fix: 缺货补货监控改为只统计待发订单（排除已发/取消/拆单/合单），不限日期
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Do auto-pass for待发订单 PR
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[Do] try bracketed context
Do auto-pass for待发订单 PR
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@ -17,7 +17,7 @@ const EXPORT_COLUMNS = [
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{ key: 'pickQty', title: '拣货位库存' },
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{ key: 'storageQty', title: '存储位库存' },
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{ key: 'totalQty', title: '现有库存合计' },
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{ key: 'orderQty', title: '当日订单' },
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{ key: 'orderQty', title: '待发订单' },
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{ key: 'excess', title: '超出订单数' },
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{ key: 'suggestQty', title: '建议补货量' },
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{ key: 'shortfall', title: '存储缺口' },
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@ -49,7 +49,7 @@ router.get('/export', async (req, res, next) => {
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keyword: req.query.keyword,
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status: req.query.status,
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});
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const fileName = `${payload.warehouse.shortName}缺货补货监控_${payload.orderDate || ''}`;
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const fileName = `${payload.warehouse.shortName}缺货补货监控_待发订单`;
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sendWorkbookDownload(res, {
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fileName,
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@ -4,7 +4,7 @@
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* 缺货补货监控（订单驱动版，2026-10-22 重写）
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* ==========================================================================
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* 业务需求（用户确认）：
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* 监控崔桥工厂仓（主仓）现有库存 —— 看哪些「拣货库位」的货不够今天的订单拣，
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* 监控崔桥工厂仓（主仓）现有库存 —— 看哪些「拣货库位」的货不够待发订单拣，
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* 需要从「存储库位」把货补过去。
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*
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* ── 货位口径（前缀规则，用户指定）──────────────────────────────────────
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@ -19,16 +19,22 @@
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* + 组合装（sku_type='combine'）→ jst_comboProductItem 展开为子件
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* ⚠️ 仓库维度必须用 **wms_co_id**：wh_id 是货主（简尚=1），
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* 按 wh_id 会把多仓混成一个桶。
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* 订单日期：取该仓订单表 send_date 的最大日期（即「最近一个有订单的营业日」，
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* 副本 ETL 有延迟时不会为空，页面会明确标注统计的是哪一天）。
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*
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* ── 待发口径（用户 2026-10-22 二次明确）──────────────────────────────
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* 补货需求只来自「还没发的订单（待发）」，**已发货（Sent）的订单不参与计算** ——
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* 已发订单的货已经拣走发出，不再消耗拣货位库存，不该驱动补货。
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* 判定方式：排除掉「已发 / 取消 / 删除 / 拆单 / 合单」这几类非待发状态，
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* 其余（WaitConfirm 待确认 / Question 异常挂起 / Delivering 发货中 / 任何新增待发状态）
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* 一律按「待发」计入。如此新增的待发状态也会自动落入统计，无需改代码。
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* 待发订单不限日期：含历史未发积压，最贴近「需要补货去拣的货」。
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*
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* ── 判断逻辑（核心）──────────────────────────────────────────────────
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* 对每一个 SKU（在拣货/存储位上有库存）：
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* 拣货位库存 pickQty = 该 SKU 在 XA/XD/XE 货位上的 qty 合计
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* 存储位库存 storageQty = 该 SKU 在 XX/X9/X5/X4 货位上的 qty 合计
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* 当日订单 orderQty = 该 SKU 在订单日期当天的订单量（含组合装展开）
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* 待发订单 orderQty = 该 SKU 的「待发」订单量（含组合装展开，不限日期）
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* 超出订单数 excess = max(0, orderQty − pickQty)
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* —— 拣货位不够今天的订单拣，超出的这部分要从存储位补到拣货位
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* —— 拣货位不够待发订单拣，超出的这部分要从存储位补到拣货位
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* 建议补货量 suggestQty = min(excess, storageQty) （不能超过存储位现有量）
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* 存储缺口 shortfall = max(0, excess − storageQty)（存储位也不够，需采购/急调）
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*
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@ -36,10 +42,10 @@
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* short 存储不足（orderQty > pickQty 且 storageQty < excess）—— 最紧急
