产品详细信息以英文显示。翻译即将推出。
速览
- 价格
- $799.00 USD
- dynamics_365_business_central 版本
- —
- 设置时间
- 45分钟
- 许可证
- 一次永久
- 语言
- 11 语言
一次性购买
Predictive Maintenance (AI)
A build-to-order Business Central AL extension that ingests machine sensor data, applies AI anomaly and failure-risk detection, and auto-creates predictive maintenance work orders before equipment fails. Installed as a per-tenant extension and supported by ECOSIRE.
$799.00USD
现在无需付款。此操作会向我们的团队发送报价请求——我们会通过邮件跟进价格和后续步骤。
核心功能
Sensor telemetry ingestion via the Business Central REST/OData v4 API or a customer push gateway into a dedicated AL readings table
Scheduled trend analysis and moving-window baselining driven by a Business Central Job Queue entry
AI/ML anomaly detection and failure-risk scoring via an external Azure Machine Learning or Azure OpenAI endpoint (model retrainable without AL changes)
Remaining-useful-life (RUL) estimation surfaced on asset and maintenance pages
Auto-created predictive maintenance work orders fired by AL event subscribers when a risk threshold is crossed
Downtime-vs-maintenance cost optimization that derives work-order priority from configurable cost parameters
Table and page extensions on item/asset and maintenance master data — no base-app modification
Configurable per-asset thresholds, sampling rates, and alert routing held in setup tables
Anomaly flags and trend charts rendered directly on Business Central pages with drill-down to raw readings
Dedicated permission set, audit logging, and clean per-tenant uninstall
Optional Dataverse / Power Platform integration to push alerts into Power Automate flows or Power BI
Telemetry and error logging for safe, observable Job Queue execution
关于此产品
Predictive Maintenance (AI) is a custom-built extension for Microsoft Dynamics 365 Business Central that turns raw machine sensor telemetry into proactive maintenance work orders — before a breakdown happens. ECOSIRE builds it, installs it as a per-tenant extension on your Business Central environment, and supports it. This is not an instant AppSource download; it is a scoped engagement delivered to fit your assets, sensor sources, and reliability workflow.
为什么选择 Predictive Maintenance (AI)
Sensor telemetry ingestion via the Business Central REST/OData v4 API or a customer push gateway into a dedicated AL readings table
Scheduled trend analysis and moving-window baselining driven by a Business Central Job Queue entry
AI/ML anomaly detection and failure-risk scoring via an external Azure Machine Learning or Azure OpenAI endpoint (model retrainable without AL changes)
Remaining-useful-life (RUL) estimation surfaced on asset and maintenance pages
Auto-created predictive maintenance work orders fired by AL event subscribers when a risk threshold is crossed
Downtime-vs-maintenance cost optimization that derives work-order priority from configurable cost parameters
The extension is written in AL and ships new tables plus table and page extensions on your maintenance and item/asset master data. Sensor readings arrive via the Business Central REST/OData v4 API (or a customer gateway pushing JSON) into a dedicated readings table. A Job Queue entry runs trend analysis and anomaly scoring on a schedule you define. Failure-risk and remaining-useful-life scoring is performed by an AI/ML model called over HTTPS — typically an Azure Machine Learning endpoint or Azure OpenAI / Dataverse + Power Platform AI service — so your model can be retrained without changing AL code.
When a machine crosses a risk threshold, an event subscriber auto-creates a predictive maintenance work order, populates the affected asset, suggested tasks, and a priority derived from a downtime-vs-maintenance cost comparison. Reliability engineers see trend charts, anomaly flags, and RUL estimates directly on Business Central pages, with drill-down to the underlying readings.
Everything ships with a dedicated permission set, telemetry-friendly logging, and clean uninstall. Because it is per-tenant, your customizations never collide with Microsoft's monthly updates, and ECOSIRE re-tests against each major BC release. You own the data; we own keeping it working.
你得到什么
- A per-tenant Business Central AL extension (.app) built to your assets and sensor sources, installed on your environment
- Scoping document mapping your equipment, sensor data shape, thresholds, and maintenance workflow to the AL design
- Sensor ingestion endpoint configuration (REST/OData or gateway) with sample payloads and a test harness
- AI/ML endpoint integration wired to your Azure ML, Azure OpenAI, or Dataverse model with a baseline model setup
- Dedicated permission set plus a Job Queue setup and runbook for scheduled scoring
- Admin and reliability-engineer documentation covering setup pages, thresholds, and work-order behavior
- Knowledge-transfer session and a defined warranty/support window with response-time commitments
这是给谁的
Reliability Engineer
Owns asset uptime at an asset-intensive plant and wants failure-risk signals and RUL estimates surfaced inside Business Central so predictive work orders are raised automatically instead of relying on calendar-based PM schedules.
