLIF(SUM(lr.duration_minutes) / 60.0, 0) AS hourly_efficiency
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FROM fact_labor_report lr
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GROUP BY DATE(lr.event_time_utc::timestamp)
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),
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with_ma_step1 AS (
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SELECT
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metric_date,
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hourly_efficiency,
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AVG(hourly_efficiency) OVER (ORDER BY metric_date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS ma7
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FROM daily_eff
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),
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with_ma AS (
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SELECT
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metric_date,
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hourly_efficiency,
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ma7,
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LAG(ma7, 1) OVER (ORDER BY metric_date) AS prev_ma7,
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LAG(ma7, 2) OVER (ORDER BY metric_date) AS prev2_ma7
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FROM with_ma_step1
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),
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turning_points AS (
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SELECT
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metric_date,
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hourly_efficiency,
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ma7,
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prev_ma7,
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prev2_ma7,
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CASE
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WHEN prev2_ma7 IS NOT NULL
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AND prev_ma7 < prev2_ma7 AND ma7 > prev_ma7 THEN 'UPWARD'
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WHEN prev2_ma7 IS NOT NULL
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AND prev_ma7 > prev2_ma7 AND ma7 < prev_ma7 THEN 'DOWNWARD'
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ELSE NULL
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END AS turning_type
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FROM with_ma
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)
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SELECT
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metric_date,
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ROUND(hourly_efficiency, 2) AS daily_efficiency,
|
||
ROUND(ma7, 2) AS ma7_line,
|
||
turning_type,
|
||
CASE
|
||
WHEN turning_type = 'UPWARD' THEN 'MAINTAIN_CURRENT_MEASURES'
|
||
WHEN turning_type = 'DOWNWARD' THEN 'INVESTIGATE_AND_IMPROVE'
|
||
ELSE 'NONE'
|
||
END AS recommendation
|
||
FROM turning_points
|
||
WHERE turning_type IS NOT NULL
|
||
ORDER BY metric_date DESC
|
||
LIMIT 10;
|