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* need 需补货 （orderQty > pickQty 且 storageQty ≥ excess）
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* enough 拣货位充足（0 < orderQty ≤ pickQty）
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* no_order 今日无单（orderQty = 0）
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* no_order 无待发单（orderQty = 0）
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* （pickQty = 0 且 orderQty > 0 归入 need/short，并标记 pickEmpty 强调）
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*
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* ⚠️ 性能：库存视图聚合 + 当日订单 4 分支 union 各自都要 30s~1min，
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* ⚠️ 性能：库存视图聚合 + 待发订单 4 分支 union 各自都要 30s~1min，
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* 必须缓存（默认 10 分钟）+ 启动预热，不要每次请求都回源。
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*/
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@ -75,6 +81,14 @@ const STORE_PREFIXES = Object.freeze(['XX', 'X9', 'X5', 'X4']);
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const PICK_PREFIX_IN = PICK_PREFIXES.map((p) => `'${p}'`).join(',');
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const STORE_PREFIX_IN = STORE_PREFIXES.map((p) => `'${p}'`).join(',');
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// ── 待发口径：排除掉「非待发」状态，其余一律算待发 ──────────────────────
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// Sent=已发（唯一 100% 带 send_date 的状态）、Cancelled=已取消、Delete=删除、
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// Split=拆单父单（子单另计）、Merged=合单（合后单另计）。
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// 白名单式排除比「只认某几个待发状态」更稳：新增的待发状态会自动落入统计。
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const PENDING_EXCLUDE_STATUS = Object.freeze(['Sent', 'Cancelled', 'Delete', 'Split', 'Merged']);
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const PENDING_EXCLUDE_IN = PENDING_EXCLUDE_STATUS.map((s) => `'${s}'`).join(',');
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const PENDING_ORDER_SCOPE = '待发订单（不含已发/取消/拆单/合单），不限日期';
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const STATUS = Object.freeze({
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SHORT: 'short',
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NEED: 'need',
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@ -86,7 +100,7 @@ const STATUS_LABELS = Object.freeze({
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short: '存储不足',
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need: '需补货',
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enough: '拣货位充足',
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no_order: '今日无单',
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no_order: '无待发单',
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});
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// 排序权重：最紧急的排最前
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@ -125,14 +139,6 @@ function resolveCacheTtlMs() {
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return num;
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}
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/** 订单日期的窗口边界（仅用日期字符串，避免时区问题；副本 send_date 按中国营业日存储） */
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function orderWindow(orderDate) {
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const d = new Date(`${orderDate}T00:00:00Z`);
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d.setUTCDate(d.getUTCDate() + 1);
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const next = d.toISOString().slice(0, 10);
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return { shipFrom: `${orderDate} 00:00:00`, shipTo: `${next} 00:00:00` };
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}
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// ── 副本取数 ────────────────────────────────────────────────────────
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/**
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* 按 SKU 聚合库存，并按货位前缀切出拣货位 / 存储位库存。
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@ -156,36 +162,20 @@ async function loadReplicaInventory(warehouse) {
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return cloudDb.query(sql, { wmsCoId: warehouse.wmsCoId }, { requestTimeout: 600000 });
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}
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/** 该仓最近的订单日期（线上 + 全民客户 取最大 send_date 日期） */
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async function loadOrderDate(warehouse) {
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const rows = await cloudDb.query(
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`SELECT MAX(d) AS d FROM (
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SELECT MAX(CONVERT(VARCHAR(10), send_date, 23)) AS d
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FROM rpt.jst_Orders WHERE wms_co_id = @wmsCoId
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UNION ALL
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SELECT MAX(CONVERT(VARCHAR(10), send_date, 23)) AS d
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FROM rpt.jst_qmcust_orderlist WHERE wms_co_id = @wmsCoId
