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As work environments become increasingly complex and digital, the resulting changes also pose major challenges for the daily work of staff members. In a learning experiment, researchers explore how employees learn production processes and what factors influence their learning success. Heike Kampe participated in the experiment to find out more.
I feel warm in my white lab coat, and the goggles pinch my nose as I stand somewhat clueless in front of the monitor of a milling and grinding machine. I’m new here and have to get acquainted with the job. In a video I was shown beforehand, the production manager explained to me how important it is to work accurately and to strictly follow instructions. After all, we are manufacturing a medical product. When it comes to a knee prosthesis, every millimeter matters. At the same time, I have to work quickly to handle my workload.
I check the instruction sheet to find out how to set the correct program to mill and grind the blank on the conveyor belt in front of me. I press a bar on the display, and the blank moves into the milling machine. I fix it, choose the short milling program for the front end, and press “start”. With a screech, the machine starts working. I’m able to monitor the process through a window at the front end. After 10 seconds, the blank has been milled; it now needs to be ground and then removed from the machine.
I still feel somewhat uncertain, so I strictly follow the instruction sheet and have to keep referring back to it to see which step comes next. Which program do I set? Are the consumables in the machine sufficient? Which box do I tick on the form? Where do I find the correct size? I have to hurry, because my colleague is waiting for the blank to continue working on it.
Gradually, I get better and better. The team manager takes the instruction sheet away from me – now I have to do without it and perform the tasks from memory.
It works! I collect the sheet with the right order number from the terminal, grab a blank with the right color and shape from the materials store, fill out the form, and grind the prostheses in the machine. I measure the blank with a caliper to make sure the size is correct. Then I mark it with a green sticker and place it on the conveyor belt. At the press of a button, the blank is transported to the next workstation, where my team colleague waits to polish it.
I really feel like I’m on a factory production line. But this is not a production hall; it is the Industry 4.0 Research and Application Center on the Griebnitzsee Campus. The production line – the conveyor belt, machines, robots – here simulates the work processes of a real factory.
Next to me, two other women simulate production processes at their respective machines. We are participating in a research experiment on learning and forgetting. The machines are not real. Everything is digitally simulated yet feels authentic. Each step of our work is being analyzed. Our goggles record our eye movements and every sound. The vast datasets we are generating will later be thoroughly evaluated by researchers from Potsdam and Bochum. They are interested in the way we master the production process, the mistakes we make, and what makes us particularly effective and fast.
The study is supervised by Christof Thim from the Chair of Business Information Systems, in collaboration with psychologist Jennifer Haase. By October 2019, hundreds of test subjects will have participated in it. Haase knows that digitization will be changing work routines at virtually every level.
“In the future, factory workers will also have to deal with new technologies, robots, tablets, and other digital tools more often,” Haase explains. Entire processes are digitized and recorded in the background in order to make planning and work more efficient and to optimize resource use. This will also impact factory work routines.
How do people cope with these changes? And how can they be supported? These are the key issues addressed by the researchers in this learning experiment. For Haase, the experiment is unique: “Very rarely does one get to research under such realistic yet controlled conditions.” The simulated production line allows the researchers to look at many variables, she explains.
How do we learn production processes and change work routines? Are there any tools that facilitate learning? Under what conditions do we forget what we have learned? In various experiments at the Application Center, the researchers are also testing the role of reward, punishment, and time pressure in learning processes and how to formulate learning material in order to facilitate learning.
Meanwhile, everything is running like clockwork on the production line. I’ve gotten faster, so my team colleague no longer has to wait for me. We are very busy at our machines completing different tasks. We have worked through the instruction sheets and are now fully committed to what we are doing. There’s not much talking.
In this respect, however, people differ, Haase explains: “In some groups, there is a lot of talking, people exchanging their views.” These social interactions are also being studied in the experiment. The researchers want to find out whether communication between team members impacts productivity. Either way, initial results indicate that all groups ultimately end up working at roughly the same rate. While a complete run takes 20 minutes at first, only six are needed after the learning phase.
We are done for today. My head’s spinning, and I’m tired, even though the job was neither physically demanding nor intellectually challenging. “The process as such is not difficult to learn,” Haase confirms, “but the amount of detail makes it strenuous.” I remove the goggles that have been tracking my eye movements for the past two hours. Before we leave, the researchers ask us to consolidate and internalize the steps we have learned today with the help of an app in the coming days. I take off my white lab coat and wonder what will happen in three weeks’ time, when I return for the second part of the experiment. And whether the results will really enable the researchers¬ – in a year from now – to tell how and when people learn production processes particularly effectively and quickly.
The learning experiment “Manuthetic” is still looking for participants. Find out more at https://manuthetic.lswi.de
Jennifer Haase studied psychology with a focus on research at the universities of Halle-Wittenberg and Lund (Sweden). She has been a research assistant at the Chair of Business Information Systems and in charge of the Manuthetic experiment since January 2018.
Dr. Christof Thim studied sociology, politics, and economics at the University of Potsdam. At the Chair of Business Information Systems he researches the adaptability of organizations to changing environments.
Text: Heike Kampe
Translation: Monika Wilke
Published online by: Alina Grünky
Contact to the online editorial office: onlineredaktionuni-potsdamde