How do the digital determination of motion data, AI and the application of the MTM method standard interact to sustainably improve work processes and conditions? At the MTM SUMMIT 2024 and here in an interview, Dr. Sascha Feldhorst, CEO MotionMiners GmbH, and Prof. Dr. Peter Kuhlang, CEO MTM ASSOCIATION e. V., describe smart paths from (subjective) gut feeling to data-based (objective) facts using the example of a parcel delivery service project.
On behalf of the German Federal Ministry of Labor and Social Affairs, MTM ASSOCIATION e. V. and MotionMiners GmbH are working on a preliminary study for the ergonomic evaluation of typical activities and process elements of parcel and package delivery. The focus is on the last part of the supply chain. On the so-called “last mile”, the parcels, some of which weigh more than 30 kg, are loaded into the delivery vehicle and delivered to the end customer. The goal of the project is to create an objective database that can be used to define reasonable performance corridors and to improve processes in terms of occupational health and safety.
Machine learning connects the ACTUAL and TARGET worlds
Peter Kuhlang and Sascha Feldhorst explain how MotionMining® (ACTUAL movement data), machine learning algorithms and interpretation using the MTM method (TARGET times) have made it possible to visualize, measure and thus evaluate the stress of employees in the last mile. To a certain extent, the much quoted “magic” lies in this connection between the ACTUAL and TARGET worlds using machine learning.
The parcel delivery project has also changed the way we look at this occupational group, says Peter Kuhlang. On the one hand, in terms of what this group has to do, the time and ergonomic stress they are exposed to, and on the other hand, in terms of the entire transportation and delivery system.
New methodology applicable to industry
Peter Kuhlang and Sascha Feldhorst answer the question of whether this evaluation concept for the “last mile” can be transferred to other areas, such as industry, with a resounding yes. Wherever managers complain about a lack of transparency and the resulting inability to plan, light can be shed into the darkness. A new methodology has emerged that combines the strengths of mass data from the ACTUAL world with descriptions of the same processes from the TARGET world.
Using automatically captured ACTUAL data to build better TARGET models – that’s what the MTM SUMMIT 2024 wants to convey to the MTM community. Sascha Feldhorst’s target audience: “Anyone who is interested in dealing with motion data and seeing what new things I can get out of the data I record.”
Find out what else is happening at the MTM SUMMIT 2024 and all information about tickets (online for free) at summit.mtm.org.