Digital ergonomics and digital work planning in university education: experiences from Germany and Austria

Digitalization is currently omnipresent. In order to prepare the students of Mechanical Engineering and Human Factors Engineering at the Chair of Ergonomics, Technical University of Munich (TUM), for their future work and profession, it is necessary to familiarize them with the different methods and tools. The students graduate with a Master of Science degree after four semesters. Due to the different levels of experience and the interdisciplinary nature of the individual students, special attention must be paid to professional training in the area of teaching. Teaching at the TUM Chair of Ergonomics focuses on the use of different digital human models for the prospective workplace or product design. Especially RAMSIS NextGen (Human Solutions GmbH 2022) and ema Work Designer (emaWD, imk Industrial Intelligence GmbH 2022), are used for this purpose.

The ergonomics simulation software RAMSIS, as well as the follow-up version RAMSIS NextGen, can be used both as a standalone version and as a workbench in CATIA V5. As an anthropometric human model, it offers the possibility of early integration into the product development cycle. By entering parameters and boundary conditions, a probability-based posture can be calculated, and various analyses can be performed with regard to ergonomics. Reachability, as well as visibility analyses are the most frequently used modules, which are applied in the design of products and workplaces and are therefore taught in the context of teaching. RAMSIS NextGen offers more flexibility, efficiency and a better representation of the market. The user achieves results more quickly by viewing several human models (manikins) in parallel. The body shapes of the models have been improved based on real, three-dimensional scans. In addition, the possibilities of graphical visualization have been extended. The reusability of data and the improved usability of RAMSIS NextGen lead to a significantly more efficient process.

EmaWD as a standalone software enables a process module-based motion simulation for planning, designing and optimizing workflows and workplaces (Leidholdt et al. 2016, Spitzhirn et al. 2022a, b). In addition to the graphical modelling, a time-, economical- and ergonomic-oriented evaluation is possible by using the software. Different analysis methods such as standard execution time according to MTM-UAS, walking distances, proportion of value-adding activities as well as ergonomic analyzes of feasibility (reachability, visual analysis) and ergonomics and health risk assessment according to EAWS (Ergonomic Assessment Worksheet, Schaub et al. 2012) and NIOSH lifting index (Eller and Cassinelli 1994) can be used to identify economic and ergonomic problems. The EAWS screening tool enables the ergonomic assessment of static postures, action forces, load handling and repetitive activities. The result is a score and a traffic light classification into three risk areas.

Both digital human models and the associated courses complement each other. Students learn that there exists not just one human model that can be applied to any problem. On the contrary, the students are sensitized within the framework of the courses to select a suitable human model for a given simulation task. While RAMSIS NextGen is used in the RAMSIS practical course, emaWD is used in the Ergonomics practical course as part of a three-hour term and in the seminar Digital Ergonomics (cp. Table 1). In further TUM courses and application domains students can use this expertise using further DHM tools like AnyBody™ or OpenSim.

In the RAMSIS practical course, students learn to apply ergonomic product design guidelines by using RAMSIS NextGen. Using the driver’s seat of a BMW Mini as an example, students will become familiar with the possibilities of the 3D CAD human model for ergonomic interior design. They use theoretical knowledge to design a vehicle around the human being. After attending the practical course, the students will be able to understand the procedure for ergonomic vehicle interior design, remember relevant standards and apply the design of e.g. seat adjustment mechanisms of a given vehicle. Based on this, students will then be able to evaluate different products according to anthropometric aspects. Fig. 1a–c shows application examples for RAMSIS NextGen.

The Ergonomics practical course and the individual session on emaWD attempt to practically supplement and deepen the content of the Ergonomics lecture regarding the design of new workplaces. After attending the course, the students will be able to understand objective measurement and evaluation procedures in the fields of environmental and system ergonomics as well as anthropometry and to use them in a situation-related manner. As part of the topic of digital human modelling, the students learn how to use the emaWD software using the example of gear assembly. This basic knowledge helps the students to get an initial overview of the software and to familiarize themselves with the system for more detailed analyzes as part of the digital ergonomics seminar, for student research projects or later in their professional life (cp. Fig. 1d-f, below).

