Högskolan i Skövde

The shift towards electric vehicle production has introduced new manufacturing challenges, particularly in tasks that require operators to handle flexible components such as electrical wire harnesses and high-voltage cables. Assembly tasks such as picking, carrying, deforming, and mounting flexible components are usually performed by operators and can result in high force demands, affecting both operator well-being and production efficiency. Ensuring that these work demands do not exceed an operator’s physical capacity is essential for maintaining a sustainable work environment, improving worker well-being, and reducing risks of work-related musculoskeletal disorders. This paper addresses this challenge by simulating and evaluating a real-world use case at Volvo Cars AB, where operators manually install electrical wire harnesses in an automotive assembly station. The study integrates the Arm Force Field method within a DHM tool to compare forces demanded by the assembly task to force capacity of the operators. Additionally, RULA and REBA are used to evaluate postural risks during the assembly. The simulation estimates force demands for picking, carrying, deforming, and mounting the harness. By analysing the ratio between work demand and human capacity, this study provides insights into how DHM tools can assist engineers and ergonomists to proactively assess assembly work of flexible objects, in turn assisting workstation design and supporting sustainable manual assembly conditions.

To ensure a sustainable work life, work demands should not exceed the capacity of members of the workforce. Digital human modelling (DHM) tools can be used to consider ergonomics issues in computer simulated settings, supporting engineers and ergonomists to proactively find design solutions that fulfil well-being related criteria. For this, DHM tools need to be able to assess risks for musculoskeletal disorders (MSDs). One key risk factor for MSDs is force exertions. This load dose on the human body is influenced by aspects such as the magnitude of the force, the direction of the force, the frequency of force exertion, the duration of the force exertion, and the posture held during force exertion. This paper compares force capacities for three different work postures and six force directions given by two methods: the Assembly Specific Force Atlas and the Arm Force Field. The study takes a DHM tool user’s point of view, envisioning the methods being used to assess a design proposal of a work scenario being simulated in a DHM tool. The results show that the two methods, for some conditions, predict quite similar force capacities, while for other conditions there are larger differences. Reasons for these findings are discussed.

This paper presents a hybrid machine learning framework to enhance traffic safety in urban road intersections. The framework employs a two-stage approach: Decision Trees predict vehicle trajectories by identifying turning behaviors, while Random Forests estimate collision probabilities involving vehicles and vulnerable road users (VRUs) such as pedestrians and cyclists. Engineered spatial, temporal, and motion-related features are derived from high-resolution trajectory data collected via connected camera systems in busy urban cores. The experimental results demonstrate high predictive accuracy, achieving an F1-Score of 0.97 for turning vehicle classification and a ROC-AUC of 0.98 for collision risk estimation. Compared to computationally intensive deep learning models, the proposed framework balances robust performance with computational efficiency, making it suitable for realtime deployment in complex urban environments. The framework integrates with in-vehicle Human-Machine Interfaces (HMIs) to enhance driver awareness and enable proactive safety interventions. This study addresses the need for interpretable and scalable road safety solutions in connected traffic systems.

Understanding players’ diverse visual recognition and visual preferences, especially in cross-cultural contexts, is critical for the creation of effective serious games. This study aimed to examine how varying levels of fidelity affect players' visual recognition, visual preference, and overall experience in serious gaming, using a mixed-method case study in the Bhaktapur district, Kathmandu, Nepal. Forty-four participants, aged 13 to 16 years, were enrolled in an A/B gameplay test. Fourteen students participated in in-depth interviews, thirty-six completed a questionnaire, and twenty-two provided valid telemetry data. We found that higher fidelity led to more positive affect, better recognition, stronger preference, higher familiarity, and positive emotional response from players. However, challenges were encountered regarding the identification of local food items. This highlights the key role of visual literacy, as adolescents are more influenced by familiar media than by real-life experiences in terms of visual recognition and preference. Effective visual communication in serious games should consider individual differences and the playing environment. This study contributes to serious game research by providing insights into an underrepresented demographic and demonstrating the importance of cultural context in visual communication. Findings offer practical guidance for game developers to design more inclusive and effective serious games.

In the design process of products and production systems, the activity to systematically evaluate initial alternative design concepts is an important step. The digital human modeling (DHM) tools include several different types of assessment methods in order to evaluate product and production systems. Despite this, and due to the fact that a DHM tool in essence is a computer-supported design and analysis tool, none of the DHM tools provide the functionality to, in a systematic way, use the results generated in the DHM tool to compare design concepts between each other. The aim of this paper is to illustrate how a systematic concept evaluation method is integrated in a DHM tool, and to exemplify how it can be used to systematically assess design alternatives. Pugh´s method was integrated into the IPS software with LUA scripting to systematically compare design concepts. Four workstation layout concepts were generated by four engineers. The four concepts were systematically evaluated with two methods focusing on human well-being and two methods focusing on system performance and cost. The result is very promising. The demonstrator illustrates that it is possible to perform a systematic concept evaluation based on human well-being, overall system performance, and other parameters, where some of the data is automatically provided by the DHM tool and other data manually. The demonstrator can also be used to evaluate only one design concept, where it provides the software user and the decision maker with an objective and visible overview of the success of the design proposal from the perspective of several evaluation methods.

