Projects

Initial situation, challenge & solution

• Over 30 external locations (mostly individual buildings spread across Berlin) have to be monitored by the maintenance team.
• There are only collective fault reports without further details on the severity, so that for every report a technician travels through Berlin to the external site at any time to carry out a manual check.
• Thanks to our built-in sensor technology and connection of machine control systems (including gas, water, heat pumps, BMS, humidity and temperature), the technicians now receive automated, dedicated fault messages and decide whether an ad-hoc intervention is necessary or whether the activities can be carried out as part of planned maintenance.

Initial situation, challenge & solution

• Legally imposed documentation obligations take up a lot of time. The digitalisation and automation of business processes is an excellent solution for relieving the burden on employees, especially at a time when there is a shortage of skilled workers in the care sector.
• The temperature of medicine refrigerators must be checked and documented at regular intervals. This is done manually by visual inspection of the thermometer and handwritten documentation in a list.
• Thanks to our built-in sensors and connection to our AiFO solution, no manual checking and recording is necessary.
• The values, including the entire history, are available to the auditors at the touch of a button.

Initial situation, challenge & solution

• Our customer wants seamless networking between the areas of production preparation and production.
• Instead of an MES system, they want a direct connection between SAP and the machine.
• Using the Tomorrow Labs expert modules SAP Connector and MTConnect Connector, which we installed on a so-called edge device (industrial-grade mini PC), the bilateral exchange between SAP and the machine was made possible.
• An order is delivered to the machine and the data previously agreed with the customer is assigned directly to the respective order and a partial selection is displayed in SAP, e.g. processing status.
• In addition to the obvious process optimisation through direct data exchange between SAP and the machine, the data obtained is used to train predictive models (AI) to optimise usage and maintenance.

Initial situation, challenge & solution

• Wittenstein would like to measure and improve machine performance. To do this, you want to use the OEE (Overall Equipment Effectiveness) as a key figure.
• Our customer has a highly heterogeneous machine landscape, i.e. data from different machine and control system manufacturers must be merged and analysed. Other platforms such as Mindsphere from Siemens do not offer these possibilities.
• 26 machines have been connected to date via our Tomorrow Labs expert modules. Our proprietary S7 connector, MTConnect, OPC-UA connector and our OPC-UA server were used - the latter transforms the S7 protocol into OPC-UA for further use, among other things.
• We held an initial workshop and accompanied the roll-out for 12 months.

Initial situation, challenge & solution

• Our customer mainly produces heaters at its Berlin site. Presses and welding robots from various manufacturers are used for this purpose.
• The customer's goal is to transport and visualise the 'actual state' from the shop floor to the top floor. In addition, critical machines, such as selected welding robots (which run 24/7), should be monitored.
• We used Siemens connectors, our Modbus connector, the OPC UA transformer and various visualisation components from our Tomorrow Labs expert kit to provide the required information directly on the shop floor, i.e. at the machines, and in a management dashboard.
• In the event of deviations from the specifications or error messages from the machines, the relevant persons are notified immediately.

Initial situation, challenge & solution

• Caverion monitors various sprinkler systems for its customer.
• The monitoring and testing tasks are precisely specified. A continuous visual inspection of the pressure gauges and controller positions are part of this.
• It should be checked which technology can be used for monitoring in order to subsequently carry out a profitability analysis.
• After selecting a suitable infrared camera, various ML and AI models (openCV and Tensorflow) were evaluated - including those we developed ourselves, which are already used to read water meters.

Initial situation, challenge & solution

• Kaspersky developed a cyber defence that enables direct monitoring of production facilities at control level. This solution was developed after the attack (Stuxnet attack) on the Iranian nuclear power plant was publicised.
• Together with the developers of the KICS (Kaspersky Industrial CyberSecurity) solution, we carried out the commissioning at our customer AGC Glass in Germany.
• Download Use Case: https://media.kaspersky.com/en/business-security/enterprise/kaspersky-case-study-agc-germany-english.pdf

Initial situation, challenge & solution

• Our customer had outsourced the entire development to India. As a result, their cloud solution did not meet the usual market standards in terms of performance and security, which meant that potential customers such as the Metro Group could not be convinced.
• The customer was looking for a service provider who could design and develop a cloud-native solution.
• With the help of our Tomorrow Labs Libraries, we developed a solution within 12 months that was so variable and performant that customers such as Heineken, Allianz, Toyota USA and ultimately the Metro Group were convinced of the technical and user benefits of the software.
• We supported the solution for a further 12 months. During this period, we built up internal resources for the customer in Germany and handed them over to the customer in full.