Högskolan i Skövde

Recently the concept of Industry 5.0 has been introduced, reinforcing the human-centric perspective for future industry. The human-centric scientific discipline and profession ergonomics is applied in industry to find solutions that are optimized in regard to both human well-being and overall system performance. It is found, however, that most production development and preparation work carried out in industry tends to address one of these two domains at a time, in a sequential process, typically making optimization slow and complicated. The aim of this paper is to suggest, demonstrate, and evaluate a concept that makes it possible to optimize aspects of human well-being and overall system performance in an efficient and easy parallel process. The concept enables production planning and balancing of human work in terms of two parameters: assembly time as a parameter of productivity (system performance), and risk of musculoskeletal disorders as a parameter of human well-being. A software demonstrator was developed, and results from thirteen test subjects were compared with the traditional sequential way of working. The findings show that the suggested relatively unique parallel approach has a positive impact on the expected musculoskeletal risk and does not necessarily negatively affect productivity, in terms of cycle time and time balance between assembly stations. The time to perform the more complex two-parameter optimization in parallel was shorter than the time in the sequential process. The majority of the subjects stated that they preferred the parallel way of working compared to the traditional serial way of working.

In industry, simulation software is used to simulate production, making it possible to predict events in production, calculate times and plan production, even in the early phases of the production development process. Software known as digital human modelling (DHM) tools can also be used to simulate humans working in production. When simulating digital human models, ergonomics evaluations can be carried out to assess whether workstation designs offer appropriate ergonomic conditions for the workers. However, simulations performed to predict and plan production are usually done separately from the human simulations performed to evaluate ergonomics. This can lead to suboptimal solutions in which a factory is optimized to improve either productivity or ergonomics. This thesis outlines the hypothesis that more optimal solutions for workstation design, layout and line balancing can be obtained in simulations by optimizing productivity and ergonomic factors simultaneously instead of considering them separately. Hence, the aim is to carry out research on the development of a simulation-based multi-objective optimization method for productivity and ergonomic factors and to realize the method as a software tool in order to test and communicate it. From an application and societal-impact perspective, the overall objective is to offer a new approach for designing production systems that focuses on both over-all system performance and the well-being of workers, reduces the effort of engineers and helps industry create more productive and sustainable workspaces.

Simuleringsverktyg används i industrin för att simulera produktion. Det gör det möjligt att förutsäga händelser, uppskatta tider och planera produktionen, även i tidiga stadier av produktionsutvecklingsprocessen. På motsvarande vis används ergonomisimuleringsverktyg för att simulera människor som arbetar i produktionen. Ergonomisimulering kan till exempel utföras för att bedöma om utformningen av arbetsstationen erbjuder lämpliga ergonomiska förhållanden för arbetarna. Emellertid görs produktionssimuleringar vanligtvis separat från ergonomisimuleringar. Det kan leda till bristfälliga lösningar där en fabrik är optimerad för att förbättra antingen produktivitet eller ergonomi. Denna avhandling utgår från hypotesen att mer optimala lösningar för arbetsstationsutformning, layout och linje-balansering kan uppnås i simuleringar genom att samtidigt optimera produktivitetsfaktorer och ergonomiska faktorer istället för att beakta dem separat. Målet är därför att utforska utvecklingen av en simulerings- och flermålsbaserad optimeringsmetod för produktivitetsfaktorer och ergonomiska faktorer och att realisera metoden som ett mjukvaruverktyg för att testa och beskriva den. Ur ett tillämpnings- och samhällspåverkansperspektiv är det övergripande målet att erbjuda ett nytt tillvägagångssätt för att utforma produktionssystem som fokuserar på både systemprestanda och människans välbefinnande, som stödjer ingenjörer i deras dagliga arbete för att hitta goda lösningar, och hjälper industrin att skapa mer produktiva och hållbara arbetsplatser.

The paper reports an investigation conducted during the DHM2020 Symposium regarding current trends in research and application of DHM in academia, software development, and industry. The results show that virtual reality (VR), augmented reality (AR), and digital twin are major current trends. Furthermore, results show that human diversity is considered in DHM using established methods. Results also show a shift from the assessment of static postures to assessment of sequences of actions, combined with a focus mainly on human well-being and only partly on system performance. Motion capture and motion algorithms are alternative technologies introduced to facilitate and improve DHM simulations. Results from the DHM simulations are mainly presented through pictures or animations.

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.

Digital human modelling (DHM) is a tool that allows humans to be modelled in three-dimensional CAD. An almost infinite variety of humans can be modelled and families of so-called manikins can be created to act as virtual user groups, evaluating the interactions between humans and products, workplaces and environments. This chapter introduces the concept of DHM, its use of, and reliance on, anthropometric data from national populations and showcases two exemplar tools in SAMMIE and IPS IMMA. Case studies are presented that highlight the advantages DHM can bring to understanding the requirements of designing for the ageing population; covering designing for the ageing workforce, the exploration of transport accessibility and how users can generate representative manikin families to properly represent the diversity of people. DHM is demonstrated to be a powerful tool for practitioners aiming to understand and design for people, including older people within society.

Work-related musculoskeletal disorders (WMSDs) are often associated with high costs for manufacturing companies and society, as well as negative effects on sustainable working life of workers. To both ensure workers’ well-being and reduce the costs of WMSDs, it is important to consider worker well-being in the design and operations of production processes. To facilitate the simulation of humans in production and improve worker well-being, there are numerous digital human modelling (DHM) tools available on the market. Besides simulation of humans in production, there are numerous production simulation software to simulate production flows of factories, robots and workstations that offer the possibility of improving the productivity of the stations, optimizing the layout and the configuration of the production lines. Despite of the capabilities of DHM and production flow simulation software, there is a lack of tools that can handle an overall optimization perspective, where it is possible to concurrently treat aspects related to both worker well-being and productivity within one tool. This study presents a prescribed tool that enables concurrent multi-objective optimization of worker well-being and productivity in DHM tools by analyzing the impact of different design alternatives. The tool was assessed in a workstation layout optimization use case. In the use case, risk scores of an ergonomics evaluation method was used as a measure of well-being, and total walking distance and workstation area were used as measures of productivity. The results show that the optimized solutions improve both total walking distance, workstation area and ergonomic risk scores compared to the initial solution. This study suggests that the concurrent multi-objective optimization of worker well-being and productivity could generate more optimal solutions for industry and increase the likelihood for a sustainable working life of workers. Therefore, further studies in this field are claimed to be beneficial to industry, society and workers.

Usually, optimizing productivity and optimizing worker well-being are separate tasks performed by engineers with different roles and goals using different tools. This results in a silo effect which can lead to a slow development process and suboptimal solutions, with one of the objectives, either productivity or worker well-being, being given precedence. Moreover, studies often focus on finding the best solutions for a particular use case, and once solutions have been identified and one has been implemented, the engineers move on to analyzing the next use case. However, the knowledge obtained from previous use cases could be used to find rules of thumb for similar use cases without needing to perform new optimizations. In this study, we employed the use of data mining methods to obtain knowledge from a real-world optimization dataset of multi-objective optimizations of worker well-being and productivity with the aim to identify actionable insights for the current and future optimization cases. Using different analysis and data mining methods on the database revealed rules, as well as the relative importance of the design variables of a workstation. The generated rules have been used to identify measures to improve the welding gun workstation design.

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.

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 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.