示意预览Build-to-order Odoo module that auto-calculates OEE (Availability × Performance × Quality) per work center with
live downtime tracking and loss analysis.
什么是 Odoo OEE & Work Center Performance Monitor？
Build-to-order Odoo module that auto-calculates OEE (Availability × Performance × Quality) per work center with live downtime tracking and loss analysis. Built to order by ECOSIRE for Odoo 17, 18, 19 — indicative price from $999.00 USD; request a quote for a scoped proposal.
核心功能
按需定制，全程代劳
无需自行搭建——由 ECOSIRE 构建、安装并提供支持的可用应用。
- 1
您下单
以一次性构建价格开始。我们在启动时与您共同确定范围。
- 2
我们构建与安装
ECOSIRE 在您的 Odoo 上构建、配置并安装。
- 3
上线 + 支持
约一个工作周内上线，并包含两周上线支持。我们交付的代码中的缺陷免费修复。
技术规格
- Odoo 兼容性
- Odoo 17, Odoo 18, Odoo 19
- 版本
- 企业版和社区版
- 许可证
- 许可证需要确认
- Python 要求
- Python 3.10+
- 数据库
- PostgreSQL 12+
关于此产品
Odoo's core Manufacturing app tells you what was produced — it doesn't tell you how efficiently your equipment ran. The OEE & Work Center Performance Monitor is a build-to-order module that ECOSIRE designs, develops, installs, and supports specifically for your plant. It computes Overall Equipment Effectiveness — the classic Availability × Performance × Quality formula — automatically for every work center and machine, straight from your existing mrp.workorder, mrp.workcenter, and mrp.workcenter.productivity records, so you get a true, defensible efficiency number instead of a spreadsheet guess.
Under the hood this is a proper Odoo addon: a clean __manifest__.py declaring dependencies on mrp (plus quality where Enterprise is available), new models.Model classes such as ecosire.oee.line and ecosire.downtime.reason with stored, indexed compute fields (availability, performance, quality, oee — each defined with @api.depends so Odoo recomputes them the instant an underlying value changes). Loss reasons extend the standard mrp.workcenter.productivity.loss records and map cleanly onto the six big losses. Access is locked down with ir.model.access.csv and record rules so operators can log downtime but only managers can edit OEE targets or reason master data. Reporting is delivered through list, pivot, graph, and OWL dashboard views, with QWeb PDF reports for shift and management review, and everything is reachable over XML-RPC / JSON-RPC for BI tools or a plant-floor MES.
Because it's built for you, availability is genuinely accurate: the module reads each work center's working calendar and shift pattern, subtracts only planned stops, and treats unplanned stops as real downtime — no more counting scheduled breaks as losses. Automated actions (Odoo base.automation) can flag a work center the moment its rolling OEE drops below your configured target, escalate a recurring breakdown, or push a discrepancy to the responsible engineer. The result is a live, drill-down picture of where your throughput is actually leaking — by line, product, shift, and operator — and a categorized loss backlog your team can attack with real Pareto data.
Delivered for Odoo 17, 18, and 19 (Community and Enterprise), tuned to your work-center layout and loss taxonomy, with source code, documentation, and a training + support window included. This is a bespoke engagement with a typical one working week build-and-install lead time — not an instant download.
你得到什么
- Complete, installable Odoo module (source code) packaged for your Odoo 17, 18, or 19 database — Community or Enterprise — with clean __manifest__.py, models, security, views, and QWeb reports
- Configured loss taxonomy and OEE targets: your six-big-losses reason tree, ideal cycle times, and per-work-center target lines set up against your real routings
- OWL dashboards and pivot/graph reports plus PDF shift and management OEE reports, tailored to your line/product/operator structure
- Data-integration hooks: XML-RPC/JSON-RPC access documented, optional scheduled rollup jobs, and a mapping spec if you plan to feed an external BI/MES tool
- Technical and user documentation — architecture notes, model/field reference, security matrix, and a step-by-step operator guide for logging downtime
- Live training session(s) for plant managers, supervisors, and operators, recorded for onboarding future staff
- Deployment to your staging then production environment with an upgrade/migration path and a rollback plan
- A defined post-go-live support and warranty window covering bug fixes and minor adjustments after acceptance
这是给谁的
Plant / Production Manager
Owns line efficiency and throughput targets. Needs one trustworthy OEE number per work center and shift — sourced from Odoo, not a manual spreadsheet — with drill-down into the losses dragging output down and alerts when a line slips below target.
Production / Manufacturing Engineer
Runs continuous-improvement and Kaizen. Wants clean six-big-losses data and Pareto charts to prioritize the vital-few downtime causes, plus accurate ideal-cycle-time and speed-loss figures to justify capex and process changes.
