---
title: "IRIS"
description: "IRIS (BMW Group, 2019/20): A clip-on camera and sensor kit lets planners diagnose machine errors remotely"
url: "https://www.sugar-network.org/en/projects/iris-2019-20/"
lang: "en"
---

# IRIS

**A clip-on camera and sensor kit lets planners diagnose machine errors remotely**

_Remote error diagnosis platform for a more connected working model._

- **Corporate partner:** [BMW Group](https://www.sugar-network.org/en/network/partners/bmw-group/) (https://www.bmwgroup.com/de.html)
- **Cohort:** [2019/20](https://www.sugar-network.org/en/projects/cohort/2019-20/)
- **Theme:** [Industry & operations](https://www.sugar-network.org/en/projects/themes/industry-operations/)
- **Type:** Platform
- **Projected:** 50 % Less time spent troubleshooting machines
- **Universities:** [University of St. Gallen](https://www.sugar-network.org/en/network/universities/hsg/), [Hasso Plattner Institute](https://www.sugar-network.org/en/network/universities/hpi/)
- **Team:** 7 master students
- **Disciplines:** Business Innovation, Cyber Security, Digital Health, IT Systems Engineering, Management

## Challenge

BMW Group wanted machine errors to be more visible and planning to become data-driven. Remote monitoring was largely manual, so planners often travelled to plants to inspect downtimes in person.

## What the team learned

Plants work autonomously without standard processes, so one tool for all would fail. BMW already owned strong software, unused for lack of reliable data, while a line stoppage costs around 17,000 euros per minute.

## What they built

IRIS is a portable kit of cameras and environmental sensors that fits on a machine within minutes. The PinIt tablet app marks defects on a 3D model, and a cloud dashboard sequences incidents. Machine learning flags anomalies and blurs people.

How it evolved:

1. Tested pointers, visualisation battles and boards: users preferred graphs over tables and zoomable detail levels.
2. BMW chose one movable kit that staff can attach within a 15-minute break.
3. A do-or-die workshop with BMW picked IRIS after 34 prototypes; the final one was tested in Dingolfing.

## Results

- On site in Dingolfing, cabling and network setup proved harder than expected.
- Testers asked for a live camera stream, flexible brackets, varied cable lengths and a heartbeat monitor.
- Projected: about 50 % less time on error analysis, an ROI above 100 % and break-even within a year.

## Impact

For BMW, IRIS promises lower travel costs and an up-to-date view of machine performance across plants. The team proposed a rollout led by a task force; adoption is not documented.

> The flexibility of IRIS is the biggest strength of the system!
>
> – BMW employee, on-site test in Dingolfing

## Full project text

IRIS is a remote error diagnosis platform that gives you real-time insights into industrial production errors, allowing you to identify and resolve incidents quickly and precisely.

### Challenge

In the context of Industry 4.0 and a more connected working model with IoT, BMW Group challenged the student team from the Hasso Plattner Institute and the University of St.Gallen with the following problem: enhance BMW Group to make machine errors more visible and bring planning processes to a data-driven working model. Particularly within remote machine monitoring, the planning and error-solving processes remain largely manual and lead to inefficiencies and high costs. In order to grasp the underlying errors of machine downtimes, a physical inspection is often necessary which requires the machine staff to frequently travel to the plants.

### Solution

IRIS is a flexible solution that bridges the gap between error-occurrence and error-analysis. A modular monitoring kit, consisting of cameras and environmental sensors, can be installed on a production machine within minutes, temporarily or permanently. In combination with a web-based application on a tablet, the error locations can be quickly identified. Error incidents are automatically sequenced and visualized in an intuitive dashboard, displaying all important metrics on a specific occurrence for evidence-based decision making. The Dashboard is accessible through the cloud.

### Impact

IRIS enables the planners and machine operators to have an always accessible and up-to-date picture of the machine performance across the global BMW network. This can save BMW approximately 50% of the time needed for troubleshooting their machines. The use of IRIS in more distant plants results in a significant reduction of travel costs for planning competencies, as they have the tools for remote error analysis.  
For BMW Group the implementation is very attractive with an ROI above 100% and a break-even in less than a year.

## Who built it.

- Moritz Blattner, Business Innovation (University of St. Gallen)
- Livia Keller, Management (University of St. Gallen)
- Pia Spori, Business Innovation (University of St. Gallen)
- Christian Reich, Business Innovation (University of St. Gallen)
- Marvin Thiele, IT Systems Engineering (Hasso Plattner Institute)
- Jonas Bücker, Cyber Security (Hasso Plattner Institute)
- Eugenia Alleva, Digital Health (Hasso Plattner Institute)

## Video

- IRIS: https://www.youtube.com/watch?v=5p4aCat0TjE

## Sources

Summarised by the SUGAR editorial team from the team’s project page, SUGAR Expo booklet, final documentation and team brochure.

Figures marked “Projected” are the team’s own estimates, not measured results.

Open the 2019/20 booklet: https://drive.google.com/file/d/1HRinlCvEZz5PSpew8VDcZzSIFRCUEvxc/view?usp=sharing