> For the complete documentation index, see [llms.txt](https://docs.buildings.ability.abb/collection/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.buildings.ability.abb/collection/success-stories/predictive-maintenance-at-ew-sennwald.md).

# Predictive Maintenance at EW Sennwald

Accessible predictive-maintenance monitoring for hydropower and photovoltaic plants.

**Industry:** Energy and Utilities\
**Organization:** EW Sennwald\
**Location:** Sennwald, Switzerland\
**Year:** 2024

## At a Glance

| Measure             | Result                                                    |
| ------------------- | --------------------------------------------------------- |
| Plants connected    | Two hydropower plants and five photovoltaic systems       |
| Diagnostic values   | Five key signals monitored live                           |
| Detection           | A developing fault was identified before failure          |
| Operator experience | Daily operation does not require the specialist interface |

## Overview

EW Sennwald wanted to manage and monitor its energy production centrally. Specialist SRT Diagnostics software provides valuable predictive-maintenance information, but its complexity made it unsuitable for everyday operation and had contributed to incorrect handling.

## Implementation

Together with the diagnostic-system manufacturer, the five most important values were selected and integrated into BuildingPro Suites. Operators can review them in dashboards and monitor them with rules and alarms. Other plant sensors are integrated as well; for example, flow measurements can be reported automatically to the environmental authority.

The operations center also provides plant control without requiring users to enter the specialist diagnostic system.

## Proactive Maintenance Result

A technician observed a small increase in acceleration together with a general temperature decrease. This combination prompted an early inspection, helping avoid a possible malfunction or failure.

The project shows how a building and infrastructure platform can translate a small number of specialist diagnostic indicators into accessible dashboards and actionable rules. This supports proactive service while reducing the risk of incorrect interaction with complex expert software.

[-> \[External Link\] Read the complete success story](https://stage.advisor.buildings.ability.abb/success-stories/predictivemaintenance-ewsennwald)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.buildings.ability.abb/collection/success-stories/predictive-maintenance-at-ew-sennwald.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.