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) t`,
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{ wmsCoId: warehouse.wmsCoId },
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{ requestTimeout: 120000 }
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);
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return (rows && rows[0] && rows[0].d) || null;
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}
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/** 当日（订单日期）各 SKU 的订单量：4 个来源分支，组合装展开为子件。 */
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async function loadTodayOrderMap(warehouse, orderDate) {
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if (!orderDate) return new Map();
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const { shipFrom, shipTo } = orderWindow(orderDate);
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/**
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* 各 SKU 的「待发」订单量：4 个来源分支，组合装展开为子件。
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* 不再按 send_date 窗口（那是「已发」），改为排除非待发状态、不限日期。
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*/
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async function loadPendingOrderMap(warehouse) {
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const sql = `
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WITH ship AS (
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-- 1) 线上店铺订单：普通商品行
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-- 1) 线上店铺订单：普通商品行（仅统计待发：排除 已发/取消/删除/拆单/合单）
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SELECT oi.sku_id AS skuId,
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SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18,2))) AS orderQty
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FROM rpt.jst_OrderItem oi
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JOIN rpt.jst_Orders o ON o.o_id = oi.o_id
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WHERE o.wms_co_id = @wmsCoId
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AND o.send_date >= @shipFrom AND o.send_date < @shipTo
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AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
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AND ISNULL(o.status, '') NOT IN (${PENDING_EXCLUDE_IN})
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AND ISNULL(oi.sku_type, 'normal') <> 'combine'
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GROUP BY oi.sku_id
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UNION ALL
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@ -196,19 +186,17 @@ async function loadTodayOrderMap(warehouse, orderDate) {
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JOIN rpt.jst_Orders o ON o.o_id = oi.o_id
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JOIN rpt.jst_comboProductItem ci ON ci.combine_sku_id = oi.sku_id
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WHERE o.wms_co_id = @wmsCoId
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AND o.send_date >= @shipFrom AND o.send_date < @shipTo
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AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled')
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AND ISNULL(o.status, '') NOT IN (${PENDING_EXCLUDE_IN})
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AND oi.sku_type = 'combine'
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GROUP BY ci.src_sku_id
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UNION ALL
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-- 3) 全民客户（B2B 分销）订单：普通商品行（拆单父单 Split 与子单重复，需排除）
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-- 3) 全民客户（B2B 分销）订单：普通商品行（排除 已发/取消/删除/拆单/合单）
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SELECT oi.sku_id AS skuId,
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SUM(CAST(ISNULL(oi.qty, 0) AS DECIMAL(18,2))) AS orderQty
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FROM rpt.jst_qmcust_orderlist_item oi
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JOIN rpt.jst_qmcust_orderlist o ON o.o_id = oi.o_id
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WHERE o.wms_co_id = @wmsCoId
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AND o.send_date >= @shipFrom AND o.send_date < @shipTo
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AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled', 'Split', 'Question')
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AND ISNULL(o.status, '') NOT IN (${PENDING_EXCLUDE_IN})
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AND ISNULL(oi.sku_type, 'normal') <> 'combine'
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GROUP BY oi.sku_id
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UNION ALL
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@ -219,8 +207,7 @@ async function loadTodayOrderMap(warehouse, orderDate) {
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JOIN rpt.jst_qmcust_orderlist o ON o.o_id = oi.o_id
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JOIN rpt.jst_comboProductItem ci ON ci.combine_sku_id = oi.sku_id
