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  • 1.
    Garcia Rivera, Francisco
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brolin, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    A Framework to Model the Use of Exoskeletons in DHM Tools2021In: Advances in Simulation and Digital Human Modeling: Proceedings of the AHFE 2021 Virtual Conferences on Human Factors and Simulation, and Digital Human Modeling and Applied Optimization, July 25-29, 2021, USA / [ed] Julia L. Wright; Daniel Barber; Sofia Scataglini; Sudhakar L. Rajulu, Cham: Springer, 2021, p. 312-319Conference paper (Refereed)
    Abstract [en]

    Work-related musculoskeletal disorders (WMSDs) constitute a large part of work absences among industry workers, together with all the health and economic problems that it carries. Exoskeletons developed for overhead operations can potentially be a solution to reduce risks for WMSDs. However, some companies are still hesitant to implement exoskeletons in their workplace, since the effects of using exoskeletons are still not fully proved. Digital human modeling (DHM) could help with this dilemma by facilitating studies of the viability of the exoskeletons for specific work tasks. This paper proposes a DHM based framework to implement the study of upper body exoskeletons focused on overhead assembly operations. The framework emphasizes the kinematics and forces interaction between the human and the exoskeleton. 

  • 2.
    Garcia Rivera, Francisco
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Iriondo Pascual, Aitor
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Using Virtual Reality and Smart Textiles to Assess the Design of Workstations2020In: SPS2020: Proceedings of the Swedish Production Symposium, October 7–8, 2020 / [ed] Kristina Säfsten; Fredrik Elgh, Amsterdam: IOS Press, 2020, Vol. 13, p. 145-154Conference paper (Refereed)
    Abstract [en]

    This paper presents a solution that integrates a smart textiles systemwith virtual reality to assess the design of workstations from an ergonomics pointof view. By using the system, ergonomists, designers, engineers, and operators,can test design proposals of workstations in an immersive virtual environmentwhile they see their ergonomics evaluation results displayed in real-time.. Thesystem allows its users to evaluate the ergonomics of the workplace in a preproduction phase. The workstation design can be modified, enabling workstationdesigners to better understand, test and evaluate how to create successfulworkstation designs, eventually to be used by the operators in production. Thisapproach uses motion capture together with virtual reality and is aimed tocomplement and integrate with the use of digital human modelling (DHM)software at virtual stages of the production development process.

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  • 3.
    Garcia Rivera, Francisco
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Lamb, Maurice
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    DHM supported assessment of the effects of using an exoskeleton during work2022In: International Journal of Human Factors Modelling and Simulation, ISSN 1742-5549, Vol. 7, no 3/4, p. 231-246Article in journal (Refereed)
    Abstract [en]

    Recently, exoskeletons have been gaining popularity in many industries, primarily for supporting manual assembly tasks. Due to the relative novelty of exoskeleton technologies, knowledge about the consequences of using these devices at workstations is still developing. Digital human modelling (DHM) and ergonomic evaluation tools may be of particular use in this context. However, there are no standard integrations of DHM and ergonomic assessment tools for assessing exoskeletons. This paper proposes a general method for evaluating the ergonomic effects of introducing an exoskeleton in a production context using DHM simulation tools combined with a modified existing ergonomic assessment framework. More specifically, we propose adapting the Assembly Specific Force Atlas tool to evaluate exoskeletons by increasing the risk level threshold proportionally to the amount of torque that the exoskeleton reduces in the glenohumeral joint. We illustrate this adaptation in a DHM tool. We believe the proposed methodology and the corresponding workflow can be helpful for decision-makers and stakeholders when considering implementing exoskeletons in a production environment.

  • 4.
    Igelmo, Victor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    García Rivera, Francisco
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Peréz Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Aiding Observational Ergonomic Evaluation Methods Using MOCAP Systems Supported by AI-Based Posture Recognition2020In: DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020 / [ed] Lars Hanson, Dan Högberg, Erik Brolin, Amsterdam: IOS Press, 2020, p. 419-429Conference paper (Refereed)
    Abstract [en]

    Observational ergonomic evaluation methods have inherent subjectivity. Observers’ assessment results might differ even with the same dataset. While motion capture (MOCAP) systems have improved the speed and the accuracy of motiondata gathering, the algorithms used to compute assessments seem to rely on predefined conditions to perform them. Moreover, the authoring of these conditions is not always clear. Making use of artificial intelligence (AI), along with MOCAP systems, computerized ergonomic assessments can become more alike to human observation and improve over time, given proper training datasets. AI can assist ergonomic experts with posture detection, useful when using methods that require posture definition, such as Ovako Working Posture Assessment System (OWAS). This study aims to prove the usefulness of an AI model when performing ergonomic assessments and to prove the benefits of having a specialized database for current and future AI training. Several algorithms are trained, using Xsens MVN MOCAP datasets, and their performance within a use case is compared. AI algorithms can provide accurate posture predictions. The developed approach aspires to provide with guidelines to perform AI-assisted ergonomic assessment based on observation of multiple workers.

