Sachsenmilch produces a variety of products from milk, butter, yogurt, cheese, anddairy derivatives for baby food to bioethanol in its state-of-the-art and almost fullyautomated facilities. Every day 4.7 million liters of fresh milk are delivered forprocessing, the equivalent of 170 truckloads. It’s essential for the company’sequipment to operate 24/7 and for the production facilities to be nearly 100 percentavailable..

萨克森牛奶公司在其现代化且几乎全自动的设施中生产各种产品，从牛奶、黄油、酸奶、奶酪和婴儿食品的乳制品衍生物到生物乙醇。每天有470万升的新鲜牛奶被运送过来进行加工，相当于170卡车的运量。公司的设备必须24/7全天候运行，生产设施几乎要达到100%的可用性。

Modern interconnected machines generate vast amounts of data

现代互联机器产生大量数据

The production environment at Sachsenmilch in Leppersdorf features moderninterconnected machines that generate large volumes of data – an ideal setting for apilot project using Senseye Predictive Maintenance, the advanced predictivemaintenance solution.

萨克森牛奶公司在莱珀斯多夫的生产环境拥有现代化的互联机器，这些机器产生大量数据——是使用Senseye预测性维护（先进的预测性维护解决方案）进行试点项目的理想环境。

Senseye Predictive Maintenance utilizes AI algorithms to identify both immediateand future machine issues, which allows proactive maintenance to be performedand prevents downtime. This capability has proven to be extremely valuable inSachsenmilch's heterogeneous production environment during the pilot project..

Senseye预测性维护利用人工智能算法识别设备的即时和未来问题，从而允许执行主动性维护并防止停机。在试点项目期间，这种能力在萨克森米尔希异构生产环境中已被证明极具价值。

One of the biggest challenges was analyzing relevant plant data like temperature,vibration levels, and frequencies to detect anomalies early on and draw the rightconclusions. The implementation process involved a careful analysis of specificfailure scenarios and the integration of existing data from the control system.

其中最大的挑战之一是分析相关的工厂数据，如温度、振动水平和频率，以早期发现异常并得出正确的结论。实施过程涉及对特定故障场景的仔细分析以及来自控制系统的现有数据的整合。

Newvibration sensors and the Siplus CMS 1200 measurement system for vibrationmonitoring were also installed..

还安装了新的振动传感器和用于振动监测的Siplus CMS 1200测量系统。

Siemens supported the maintenance team at Sachsenmilch with technical andproject management expertise. 'What we like about this project is that Siemens hasknow-how on both the technological and the technical sides as well as in projectmanagement,' said Roland Ziepel, Technical Manager and head of projectmanagement at Sachsenmilch in Leppersdorf.

西门子为萨克森米尔希的维修团队提供了技术和项目管理方面的专业知识支持。萨克森米尔希勒佩斯多夫分公司的技术经理兼项目管理主管罗兰·齐佩尔表示：“我们喜欢这个项目的原因在于，西门子在技术、工艺以及项目管理方面都具备专业知识。”

After being trained and the solution’simplementation, the Sachsenmilch team was able to independently continue andsuccessfully complete the pilot..

在培训和解决方案实施后，萨克森米尔希团队能够独立继续并成功完成试点项目。

Reduced downtime: Pump replacement pays off in the pilot project

减少停机时间：泵更换在试点项目中取得回报

The pilot with Senseye Predictive Maintenance has already achieved significant costsavings by reducing unplanned downtime. 'We can confirm that the pilot project with Senseye Predictive Maintenance has already paid off. Detecting a faulty pump at anearly stage saved us a lot of expense – in the low six figures,' Ziepel concluded..

Senseye预测性维护的试点项目已经通过减少计划外停机时间实现了显著的成本节约。Ziepel总结道：“我们可以确认，与Senseye预测性维护的试点项目已经取得了回报。及早发现一个故障泵为我们节省了大量开支——达到六位数的低位。”

'We’re pleased that with Senseye Predictive Maintenance, we were able tosuccessfully support Sachsenmilch in integrating a preventive maintenance strategyin its existing processes. This promotes efficiency and competitiveness inincreasingly complex industries. And the continuing development of our Maintenance Copilot Senseye is another significant step toward transformingmaintenance operations,' said Margherita Adragna, CEO of Customer Services atSiemens Digital Industries..

“我们很高兴通过Senseye预测性维护，成功支持了Sachsenmilch在其现有流程中整合预防性维护策略。这促进了在日益复杂的行业中的效率和竞争力。而我们的维护副驾Senseye的持续发展是转变维护操作的又一重要步骤。”西门子数字工业客户服务部首席执行官Margherita Adragna表示。

Sachsenmilch and Siemens plan their next project

萨克森牛奶和西门子计划他们的下一个项目

Building on this success, Sachsenmilch plans to further integrate Senseye Predictive Maintenance with their SAP Plant Maintenance System, with the goal of automatically transferring maintenance notifications from the Siemens solution to SAP Plant Maintenance to improve maintenance planning.

基于这一成功，萨克森牛奶公司计划进一步将 Senseye 预测性维护与其 SAP 植物维护系统集成，目标是自动将维护通知从西门子解决方案传输到 SAP 植物维护，以改进维护计划。

Example of the Senseye Predictive Maintenance user interface for the food and beverage industry (Source: Siemens AG)

食品饮料行业Senseye预测性维护用户界面示例（来源：西门子股份公司）

In addition, recommendations for data-driven maintenance provided by the Maintenance Copilot Senseye should also be increasingly utilized to help maintenance teams with their work. This is one of the ways that Siemens supports its customers in their innovative and integrated approach to maintenance in order to ensure their long-term operational success..

此外，应越来越多地利用Maintenance Copilot Senseye提供的数据驱动维护建议，以帮助维护团队开展工作。这是西门子支持客户以创新和集成方式实施维护的途径之一，旨在确保客户的长期运营成功。