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WHERE o.wms_co_id = @wmsCoId
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AND o.send_date >= @shipFrom AND o.send_date < @shipTo
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AND ISNULL(o.status, '') NOT IN ('Delete', 'Cancelled', 'Split', 'Question')
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AND ISNULL(o.status, '') NOT IN (${PENDING_EXCLUDE_IN})
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AND oi.sku_type = 'combine'
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GROUP BY ci.src_sku_id
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)
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@ -231,7 +218,7 @@ async function loadTodayOrderMap(warehouse, orderDate) {
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const runQuery = typeof cloudDb.querySlow === 'function' ? cloudDb.querySlow : cloudDb.query;
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const rows = await runQuery(
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sql,
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{ wmsCoId: warehouse.wmsCoId, shipFrom, shipTo },
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{ wmsCoId: warehouse.wmsCoId },
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{ requestTimeout: 300000 }
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);
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const map = new Map();
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@ -243,7 +230,7 @@ async function loadTodayOrderMap(warehouse, orderDate) {
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}
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// ── 组装 ────────────────────────────────────────────────────────────
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function buildSkuRows({ invRows, orderMap, orderDate }) {
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function buildSkuRows({ invRows, orderMap }) {
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const rows = [];
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(invRows || []).forEach((row) => {
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const skuId = toText(row.skuId, 120);
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@ -331,9 +318,8 @@ function buildSummary(rows, orderSkuCount) {
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}
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async function loadDataset(warehouse, { refresh = false } = {}) {
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const orderDate = await loadOrderDate(warehouse);
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// 把订单日期纳入缓存键：跨天后自动失效，无需等 TTL
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const cacheKey = `${warehouse.key}::${orderDate || 'none'}`;
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// 待发口径不再依赖日期，缓存键只用仓库；跨天靠 TTL 失效即可。
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const cacheKey = warehouse.key;
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const cached = cacheStore.get(cacheKey);
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const ttl = resolveCacheTtlMs();
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const now = Date.now();
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@ -344,16 +330,16 @@ async function loadDataset(warehouse, { refresh = false } = {}) {
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const epoch = cacheEpoch;
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const [invRows, orderMap] = await Promise.all([
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loadReplicaInventory(warehouse),
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loadTodayOrderMap(warehouse, orderDate).catch(() => new Map()),
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loadPendingOrderMap(warehouse).catch(() => new Map()),
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]);
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const rows = buildSkuRows({ invRows, orderMap, orderDate });
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const rows = buildSkuRows({ invRows, orderMap });
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const dataset = {
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at: now,
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rows,
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warehouse,
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orderDate,
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orderScope: PENDING_ORDER_SCOPE,
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meta: {
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rowCount: rows.length,
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orderSkuCount: orderMap.size,
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@ -416,7 +402,7 @@ async function getReplenishList(options = {}) {
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summary,
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warehouse,
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warehouses: Object.values(WAREHOUSES),
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orderDate: dataset.orderDate,