The seminar Digital Ergonomics teaches the approach of virtual planning, design and optimization of work processes, workplaces and products. After attending the course, the students are able to explain the basics of ergonomic design and evaluation and to use the emaWD software for ergonomic workplace design. Based on the example of gearbox assembly, the students will be able to transfer the contents learned to other workplace situations in the field of production/manufacturing and to carry out and assess workplace layouts according to EAWS principles. For this reason, you set up new scenarios and carry out optimizations in the ergonomic sense (e.g. assembly of an electric motor, automobile assembly (cp. Fig. 1d-f, below)).

The Chair of Labor Engineering at the Technische Universität Dresden (TUD) offers modules on Process and Product Ergonomics and Work Science for students in the Diploma program in Mechanical Engineering, in the Diploma and master degrees in Industrial Engineering and Business Administration, and in the Diploma degree in Transportation Engineering, where teaching content on digital a is integrated (cp. Table 2, TUD 2022).

The objective of the courses is to raise awareness of the significance of ergonomic task fields and to generate interest in them. Students will acquire the relevant technical and methodological expertise that will allow them to consciously and confidently shape their future professional field. They will be able to recognize the relevance and necessity of prospective working methods, in particular, via digital ergonomics validation. The teaching content includes the aspect that the two practical fields of product and process ergonomics encompass differentiated issues in their sphere of activity and that digital ergonomics tools with various functionalities have their raison d’être. Students are able to understand that digital and conventional methods, virtual and real validation complement each other in a meaningful way. They will learn that digital ergonomics tools constitute an aid in an iterative problem-solving process and that the success of their application depends on the students’ own ergonomics know-how and experience, solution strategies and their limitations. A workflow for the digital approach will be provided. The following digital tools are used:

Process Ergonomics comprises lectures (2 weekly hours per semester) and exercises (1 weekly hour per semester). The lectures conclude with a written exam and are divided into five complexes:

These elements are supplemented by application-oriented case studies including exercises for calculation, dimensioning, analysis and evaluation according to various methodological approaches for different load scenarios. Scenes simulated using digital human models (situational workplace conditions) are also utilized, as their visualization helps to demonstrate e.g. correlations between user anthropometry and stress characteristics, both partially or in workflows.

The exercise comprises nine modules, which are structured so that teaching content is deepened through complex application-related tasks. Thus, the interconnection between paper-and-pencil methods and digital ergonomics becomes apparent:

Technical and organizational requirements for the implementation are:

In the exercise Digital Human Models (1 SWS—semester hours per week) in the context of Product Ergonomics and Product Safety (2 SWS lectures), simplified and adapted application examples from industrial projects are discussed with the students. To this purpose, a structured course of action is taught and worked through step by step in ergonomic subtasks. The CharAT Ergonomics software is available to students in the computer lab and privately for a limited period of time. Project tasks are worked on in small groups in on-site exercises and self-study with consultation and then the grade is determined.

Assignments include: The creation of an animation scene to elucidate human model configuration and movement in the context of product handling (introductory example); dimensional design of a multifunctional armrest for mobile machines taking into account user anthropometries; anthropometric design of a tiler’s table; ergonomic requirements for choosing operating elements of an armrest control console; evaluation and design of visibility conditions at a test workstation.

Fig. 2 shows application examples for emaWD in the exercise Process Ergonomics (Fig. 2a, b) and for the exercise Digital Human Models with CharAT Ergonomics (Fig. 2c–e).

At the Institute of Management Science, the research group Human-Machine Interaction develops various industrial demonstrators for human-machine interaction, mostly at TU Wien Pilot Factory. In the context of designing human-oriented workplaces, the focus of the research group is on the use of assistance systems such as collaborative robots. The digital planning of robotic cells is a classic application of factory planning, but when using cobots, the consideration of human parameters and behaviour is indispensable (Fischer and Schlund 2021).