The type of ergonomics assessment methods typically used in digital human modelling (DHM) tools and automated assessment processes were rather developed to be used by ergonomists to assess ergonomics by observing the characteristics of the work. Direct measurement methods complement observation methods. Direct measurement methods have a design that suits being implemented into DHM tools. A drawback of direct measurement methods is that they traditionally do not include action levels. However, action levels in direct measurement methods have recently been suggested. The aim of this paper is to illustrate how these recent physical load exposure calculations and recommendations can be integrated in a DHM tool and in an automated assessment process. A demonstrator solution was developed that inputs exposure data from simulations in the DHM tool IPS IMMA as well as exposure data that originate from tracking real workers’ motions, using the motion capture system Xsens MVN. The demonstrator was applied in two use cases: one based on predicted human motions and one based on captured human motions. In the demonstrator, head posture, upper left and right arm posture and velocity, as well as left and right wrist velocity were calculated. Exposure data were compared with action levels, and extreme action levels were indicated by colouring the information. The results are promising, and the demonstrator illustrates that it is possible to follow the trends in Industry 4.0 and Industry 5.0 to automate and digitalize ergonomics assessment processes in industry.

Simulation using virtual models is used widely in industries because it enables efficient creation, testing, and optimization of the design of products and production systems in virtual worlds. Simulation is also used in the design of workstations to assess worker well-being by using digital human modeling (DHM) tools. DHM tools typically include musculoskeletal risk assessment methods, such as RULA, REBA, OWAS, and NIOSH Lifting Equation, that can be used to study, analyze, and evaluate the risk of work-related musculoskeletal disorders of different design solutions in a proactive manner. However, most musculoskeletal risk assessment methods implemented in DHM tools are in essence made to assess static instances only. Also, the methods are typically made to support manual observations of the work rather than by algorithms in a software. This means that, when simulating full work sequences to evaluate manikins’ well-being, using these methods become problematic in terms of the legitimacy of the evaluation results. In addition to that, to consider objectives in optimizations, they should be measurable with real numbers, which most of musculoskeletal risk assessment methods cannot provide when simulating full work sequences.

In this study, we implemented the musculoskeletal risk assessment method OWAS in a digital tool connected to the DHM tool IPS IMMA. We applied the Lundqvist index on top of the OWAS whole body risk category score. This gave us an integer of the time-based ergonomic load for a specific simulation sequence, enabling us to qualitatively compare different design solutions. Using this approach, we performed an optimization in a welding gun workstation to improve the design of the workstation. The results show that using time-based musculoskeletal risk assessment methods as objective functions in optimizations in DHM tools can provide valuable decision support in finding solutions for workstation designs that consider worker well-being.

This paper describes the use of the WOz method in the development of a prototype for a multi-player mixed reality game for children. It is an adventure game with hidden treasures, clues to hiding places, and information that should not be revealed. The game design, however, includes deceptive elements aimed at luring players to give up information. The game’s underlying intent is to raise children’s online risk awareness. The WOz was used in the early developmental stage to evaluate and explore the game concept, and to find a way to synchronise and integrate different in-game processes. We describe four central game mechanics for which the wizarding proved to be highly useful. We also discuss some ethical aspects related to the method a such as well as to the game design. In sum, we found the WOz method as such to be very useful for game design and development.

Objective. Simulation based training with full-size mannequins is a prominent means of training within the healthcare sector. Prehospital missions include all parts of the healthcare process which take place before a patient is handed over to the receiving hospital. This implies that the context for prehospital care is varied and potentially challenging or dangerous in several ways. In this article we present a study which explores immersion and performance by emergency medical services (EMS) professionals in in a training situation which takes the specifics of prehospital interventions into account.

Methods. The study was carried out as a field experiment at an ambulance unit. The experiment was designed to compare the differences between two types of medical scenarios: basic and contextualized. We analyzed the levels of immersion throughout the scenarios and then team performance was evaluated by independent experts. Both analyses were made by observing video recordings from multiple camera angles with a custom made analysis tool.

Results. Our results show that the contextualization of a medical scenario increases both immersion as measured by the Immersion Score Rating Instrument (ISRI) and team performance as measured by the Global Rating Scale (GRS). The overall ISRI score was higher in the contextualized condition as compared to the basic condition, with an average team wise difference of 2.94 (sd = 1.45). This difference is significant using a paired, two-tailed t-test (p<.001). The GRS score was higher for overall clinical performance in the contextualized scenario with an average team wise difference of 0.83 (sd = 0.83, p=.005).

Conclusions. Full-size mannequin simulation based training for EMS professionals may be enhanced by contextualizing the medical scenarios. The main benefits are that the contextualized scenarios better take prehospital medical challenges into account and allow participants to perform better.