Maintenance / Reliability Lead
Cares about breakdown and setup losses. Uses categorized downtime capture and automated escalations to spot recurring machine failures, tie them to maintenance activities, and prove the reliability impact on availability.
Operations Director / COO
Tracks efficiency across multiple lines or plants. Needs period-over-period OEE trends and management PDF reports, and wants the metric feeding the wider BI stack over XML-RPC/JSON-RPC for board-level reporting.
Odoo OEE & Work Center Performance Monitor 如何比较
| 标准 | 伊科西尔 | 定制建造 | 竞争对手 | Odoo 原生 |
|---|---|---|---|---|
| True OEE = Availability × Performance × Quality, auto-calculated | 包含 | 部分支持 | 部分支持 | 不包括在内 |
| Fits your exact work-center layout, shifts & loss taxonomy | 包含 | 包含 | 不包括在内 | 不包括在内 |
| Six-big-losses categorization with Pareto analysis | 包含 | 部分支持 | 部分支持 | 不包括在内 |
| Shift/calendar-aware availability (planned vs unplanned stops) | 包含 | 部分支持 | 不包括在内 | 不包括在内 |
| Configurable OEE targets with automated below-target alerts | 包含 | 部分支持 | 不包括在内 | 不包括在内 |
| Delivered, installed & supported for Odoo 17/18/19 by the builder | 包含 | 部分支持 | 不包括在内 | 不包括在内 |
| XML-RPC/JSON-RPC feed to Power BI / MES with scheduled rollups | 包含 | 部分支持 | 部分支持 | 部分支持 |
| Role-based security (operators log, managers set targets) | 包含 | 部分支持 | 部分支持 | 部分支持 |
| Full source code ownership & migration path across versions | 包含 | 包含 | 不包括在内 | 包含 |
关于Odoo OEE & Work Center Performance Monitor的常见问题
How long until the module is delivered and installed?
This is a build-to-order engagement, not an instant download. Typical lead time is one working week from a confirmed scope: we begin with a short discovery on your work-center layout, shift calendars, routings, and loss taxonomy, then build against your Odoo version, deliver to staging for your sign-off, and deploy to production. Timeline scales with the number of lines and any external BI/MES integration; we confirm dates in writing before starting.
How are support and updates handled after go-live?
Every engagement includes a defined post-go-live support and warranty window covering bug fixes and minor adjustments after acceptance. You receive the full module source code, so nothing is locked. When you upgrade Odoo (for example 18 to 19) we provide a migration path, and ongoing support or an annual maintenance retainer for enhancements and new-version compatibility is available on request.
Does this work with Odoo Community, or only Enterprise?
Both. The module depends on the standard mrp (Manufacturing) app, which exists in Community and Enterprise, and is delivered for Odoo 17, 18, and 19. On Enterprise we can additionally source the Quality factor from Odoo Quality checks and integrate with Maintenance; on Community we derive quality from scrap/rework quantities. We tailor the build to your exact edition and version.
Where does the OEE data actually come from — do operators have to enter it twice?
No double entry. The module reads your existing manufacturing transactions: work orders (mrp.workorder), work-center productivity/time logs (mrp.workcenter.productivity), scrap, and calendars. Operators only add value where Odoo doesn't already know something — for example picking a structured downtime reason when a stop occurs. Availability, performance, and quality are then computed automatically as @api.depends fields.
Can we feed the OEE numbers into Power BI or another external system?
Yes. All OEE and loss models are exposed over Odoo's XML-RPC and JSON-RPC APIs, and we can add scheduled ir.cron rollup tables so dashboards stay fast. We document the field mappings and, if needed, help wire the feed into Power BI, Grafana, or a plant-floor MES as part of the deliverables.
How is access controlled so operators can't change targets or fudge numbers?
Security is enforced with ir.model.access.csv and record rules. Operators can log downtime and reasons but cannot edit OEE targets, ideal cycle times, or loss master data — those are restricted to supervisor/manager groups. This keeps the metric auditable and consistent across shifts and plants.
相关模块
Odoo OEE & Work Center Performance Monitor
Build-to-order Odoo module that auto-calculates OEE (Availability × Performance × Quality) per work center with live downtime tracking and loss analysis.
- Automatic OEE calculation (Availability × Performance × Quality) per work center and per machine, stored as @api.depends compute fields so numbers refresh the moment a work order or downtime record changes
- Six-big-losses categorization — breakdown, setup/adjustment, idling/micro-stops, reduced speed, defects/rework, and startup/yield — mapped onto extended mrp.workcenter.productivity.loss records
- Structured downtime and blocked-reason capture from the work-order screen, with a reason tree operators pick from and mandatory notes for major stops
- Shift- and calendar-aware availability that reads each work center's resource.calendar, subtracts only planned stops, and never counts scheduled breaks as loss