Hospitals, logistics centres as well as production sites all depend on manual labour and require the movement of staff and various work steps. This includes unhealthy bending processes, lifting of heavy items, overhead work and long walking distances that can be exhausting and entail lasting negative effects on the health of the employees, such as musculoskeletal disorders. Eventually, high sickness and absence rates are the result if manual processes are not coordinated and ergonomically optimized. Also, such processes lead to significant costs and take up a lot of time and resources that could be used otherwise.
In a hospital, work processes involve operation logistics such as supplying the operating room with materials (e.g. using a trolley), straightening instruments, cleaning the operating room, preparing trays, storing and picking of surgical material and the pushing of beds or carts. In a logistics warehouse, this might be the handling and transport of incoming goods to storage picking and dispatch or packaging activities. In an industrial shop floor or production site, relevant processes include the movement and handling of tugger trains or the supply of spare parts and tools or the disposal of defective components during maintenance.
Up to now, most companies trying to improve their work processes collect relevant data manually – by monitoring with cameras, timer and clipboard – or simply rely on estimations. The crux of such a process is that the monitored person is well aware of it, which can cause falsified results. In addition, the manual monitoring is costly and complicated or steps are difficult to quantify due to insufficient entries in the system.
A German company has developed a solution for the anonymous and automated collection of motion data, the quantification and verification of the different work steps, their analysis and the identification of optimization potential regarding efficiency and ergonomics.
Sensors that employees can wear on their wrists and belts during their work shift collect data anonymously. These sensors can collect very fine motion data such as hand gestures or vibrations. Also, information on the surroundings like temperature or light will be determined. In addition, transport equipment can be equipped with sensors to provide even more accurate human-machine interaction data. The localization of employees and activities is done with beacons (miniature radio transmitters).
The collected data is then automatically analyzed. Activities and process steps, but also waiting times in front of elevators, loads when pushing beds or carts or exposure to temperature, can be determined. The different processes are assigned using a pattern recognition method based on deep learning. Artificial intelligence automatically recognizes the various process elements and identifies weak points.
The software platform in combination with human know-how can then use the collected data to assess ergonomics, provide a transparent visualization of all processes and suggest concrete counter measures. Users are provided with an implementation plan they can follow. As a result, process times in hospitals or companies will shorten, costs will go down, workload of employees will diminish and their physical working conditions will improve.
The German SME is looking for partners from the above mentioned three sectors for commercial agreements with technical assistance. Task to be performed in this kind of agreement is the implementation of the technology in order to make manual processes more efficient. The necessary know-how for technology transfer will be provided by the German company.
The German SME is also looking for service providers with IT expertise for these sectors for license agreements. Task to be performed in this kind of agreement is the use of the technology with own clients after the acquisition of a license.