Project · 2019/202019/20Type: Platform

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 Visit website ↗Cohort 2019/20Theme Industry & operations

IRIS – BMW Group (2019/20)
Key fact
50 %ProjectedLess time spent troubleshooting machines
Team
7 master students
Universities
Disciplines
Business Innovation · Cyber Security · Digital Health · IT Systems Engineering · Management
The project · from brief to prototype

What happened, step by step.

01

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.

02

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.

03

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. Step 1Tested pointers, visualisation battles and boards: users preferred graphs over tables and zoomable detail levels.
  2. Step 2BMW chose one movable kit that staff can attach within a 15-minute break.
  3. Step 3A do-or-die workshop with BMW picked IRIS after 34 prototypes; the final one was tested in Dingolfing.
04

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.
  • Projectedabout 50 % less time on error analysis, an ROI above 100 % and break-even within a year.
05

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.

In their words

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

Full project text

The team’s original texts from the project page.

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.

Video

Watch the team’s pitch.

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Team · 7 students, 2 universities

Who built it.

Moritz Blattner
University of St. Gallen

Moritz Blattner

Business Innovation

Livia Keller
University of St. Gallen

Livia Keller

Management

Pia Spori
University of St. Gallen

Pia Spori

Business Innovation

Christian Reich
University of St. Gallen

Christian Reich

Business Innovation

Marvin Thiele
Hasso Plattner Institute

Marvin Thiele

IT Systems Engineering

Jonas Bücker
Hasso Plattner Institute

Jonas Bücker

Cyber Security

Eugenia Alleva
Hasso Plattner Institute

Eugenia Alleva

Digital Health