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  • 5.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Lämkull, Dan
    Advanced Manufacturing Engineering, Volvo Car Corporation, Göteborg, Sweden.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Global Industrial Development, Scania CV AB, Södertälje, Sweden.
    Optimization of Productivity and Worker Well-Being by Using a Multi-Objective Optimization Framework2021In: IISE Transactions on Occupational Ergonomics and Human Factors, ISSN 2472-5838, Vol. 9, no 3-4, p. 143-153Article in journal (Refereed)
    Abstract [en]

    OCCUPATIONAL APPLICATIONS

    Worker well-being and overall system performance are important elements in the design of production lines. However, studies of industry practice show that current design tools are unable to consider concurrently both productivity aspects (e.g., line balancing and cycle time) and worker well-being related aspects (e.g., the risk of musculoskeletal disorders). Current practice also fails to account for anthropometric diversity in the workforce and does not use the potential of multi-objective simulation-based optimization techniques. Accordingly, a framework consisting of a workflow and a digital tool was designed to assist in the proactive design of workstations to accommodate worker well-being and productivity. This framework uses state-of-the-art optimization techniques to make it easier and quicker for designers to find successful workplace design solutions. A case study to demonstrate the framework is provided

    TECHNICAL ABSTRACT

    Rationale: Simulation technologies are used widely in industry as they enable efficient creation, testing, and optimization of the design of products and production systems in virtual worlds. Simulations of productivity and ergonomics help companies to find optimized solutions that maintain profitability, output, quality, and worker well-being. However, these two types of simulations are typically carried out using separate tools, by persons with different roles, with different objectives. Silo effects can result, leading to slow development processes and suboptimal solutions.

    Purpose: This research is related to the realization of a framework that enables the concurrent optimization of worker well-being and productivity. The framework demonstrates how digital human modeling can contribute to Ergonomics 4.0 and support a human factors centered approach in Industry 4.0. The framework also facilitates consideration of anthropometric diversity in the user group.

    Methods: Design and creation methodology was used to create a framework that was applied to a case study, formulated together with industry partners, to demonstrate the functionality of the noted framework.

    Results: The framework workflow has three parts: (1) Problem definition and creation of the optimization model; (2) Optimization process; and (3) Presentation and selection of results. The case study shows how the framework was used to find a workstation design optimized for both productivity and worker well-being for a diverse group of workers.

    Conclusions: The framework presented allows for multi-objective optimizations of both worker well-being and productivity and was successfully applied in a welding gun use case.

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  • 6.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Scania CV AB, Global Industrial Development, Södertälje, Sweden.
    Lämkull, Dan
    Advanced Manufacturing Engineering, Volvo Car Corporation, Göteborg, Sweden.
    Multi-objective Optimization of Ergonomics and Productivity by Using an Optimization Framework2022In: Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches / [ed] Nancy L. Black; W. Patrick Neumann; Ian Noy, Cham: Springer, 2022, p. 374-378Conference paper (Refereed)
    Abstract [en]

    Simulation technologies are widely used in industry as they enable efficient creation, testing, and optimization of the design of products and production systems in virtual worlds, rather than creating,testing, and optimizing prototypes in the physical world. In an industrial production context, simulation of productivity and ergonomics helps companies to find and realize optimized solutions that uphold profitability, output, quality, and worker well-being in their production facilities. However, these two types of simulations are typically carried out using separate software, used by different users, with different objectives. This easily causes silo effects, leading to slow development processes and sub-optimal solutions. This paper reports on research related to the realization of an optimization framework that enables the concurrent optimization of aspects relating to both ergonomics and productivity. The framework is meant to facilitate the inclusion of Ergonomics 4.0 in the Industry 4.0 revolution.