Against this background and with particular emphasis on ergonomics in mutual human-robot work systems, a lecture entitled Digital Simulation of Ergonomics and Robotics (DSER) was initiated in 2020. The lecture aims at master students of Mechanical Engineering and Industrial Engineering. The software tools emaWD (imk Industrial Intelligence GmbH 2022) and Tecnomatix Process Simulate (Siemens AG 2022) with the respective human models are used to simulate workplaces that have been designed within various research projects. Well established ergonomics risk assessment methods (NIOSH and EAWS) can be used and attribute scores for work postures, forces, loads and in EAWS also additional extra points for specific tasks, such as unergonomic wrist positions. The scores are summed up, in order to evaluate the task by comparing it to a final score (Schaub et al. 2012).

Students learn about the role of ergonomics in manufacturing, use various analysis tools for its evaluation and employ assistance systems for ergonomic improvements. Furthermore, they get to know digital human models and process simulation tools theoretically and practically through the implementation and improvement of industry-like use cases. The DSER course of 3 ECTS covers a period of six weeks and was delivered in an online blended learning mode due to the Covid-19 pandemic, consisting of distance self-learning and online live lectures. The communication software Microsoft Teams is used for the online lectures. After an online organizational meeting, the students learn the theoretical content in a self-study phase. A course on TUWEL, the TU Wien online learning platform, provides access to e‑lectures, slides and non-graded self-assessment tests. This theoretical part covers a period of three weeks, in which the students can work time flexibly on the documents. In order to proceed to the practical part, participants perform a graded multiple-choice test, which has to be passed in order to proceed with the practical part of the lecture. This part starts with a virtual live lecture with focus on the simulation software. Hands-on practical examples deepen the knowledge. After an introduction to the user interface, the first steps of the use case simulations are carried out. Furthermore, there is usually at least one topically related guest lecture from industry. Afterwards, students have three weeks to work in groups of two on the simulation and improvement of a chosen use case: human-cobot interaction or fan cowl assembly. Program files with the initial scenarios of the use cases are provided in order to ensure that everyone works with the same arrangement (cp. Fig. 3). The cobot use case illustrates a part of the assembly of a ski binding. Followed by the instructions on a PC-terminal, the human model picks up the ski from a pallet, puts it on the working table and screws together the binding components after the robot has placed them correctly on the ski. The second use case represents a manual fan cowl assembly. A fan cowl is an aircraft turbine housing that is manufactured layer by layer by mounting carbon mats. In the initial situation, the mats are placed on the pallet in an ergonomically unsuitable position and should be placed on the assembly object, according to the instructions of the PC-terminal.

Within a group, both simulation tools are distributed between the two team members. For each scenario, a help document, that introduces the user interface and gives step-by-step instructions for setting up the simulation, is provided via TUWEL by the supervisors. Students also can use videos to see what the final representation of the use case should look like. Furthermore, the students can use the ema help catalogue and the documentation of Siemens Learning Advantage, respectively. After a joint set-up of the initial scenario, the students develop and evaluate ergonomic improvements and implement them separately. In order to identify improvements, multiple analyses, such as path, time and ergonomics assessment are recommended. Within the project, mandatory consultation meetings to discuss intermediate results are carried out. It turned out that the use of an online collaboration tool facilitates the discussion, as the software allows to share control of the screen to solve problems directly in the programs of the students. In the closing lecture, the students present their group results as well as their experiences with the two simulation programs with special emphasis on the use of DHM.

Two student examples of ergonomics improvements are shown in Fig. 4, one for each use case. For both scenarios, the student groups raised the starting positions for the material, for example by replacing the pallet in order to avoid unergonomic lifting. In the scenario of the ski use case, a conveyor belt was installed that moves the ski directly to the assembly position, cp. Fig. 4a). Furthermore, a display for work instructions was mounted on top of the workplace. Besides significantly improving the body postures, from unfavourable 53.5 EAWS points (‘red’ region of high ergonomics risk) to suitable 13.5 points, the walking distance was reduced to less than half. Similar results were achieved in the shown fan cowl scenario, cp. Fig. 4b). It is realized by a U-shaped assembly station, where the instruction terminal and material pallets are placed on tables of adjustable height. Furthermore, the fan cowl is mounted on a turntable that rotates towards favourable working positions, so that the employee can always walk straight ahead after picking up the carbon mat and mounting it on the component.

