Increasingly automation and digitization are taking over numerous processes. Self-driving delivery vehicles, such as forklifts, are finding their way into a number of areas — and companies are reporting potential cost and time savings. However, an interdisciplinary study team from the universities of Göttingen, Duisburg-Essen, and Trier has learned that cooperation between humans and machines can be more productive than just human or just robot teams independently. The outcomes were published in the International Journal of Advanced Manufacturing Technologies.
The study team mimicked a process from production logistics, such as the usual supply of materials for use in the engineering or car industries. A team of human drivers, a swarm of robots and a mixed group of humans and robots were allocated transport tasks using vehicles. The time they required was measured. The results were that the mixed team of humans and robots were able to outdo the other teams; this synchronization of processes was most efficient and caused the least number of accidents. This was quite unanticipated, as the maximum levels of efficiency are frequently assumed to belong to those systems that are fully automated.
"This brings a crucial ray of hope when considering efficiency in all discussions involving automation and digitisation", says the first author of the study, Professor Matthias Klumpp from the University of Göttingen. "There will also be many scenarios and uses in the future where mixed teams of robots and humans are superior to entirely robotic machine systems. At the least, excessive fears of dramatic job losses are not justified from our point of view.”
The scientists from the different disciplines of business administration, computer science and sociology of work and industry emphasized the requirements for effective human-machine interaction. In a number of corporate and business sites, decisions will continue to be made by people. The scientists, thus, conclude that companies should give more attention to their employees in the technical execution of automation.