  • 7.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    García Rivera, Francisco
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Pérez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Scania CV, Södertälje, Sweden.
    Implementation of Ergonomics Evaluation Methods in a Multi-Objective Optimization Framework2020In: DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020 / [ed] Lars Hanson, Dan Högberg, Erik Brolin, Amsterdam: IOS Press, 2020, p. 361-371Conference paper (Refereed)
    Abstract [en]

    Simulations of future production systems enable engineers to find effective and efficient design solutions with fewer physical prototypes and fewer reconstructions. This can save development time and money and be more sustainable. Better design solutions can be found by linking simulations to multiobjective optimization methods to optimize multiple design objectives. When production systems involve manual work, humans and human activity should be included in the simulation. This can be done using digital human modeling (DHM) software which simulates humans and human activities and can be used to evaluate ergonomic conditions. This paper addresses challenges related to including existing ergonomics evaluation methods in the optimization framework. This challenge arises because ergonomics evaluation methods are typically developed to enable people to investigate ergonomic conditions by observing real work situations. The methods are rarely developed to be used by computer algorithms to draw conclusions about ergonomic conditions. This paper investigates how to adapt ergonomics evaluation methods to implement the results as objectives in the optimization framework. This paper presents a use case of optimizing a workstation using two different approaches: 1) an observational ergonomics evaluation method, and 2) a direct measurement method. Both approaches optimized two objectives: the average ergonomics results, and the 90th percentile ergonomics results.

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  • 8.
    Lamb, Maurice
    et al.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brundin, Malin
    University of Skövde, School of Informatics.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Billing, Erik
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Eye-Tracking Beyond Peripersonal Space in Virtual Reality: Validation and Best Practices2022In: Frontiers in Virtual Reality, E-ISSN 2673-4192, Vol. 3, article id 864653Article in journal (Refereed)
    Abstract [en]

    Recent developments in commercial virtual reality (VR) hardware with embedded eye-tracking create tremendous opportunities for human subjects researchers. Accessible eye-tracking in VR opens new opportunities for highly controlled experimental setups in which participants can engage novel 3D digital environments. However, because VR embedded eye-tracking differs from the majority of historical eye-tracking research, in both providing for relatively unconstrained movement and stimulus presentation distances, there is a need for greater discussion around methods for implementation and validation of VR based eye-tracking tools. The aim of this paper is to provide a practical introduction to the challenges of, and methods for, 3D gaze-tracking in VR with a focus on best practices for results validation and reporting. Specifically, first, we identify and define challenges and methods for collecting and analyzing 3D eye-tracking data in VR. Then, we introduce a validation pilot study with a focus on factors related to 3D gaze tracking. The pilot study provides both a reference data point for a common commercial hardware/software platform (HTC Vive Pro Eye) and illustrates the proposed methods. One outcome of this study was the observation that accuracy and precision of collected data may depend on stimulus distance, which has consequences for studies where stimuli is presented on varying distances. We also conclude that vergence is a potentially problematic basis for estimating gaze depth in VR and should be used with caution as the field move towards a more established method for 3D eye-tracking.

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  • 9.
    Lamb, Maurice
    et al.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Pérez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Billing, Erik
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Understanding Eye-Tracking in Virtual Reality2022In: AIC 2022 Artificial Intelligence and Cognition 2022: Proceedings of the 8th International Workshop on Artificial Intelligence and Cognition, Örebro, Sweden, 15-17 June, 2022 / [ed] Hadi Banaee; Amy Loutfi; Alessandro Saffiotti; Antonio Lieto, CEUR-WS.org , 2022, p. 180-181Conference paper (Refereed)
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  • 10.
    Perez Luque, Estela
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Lamb, Maurice
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Challenges for the Consideration of Ergonomics in Product Development in the Swedish Automotive Industry – An Interview Study2022In: DESIGN2022, Cambridge University Press, 2022, Vol. 2, p. 2165-2174Conference paper (Refereed)
    Abstract [en]

    This paper presents an interview study aiming to understand the state of the art of how ergonomics designers work in the vehicle development process within the Swedish automotive industry. Ten ergonomic designers from seven different companies participated in the interview study. Results report the ergonomics designers' objectives, workflow, tools, challenges, and ideal work performance tool. We identify four main gaps and research directions that can enhance the current challenges: human behavior predictions, simulation tool usability, ergonomics evaluations, and integration between systems.