Maintenance / Operations Manager
Needs to cut unplanned downtime and balance maintenance spend against failure cost. Uses the cost-optimization scoring to prioritize which auto-created work orders get crews first.
Business Central Administrator / IT Lead
Responsible for the BC environment and integrations. Cares that the solution is a clean per-tenant extension with a scoped permission set, observable Job Queue jobs, and no base-app modification that breaks Microsoft updates.
安装概述
从ECOSIRE下载
在 ecosire.com 上购买许可证并从您的帐户仪表板下载 Predictive Maintenance (AI) 模块 ZIP。
上传至Odoo
将 ZIP 解压到服务器上的 Odoo 自定义插件文件夹中（或通过“应用程序”>“从 Odoo.sh / runbot 上的文件安装”上传）。
安装模块
激活开发者模式，打开应用程序，单击更新应用程序列表，搜索 Predictive Maintenance (AI)，然后按安装。
配置设置
打开新菜单，粘贴您的 ECOSIRE 许可证密钥，连接任何外部凭据（Shopify、Amazon、Stripe 等），然后保存。
验证并上线
运行内置连接测试，同步前 10 条记录，并安排定期 cron。如果出现任何问题，请联系支持人员。
Predictive Maintenance (AI) 如何比较
| 标准 | 伊科西尔 | 定制建造 | 竞争对手 | 奥杜本机 |
|---|---|---|---|---|
| AI anomaly detection and failure-risk scoring built in | 包含 | 部分支持 | 部分支持 | |
| Auto-created predictive maintenance work orders from sensor thresholds | 包含 | 部分支持 | 部分支持 | |
| Remaining-useful-life (RUL) estimation surfaced in Business Central | 包含 | 部分支持 | 部分支持 | |
| Tailored to your specific assets, sensors, and maintenance workflow | 包含 | 包含 | 不包括在内 | |
| Delivered as a clean per-tenant extension (no base-app modification) | 包含 | 部分支持 | 包含 | |
| Built, installed, and supported for you with a defined SLA | 包含 | 不包括在内 | 部分支持 | |
| Sensor ingestion via BC REST/OData API or customer gateway | 包含 | 部分支持 | 部分支持 | |
| Model retrainable / swappable without AL code changes | 包含 | 部分支持 | 不包括在内 |
关于Predictive Maintenance (AI)的常见问题
Is this an instant AppSource download?
No. This is a build-to-order engagement. ECOSIRE builds the AL extension to fit your assets and sensor sources, then installs it as a per-tenant extension on your Business Central environment. There is no public AppSource listing or self-service download — you get a solution tailored to your reliability workflow and deployed for you.
How long does delivery take?
A typical build runs about 3 to 5 weeks after scoping sign-off, depending on the number of asset types, sensor data complexity, and which AI/ML endpoint you use. We start with a scoping document, build and test in a sandbox, then schedule the production install with you. The price covers the standard scope; unusual sensor protocols or many distinct asset models may extend the timeline, which we agree before starting.
What about ongoing support and updates?
Every build includes a warranty/support window with agreed response times. Because it is a per-tenant extension, ECOSIRE re-tests it against each major Business Central release and ships compatibility updates. Beyond the included window, we offer a support retainer covering bug fixes, threshold and model tuning, and adapting to new sensor sources or asset lines as your plant grows.
What sensor sources and AI models can you use?
Readings can arrive through the Business Central REST/OData v4 API or via a gateway that pushes JSON from your historian, IoT hub, or SCADA layer. The anomaly and RUL scoring runs on an external endpoint — commonly Azure Machine Learning, Azure OpenAI, or a Dataverse/Power Platform AI service — so you can retrain or swap the model without us rewriting AL code. We confirm the exact integration during scoping.
Will this interfere with Microsoft's Business Central updates?
No. The solution is delivered as a per-tenant extension using table extensions, page extensions, and event subscribers — it never modifies the base application. This is the supported customization model, so Microsoft's monthly and major updates apply normally. ECOSIRE validates the extension against each major release and provides any needed fixes.
相关模块
申请报价
Predictive Maintenance (AI)
A build-to-order Business Central AL extension that ingests machine sensor data, applies AI anomaly and failure-risk detection, and auto-creates predictive maintenance work orders before equipment fails. Installed as a per-tenant extension and supported by ECOSIRE.
- Sensor telemetry ingestion via the Business Central REST/OData v4 API or a customer push gateway into a dedicated AL readings table
- Scheduled trend analysis and moving-window baselining driven by a Business Central Job Queue entry
- AI/ML anomaly detection and failure-risk scoring via an external Azure Machine Learning or Azure OpenAI endpoint (model retrainable without AL changes)
- Remaining-useful-life (RUL) estimation surfaced on asset and maintenance pages