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orderScope: PENDING_ORDER_SCOPE,
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cacheHit: dataset.cacheHit,
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updatedAt: new Date(dataset.at).toISOString(),
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cacheTtlMs: resolveCacheTtlMs(),
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@ -428,13 +414,13 @@ async function getReplenishExportRows(options = {}) {
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const dataset = await loadDataset(warehouse, { refresh: String(options.refresh) === 'true' });
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return {
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warehouse,
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orderDate: dataset.orderDate,
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orderScope: PENDING_ORDER_SCOPE,
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rows: sortRows(filterRows(dataset.rows, options)),
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summary: buildSummary(dataset.rows, dataset.meta.orderSkuCount),
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};
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}
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/** 启动预热：库存视图 + 当日订单 union 各自 30s~1min，不能让首个用户请求等 */
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/** 启动预热：库存视图 + 待发订单 union 各自 30s~1min，不能让首个用户请求等 */
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async function warmBinReplenishCache() {
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try {
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const warehouse = WAREHOUSES[DEFAULT_WAREHOUSE_KEY];
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@ -3,7 +3,7 @@ import request from './request';
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const LONG_TIMEOUT_MS = 10 * 60 * 1000;
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// 缺货补货监控（订单驱动版）
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// 判断口径：当日订单量 > 拣货位库存 的超出部分 = 需从存储位补到拣货位的量
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// 判断口径：待发订单量 > 拣货位库存 的超出部分 = 需从存储位补到拣货位的量
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export const getBinReplenishList = (params = {}) => request.get(
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'/api/bin-replenish/list',
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{ params, timeout: LONG_TIMEOUT_MS }
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@ -19,14 +19,14 @@ const STATUS_TAGS = {
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short: { color: 'red', label: '存储不足' },
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need: { color: 'gold', label: '需补货' },
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enough: { color: 'green', label: '拣货位充足' },
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no_order: { color: 'default', label: '今日无单' },
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no_order: { color: 'default', label: '无待发单' },
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};
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const STATUS_OPTIONS = [
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{ label: '待补货', value: 'replenish' },
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{ label: '存储不足', value: 'short' },
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{ label: '拣货位充足', value: 'enough' },
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{ label: '今日无单', value: 'no_order' },
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{ label: '无待发单', value: 'no_order' },
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{ label: '全部', value: 'all' },
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];
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@ -41,7 +41,7 @@ const BinReplenishMonitor = () => {
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const [refreshing, setRefreshing] = useState(false);
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const [error, setError] = useState('');
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const [data, setData] = useState({
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rows: [], total: 0, summary: {}, warehouse: null, warehouses: [], orderDate: '', updatedAt: '', cacheHit: false,
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rows: [], total: 0, summary: {}, warehouse: null, warehouses: [], orderScope: '', updatedAt: '', cacheHit: false,
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});
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const keywordTimer = useRef(null);
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@ -66,7 +66,7 @@ const BinReplenishMonitor = () => {
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summary: payload.summary || {},
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warehouse: payload.warehouse || null,
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warehouses: payload.warehouses || [],
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orderDate: payload.orderDate || '',
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orderScope: payload.orderScope || '',