The student’s grades consist of the results of the online test (10%), presentation (30%) and exercises (60%). Assessment criteria of the exercises include structure and functionality of the use case and ergonomics improvements. Presentation, ergonomic analysis and comparison of the simulations are evaluated as well. Students have the opportunity to further develop their skills in the use of digital human models as part of a seminar or master thesis, after the course. For future courses, the ergonomic parts of the lectures will be expanded by a practical EAWS lecture, where students learn to use EAWS hand sheets as well as automatic evaluation with the help of motion tracking. In addition, the focus on robotics simulation will also be expanded. However, the online self-study phase will remain online. The same applies to status meetings, also because the screen control in MS Teams has proven as a very helpful tool for quick and effective problem solving.

Digital examination of products within the framework of an underlying virtual production prior to real implementation embodies an immense trend for the future. Changes arising from this trend are not solely influencing industry practice, but also the state-of-the-art design of teaching. Simply working through course contents utilizing slide decks without experimental components does not lead to a promising transfer of knowledge anymore.

But how can knowledge from industrial engineering be conveyed vividly and practically while due to Covid-19 restrictions there is no possibility to experiment in real factories? Derived from this question, a newly structured teaching concept is presented, which finds its initial application during the module Industrial Engineering as part of the master’s program Wirtschaftsingenieurwesen at Jade University of Applied Sciences.

This course aims to enable students to independently analyze, design and improve micro and macro work systems from efficiency and humanization perspectives as realistically as possible utilizing digital tools like emaWD (imk Industrial Intelligence 2022) and visTABLE (plavis 2022).

To enable the students to enter the subject of Industry 4.0, additionally, the software OPC Router (inray 2022) is deployed. The overall student’s workload accumulates to 240 h, of which 72 h are allocated for contact study and 168 h for self-study. The lecture is offered annually with 4 SWS and is considered to be mandatory with 8 ECTS.

The idea of this one-semester teaching concept is that the instructor acts as a fictional customer, who requests students to submit an offer in the form of a concept for the production of a product like an e‑scooter. Within this concept, students work in teams of two and are required to compete with other student teams across the module to prove themselves as potential product suppliers. Instead of the lowest price product prioritization, the primary focus is the fictional customer’s desire for a transparent concept presentation for value-added service production developed by the teams over the course of the semester. Progress is continuously presented by the teams and based on the value stream for product manufacturing which is illustrated in Fig. 5.

Concept development starts for the students in Part 1 by getting to know the product and the customer requirements. Subsequently, product, process and resource data suitable for assembly are developed in cooperation with the fictional customer. In Part 2, the concept for product assembly in the form of a manual flow line with integrated human-robot interaction is digitally modelled utilizing the emaWD software. The emerging assembly embodies the pacemaker within the overall process of value creation and is therefore considered as the entry point for process representation. The process times determined deploying MTM methods incorporated in the emaWD should be shorter than the demand-dependent takt time and the ergonomic values determined deploying EAWS should be in the range with a low risk of biomechanical overload. Levelling the overall flow is an additional challenge.

In Part 3, students practice in teams how leadership is performed on the shopfloor level with e.g. Toyota KATA (Rother 2010) utilizing previously digitally developed assembly. Thereby a continuous improvement process is created in the direction of further value creation. Furthermore, a concept for the training of employees at the assembly line applying TWI (Training Within Industry) is developed, which is practiced at the virtual assembly line (cp. Fig. 6). The students’ ability to apply TWI must be demonstrated in a short video that shows the simulation of the assembly from emaWD and a role play between mentor and mentee.

With the utilization of preparatory work from Part 1 (process and resource data), the entire value stream is finally designed in Part 4 for all components of the product, which are manufactured in-house. The virtual representation of the value stream, including layout planning and material flow analysis, is performed via the visTABLE software. By expanding the ‘classic’ value stream mapping by additional elaboration of information logistics (Meudt et al. 2017), the students learn to identify key performance indicators within the production process, which are to be digitized in Part 5. During this last part of the overall concept, the students perform Industry 4.0 experiments and practice digitization of processes using smart sensors, cloud technologies and the OPC Router communication software.