  • 11.
    Perez Luque, Estela
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Lamb, Maurice
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Simulation of hip joint location for occupant packaging design2022In: Proceedings of the 7th International Digital Human Modeling Symposium (DHM 2022), August 29–30, 2022, Iowa City, Iowa, USA, University of Iowa Press, 2022, Vol. 7, p. 1-12, article id 34Conference paper (Refereed)
    Abstract [en]

    DHM tools have been widely used to analyze and improve vehicle occupant packaging and interior design in the automotive industry. However, these tools still present some limitations for this application. Accurately characterizing seated posture is crucial for ergonomic and safety evaluations. Current human posture and motion predictions in DHM tools are not accurate enough for the precise nature of vehicle interior design, typically requiring manual adjustments from DHM users to get more accurate driving and passenger simulations. Manual adjustment processes can be time-consuming, tedious, and subjective, easily causing non-repeatable simulation results. These limitations create the need to validate the simulation results with real-world studies, which increases the cost and time in the vehicle development process. Working with multiple Swedish automotive companies, we have begun to identify and specify the limitations of DHM tools relating to driver and passenger posture predictions given predefined vehicle geometry points/coordinates and specific human body parts relationships. Two general issues frame the core limitations. First, human kinematic models used in DHM tools are based on biomechanics models that do not provide definitions of these models in relation to vehicle geometries. Second, vehicle designers follow standards and regulations to obtain key human reference points in seated occupant locations. However, these reference points can fail to capture the range of human variability. This paper describes the relationship between a seated reference point and a biomechanical hip joint for driving simulations. The lack of standardized connection between occupant packaging guidelines and the biomechanical knowledge of humans creates a limitation for ergonomics designers and DHM users. We assess previous studies addressing hip joint estimation from different fields to establish the key aspects that might affect the relationship between standard vehicle geometry points and the hip joint. Then we suggest a procedure for standardizing points in human models within DHM tools. A better understanding of this problem may contribute to achieving closer to reality driving posture simulations and facilitating communication of ergonomics requirements to the design team within the product development process.

  • 12.
    Perez Luque, Estela
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Iriondo Pascual, Aitor
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Lämkull, Dan
    Global Strategy & Process Development, Volvo Cars, Gothenburg, Sweden.
    Garcia Rivera, Francisco
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Motion Behavior and Range of Motion when Using Exoskeletons in Manual Assembly Tasks2020In: SPS2020: Proceedings of the Swedish Production Symposium, October 7–8, 2020 / [ed] Kristina Säfsten; Fredrik Elgh, Amsterdam: IOS Press, 2020, p. 217-228Conference paper (Refereed)
    Abstract [en]

    The manufacturing industry is becoming increasingly more complex as the paradigm of mass-production moves, via mass-customization, towards personalized production, and Industry 4.0. This increased complexity in the production system also makes everyday work for shop-floor operators more complex. To take advantage of this complexity, shop-floor operators need to be properly supported in order to perform their important work. The shop-floor operators in this future complex manufacturing industry, the Operator 4.0, need to be supported with the implementation of new cognitive automation solutions. These automation solutions, together with the innovativeness of new processes and organizations will increase the competitiveness of the manufacturing industry. This paper discusses three different aspects of production innovation in the context of the needs and preferences of information for Operator 4.0. Conclusively, product innovations can be applied in the manufacturing processes, and thus becoming process innovations, but the implementation of such innovations require organizational innovations.

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  • 13.
    Scataglini, Sofia
    et al.
    University of Antwerp, Faculty of Design Sciences, Department of Product Development, Antwerp, Belgium.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Closing the Gender Gap in DHM2020In: DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020 / [ed] Lars Hanson; Dan Högberg; Erik Brolin, Amsterdam: IOS Press, 2020, p. 408-418Conference paper (Refereed)
    Abstract [en]

    Digital Human Modelling by Women (DHMW) is an international group of women and supporters with the main purpose of eliminating the gender gap, empowering women to exchange ideas, results, visions, and promote the women's participation in the STEM (science, technology, engineering, and math) and DHM fields. This study presents a demographic investigation of human factors and behaviors affecting women in the DHM field. A questionnaire composed of several items was set up to analyze the situation: demographic map of women in DHM (age, country, and level of education), the field of application, factors related to career progression, and correct instruments to change the current situation of underrepresentation. Our results show a gap of women working in the DHM field in the industry or research institutes (21% and 8% respectively). While, the 56% are involved in the Academic world, with a 30% PhD and 26% PostDoc level. Worklife-balance (WLB), career progress (CP), family-balance vs career (FB VS C), and work schedule flexibility (WSF) resulted lower in women of 30-34 and 35-39 years old. As a result, it is necessary to adopt strategies focus on support mentoring programs, career progress, childcare support, and flexible work schedule aiming to eliminate women inequality and stigmatization. This will open up borders in Academics, Industry, and Research education closing the gap in the DHM field.

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