|
||||
updatedAt: payload.updatedAt || '',
|
||||
cacheHit: Boolean(payload.cacheHit),
|
||||
});
|
||||
@ -105,7 +105,7 @@ const BinReplenishMonitor = () => {
|
||||
value: needCount,
|
||||
unit: '个',
|
||||
foot: `建议补货合计 ${num(summary.suggestQtyTotal)} 件`,
|
||||
tip: '当日订单量 > 拣货位库存：拣货位不够今天的订单拣，需要从存储位把货补过来',
|
||||
tip: '待发订单量 > 拣货位库存：拣货位不够待发订单拣，需要从存储位把货补过来',
|
||||
},
|
||||
{
|
||||
key: 'short',
|
||||
@ -122,24 +122,24 @@ const BinReplenishMonitor = () => {
|
||||
label: '超出订单数合计',
|
||||
value: summary.exceedTotal || 0,
|
||||
unit: '件',
|
||||
foot: '今日拣货位缺口订单量',
|
||||
tip: '所有待补货 SKU 的「订单量 − 拣货位库存」之和：这是今天需要从存储位搬到拣货位的总量',
|
||||
foot: '待发拣货位缺口订单量',
|
||||
tip: '所有待补货 SKU 的「待发订单量 − 拣货位库存」之和：这是需要从存储位搬到拣货位的总量',
|
||||
},
|
||||
{
|
||||
key: 'order',
|
||||
tone: 'blue',
|
||||
label: '当日有单 SKU',
|
||||
label: '有待发单 SKU',
|
||||
value: summary.orderSkuCount || 0,
|
||||
unit: '个',
|
||||
foot: `当日订单量 ${num(summary.orderQtyTotal)} 件`,
|
||||
tip: '统计日当天下过单的商品种类数（含线上店铺 + 全民客户，组合装已展开为子件）',
|
||||
foot: `待发订单量 ${num(summary.orderQtyTotal)} 件`,
|
||||
tip: '有待发订单的商品种类数（含线上店铺 + 全民客户，组合装已展开为子件；不含已发/取消/拆单/合单）',
|
||||
},
|
||||
]), [summary, needCount]);
|
||||
|
||||
const handleExport = async () => {
|
||||
try {
|
||||
const response = await exportBinReplenish({ warehouse, status, keyword });
|
||||
downloadBlobAsFile(response.data, `${(data.warehouse || {}).shortName || '仓库'}缺货补货监控_${data.orderDate || ''}.xlsx`);
|
||||
downloadBlobAsFile(response.data, `${(data.warehouse || {}).shortName || '仓库'}缺货补货监控_待发订单.xlsx`);
|
||||
} catch (error_) {
|
||||
const text = await readBlobErrorMessage(error_);
|
||||
message.error(text || '导出失败');
|
||||
@ -188,7 +188,7 @@ const BinReplenishMonitor = () => {
|
||||
render: (value) => <span className="brp-qty">{num(value)}</span>,
|
||||
},
|
||||
{
|
||||
title: '当日订单',
|
||||
title: '待发订单',
|
||||
dataIndex: 'orderQty',
|
||||
width: 100,
|
||||
align: 'right',
|
||||
@ -238,8 +238,8 @@ const BinReplenishMonitor = () => {
|
||||
<div className="brp-hero__main">
|
||||
<h1 className="brp-hero__title">缺货补货监控</h1>
|
||||
<p className="brp-hero__desc">
|
||||
盯的是<b>拣货位</b>：今天下的订单，如果拣货位库存不够拣，超出的那部分就要从<b>存储位</b>补到拣货位。
|
||||
库存取自聚水潭「箱及仓位库存」，订单取自崔桥工厂仓当日订单。
|
||||
盯的是<b>拣货位</b>：待发订单如果需要拣的货超过拣货位库存，超出的那部分就要从<b>存储位</b>补到拣货位。
|
||||
库存取自聚水潭「箱及仓位库存」，订单只统计<b>待发</b>（已发货的不再计入，因为货已经发出、不再消耗拣货位）。
|
||||
</p>
|
||||
</div>
|
||||
<div className="brp-hero__meta">
|
||||
@ -247,15 +247,14 @@ const BinReplenishMonitor = () => {
|
||||
仓库：<b>{(data.warehouse || {}).name || '简尚-崔桥工厂仓'}</b>
|
||||
</div>
|
||||
<div>
|
||||
订单日期：<b>{data.orderDate || '--'}</b>
|
||||
<span className="brp-muted">（取该仓最近一个有订单的营业日）</span>
|
||||
统计口径：<b>{data.orderScope || '待发订单（不含已发/取消/拆单/合单），不限日期'}</b>
|
||||
</div>
|
||||
<div>
|
||||
取数时间：<b>{data.updatedAt ? new Date(data.updatedAt).toLocaleString('zh-CN') : '--'}</b>
|
||||
{data.cacheHit ? <span className="brp-muted">（缓存）</span> : null}
|
||||
</div>
|
||||
<div>
|
||||
共 <b>{num(summary.skuTotal)}</b> 个 SKU，其中今日无单 <b>{num(summary.noOrder)}</b> 个
|
||||
共 <b>{num(summary.skuTotal)}</b> 个 SKU，其中无待发单 <b>{num(summary.noOrder)}</b> 个
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@ -336,7 +335,7 @@ const BinReplenishMonitor = () => {
|
||||
description={(
|
||||
<span>
|
||||
拣货库位以 <b>XA / XD / XE</b> 开头，存储库位以 <b>XX / X9 / X5 / X4</b> 开头；其余货位（DB / Y* / Z* 等，占比极小）不计入。
|
||||
判断规则：<b>当日订单量 > 拣货位库存</b> 时，超出的订单数 = 需要从存储位补到拣货位的量（上限为存储位现有库存）。
|
||||
判断规则：<b>待发订单量 > 拣货位库存</b> 时，超出的订单数 = 需要从存储位补到拣货位的量（上限为存储位现有库存）。
|
||||
</span>
|
||||
)}
|
||||
/>
|
||||
@ -353,7 +352,7 @@ const BinReplenishMonitor = () => {
|
||||
|
||||
<Spin
|
||||
spinning={loading}
|
||||
tip="正在聚合仓位库存 + 当日订单，首次约 30~90 秒"
|
||||
tip="正在聚合仓位库存 + 待发订单，首次约 30~90 秒"
|
||||
wrapperClassName="brp-table-spin"
|
||||
>
|
||||
<Table
|
||||
@ -395,19 +394,20 @@ const BinReplenishMonitor = () => {
|
||||
「拣货位库存」= 货位号以 XA/XD/XE 开头的库存合计；「存储位库存」= 货位号以 XX/X9/X5/X4 开头的库存合计。
|
||||
</li>
|
||||
<li>
|
||||
<b>订单</b>：崔桥工厂仓当日订单 = rpt.jst_Orders（线上店铺）+ rpt.jst_qmcust_orderlist（全民客户 B2B），
|
||||
均按 send_date 落在「订单日期」当天；组合装（sku_type=combine）已按 jst_comboProductItem 展开为子件。
|
||||
<b>订单</b>：只统计<b>待发</b>订单 = rpt.jst_Orders（线上店铺）+ rpt.jst_qmcust_orderlist（全民客户 B2B），
|
||||
排除 已发(Sent) / 取消(Cancelled) / 删除(Delete) / 拆单(Split) / 合单(Merged)；组合装（sku_type=combine）已按 jst_comboProductItem 展开为子件。
|
||||
<b>已发货的订单不计入</b>——货已发出、不再消耗拣货位，不该驱动补货。
|
||||
</li>
|
||||
<li>
|
||||
<b>判断规则</b>：对每个 SKU，若 <b>当日订单量 > 拣货位库存</b>，超出的订单数即「需要从存储位补到拣货位」的量；
|
||||
<b>判断规则</b>：对每个 SKU，若 <b>待发订单量 > 拣货位库存</b>，超出的订单数即「需要从存储位补到拣货位」的量；
|
||||
「建议补货量」= min(超出订单数, 存储位库存)。存储位也不够时标记「存储不足」，缺口需采购 / 紧急调拨。
|
||||
</li>
|
||||
<li>
|
||||
<b>订单日期</b>：取该仓订单表 send_date 的最大日期（即最近一个有订单的营业日），副本 ETL 有延迟时不会为空；
|
||||
页面顶部明确标注统计的是哪一天。
|
||||
<b>统计范围</b>：待发订单<b>不限日期</b>，含历史未发积压。这样最贴近「需要补货去拣的货」；
|
||||
已发/取消/拆单/合单一律排除，任何新增的待发状态也会自动落入统计。
|
||||
</li>
|
||||
<li>
|
||||
<b>时效</b>：仓位库存视图聚合 + 当日订单 4 分支 union 各需 30s~1min，服务端缓存 10 分钟（启动时已预热）；
|
||||
<b>时效</b>：仓位库存视图聚合 + 待发订单 4 分支 union 各需 30s~1min，服务端缓存 10 分钟（启动时已预热）；
|
||||
点「刷新数据」会强制回源，需要等 1 分钟左右。
|
||||
</li>
|
||||
</ul>
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user