For the application of the presented overall teaching concept, for each semester an individual product or demonstrator is selected and CAD data of the product to be assembled is prepared in detail. During the semester, students are taught theoretical foundations by the instructor, receive content through tutorials held by trained lab engineers and get access to explanatory videos on the integrated software. Students can immediately put newly acquired knowledge into action, because virtually created assembly concepts as well as the entire production can be modified experimentally. Through the role plays, the students practice managing employees and change processes, while learning leadership skills that would not be achieved solely through lectures. Utilizing tools such as Virtual Reality (VR) and Augmented Reality (AR), students are enabled to virtually ‘walk through’ the assembly and the factory. Via virtual collaboration, students can work simultaneously on the same factory in a virtual space. To evaluate the concept, the students must create a written elaboration and explanatory videos. In the videos, the students present their demonstrator and the respective concept of industrial production. The team who presents the overall best concept according to customer requirements receives the (fictional) order and a corresponding very good grade.

During the course, the master’s students deal with individual topics Part 1 to Part 5 whereby many activities can be performed independently and digitally. An additional learning effect is achieved through regular presentations and discussions of partial results of the topics in front of and within a group. The module is also characterized by the fact that the event is held in the form of a competition, which encourages students’ ambition. In retrospect, a master’s student evaluates the module as follows: “My experience is that the module is very practical and includes many digital tools that are valuable and can be used directly for planning tasks in companies.” A reduction in students’ workload is possible by a future concept which focuses on an already existing production (brownfield planning). To further improve the interfaces between the software packages, emaPD (imk Industrial Intelligence GmbH 2022) will also be used additionally in the future for layout planning and material flow analysis.

The Chair of Ergonomics and Innovation Management at the Technische Universität Chemnitz is involved in research and teaching on digital human models for quite some time (Bullinger-Hoffmann and Mühlstedt 2016; Kaiser et al. 2020; Kaiser and Bullinger 2020). In terms of teaching, the chair customarily offers single tutorials on digital human models within courses such as Arbeitswissenschaft and Arbeitsanalyse und Arbeitsgestaltung. These courses are part of various degree programs. Within the tutorials, students gain a general overview of purposes, concepts and types of digital human models. They also find opportunities to try out digital human model software. For example, they can manipulate given manikins and scenes, assess and—to a suitable extent—improve existing models of workplaces.

Since 2018, the chair has participated in the Master’s program Advanced Manufacturing by means of the elective course Digital Ergonomics, where digital human models make up a large part of the course. The course is held in English. Teaching forms are seminars (90 min per week) and exercises (90 min per week). The student’s workload amounts to 150 working hours. Five credit points are awarded.

In the course, various self-learning material for ergonomic analysis and ergonomic work design is provided. On this basis, methodological skills are deepened in seminars and exercises in order to apply ergonomic concepts with the help of advanced digital tools. The seminars focus on:

Subject to the exercises and the homework is a case study—the analyses and redesign of a work system—consisting of:

Students have to supply five recorded practical achievements as part of homework, and a report of the case study including developed optimizations. The final event is an oral presentation and discussion of the results of the case study (cp. Fig. 8).

Usually, exercises were held at the university’s PC pool using educational licenses for ema Work Designer and SketchUp Pro. Due to the Covid-19 pandemic, students had to attend remotely using their private computers or logging into virtual computers provided by the university. Appropriate software licenses were provided as well.

In the course described the use of digital human models in teaching shows the following advantages:

On the other hand, there are disadvantages and challenges:

However, the increasing number of participants shows the success of the (elective) course.

Digital simulations with the use of digital human models have the potential to improve teaching in various engineering disciplines such as mechanical engineering, industrial engineering and management and product development as demonstrated in training processes in the industry (Dennerlein et al. 2015; Spitzhirn et al. 2017). Digital simulations enable various scenarios, different planning alternatives and the setup of complex work systems.

The following advantages become evident throughout the use of digital ergonomics tools, especially in university teaching:

Using digital human models for academic teaching purposes still bears some inconveniences such as the time-consuming setup and upgrade routines before each course and, in some cases—especially regarding the integrated software suites—a complex learning procedure for the program itself. At the moment the preparation and supervision effort for the teaching staff is still high, as individual support is required for problem-solving in dealing with the software, depending on the previous knowledge of the students. The results of the ergonomics assessments and time analysis are difficult to compare due to possible variations in the underlying 3D environments modelled by the students themselves. However, the experiences in the courses also help to feedback on important aspects, findings, advantages, and disadvantages to the manufacturers of digital human models. The manufacturers can benefit from these statements, weigh them up, and reflect them in revisions. Universities and research institutions not only focus on the result of the analysis but also on the usability of software and intuitive application, in order to keep the load on the user of the software as low as possible.

Experience shows that the active and independent use of digital ergonomics tools gives students pleasure and motivates them to deal intensively with complex tasks in terms of time and content. Feedback is consistently positive over all the involved lectures and universities. Students develop an interest in deepening ergonomics subject areas in the further course of their studies (e.g. in the form of seminar papers and theses) and internalizing them in their future professional lives. The sensible dovetailing of paper-and-pencil methods or theoretical principles and digital ergonomics tools are perceived more strongly.

Furthermore, the automated evaluation and optimization assessment focus more on the results and less on the methodological foundation of the evaluation. Thus, additional theoretical input—e.g. basic principles of productivity and ergonomics evaluation—is still necessary. For example, prior learning of paper-and-pencil methods is recommended. Last but not least, digital simulations only provide modelled instances of reality. Despite various simulations and tests, some impacts of work system design can be perceived in reality only. Especially for the use in SMEs and the involvement of shop floor staff, tangible, hands-on prototypes often provide a feasible alternative for early participation and commitment of people that are not familiar with digital planning tools.

As worldwide pandemics forced the use of digital learning, the use of digital human models has experienced a boost in relevance for teaching, but also for implementation purposes in industry. Digital tools, such as human models have proven to be valuable alternatives to classroom teaching and physical prototypes. From a short-term perspective, they even replaced traditional approaches. Based on the experience, but also the inconveniences of interaction and commitment in online teaching settings, we expect a stronger trend towards hybridization of real and digital tools in education over the long term. Lessons learned over all the presented approaches show a preference towards project-based, multi-modal learning settings with well-chosen tool use. These experiences align well with the results of industrial up- and reskilling approaches (Hader et al. 2022). The opportunities to use synchronous and asynchronous learning settings have been well-received by the students as well as a return to work-based learning infrastructures such as learning factories (Komenda et al. 2021). Consequently, digital simulations are considered as an integral part of future skill sets in work system planning.

Beyond education and learning purposes, we expect a growing emphasis on digital human models within the ongoing discussion on further integration of physical virtual characteristics of products, processes and services. Various sensors, sensor fusion, and wireless data transmission enable the creation of digital twins as digital representations of objects and product-services (Stark and Damerau 2019). In order to promote the design of work systems according to the principles of socio-technical systems the further integration of human parameters, behaviour and requirements will be of crucial importance. Therefore, existing approaches need to be improved in terms of standardized data interfaces, transparent algorithms, further analysis functions, a realistic representation of the human and real real-time synchronization with the physical work system. For digital twins used for (longer-term) planning, generic human models with typical percentile characteristics and standard performance may be sufficient. Especially if the digital twins are to be synchronized with physical production in (almost) real-time for the purposes of operational planning and control, digital human models must be more customizable (e.g. individual qualifications, skill limitations, availability). In this regard, the first steps have been taken with regard to age-related ability changes (Wirsching and Spitzhirn 2019; Spitzhirn et al. 2022b). Recent developments in sensor technology allow performant use of human activity recognition and adaptable work systems (Schlund and Kostolani 2022). Consequently, the traditional planning process of work system design, planning and use might be developed into a dynamic on-site improvement of an adaptive work system, whereas possible adjustments are simulated in parallel via a digital twin including a digital human model.