The growing implementation of ergonomics in the automotive sector sets high demands on Digital Human Modelling (DHM) functionalities towards the simulation of more realistic environments and the reduction of physical model dependency. During the current degree project a leading element that smartly assembles DHM usage (implementation of high-level commanding languages) was designed, revolving around the industries’ needs which were gathered and interpreted in order to organize current functions in this language and suggest new complementary functions that would create a language environment suitable for non-expert users. This was achieved by focusing in an intuitive word-function structure, the proposal of defaults and other tools that aid users with different kinds of expertise. The need for realism of simulations was assessed by the language design especially by designing means to coordinate synchronic manikin-actions. / Virtual Driver

Background: Work-related musculoskeletal disorders (WRMSD) are a disadvantage for companies both from the health and economics view. To reduce them, workstation ergonomics need to be accounted for. Previous ergonomics assessments involved spreadsheets filled and analysed by ergonomists and were regarded as time and resource-consuming, but recent improvements in virtual reality (VR), motion capture (MoCap) and digital human modeling (DHM) tools have open new options for analyses. Workstation redesign is one of the most common ways to improve working conditions, but a proper strategy that allows recording a sequence of actions using VR and assesses ergonomics is needed. Limitations: The strategy was designed for Simumatik, software for virtual commissioning of workstations that wanted to also consolidate itself as a DHM tool. Simumatik and HTC Vive were used as MoCap system and Ergonomics in production platform (EPP) as the assessment tool. Method: Literature review – prestudies and definition of use cases to test strategy and implement in it - requirements and wishes – strategy development – validation of use cases – evaluation. Results: Compared to manual simulations performed manually in IPS IMMA where the user performs same tasks, the strategy output accuracy of 73.3%. However, there are some misinterpretations to fix within the performance of the strategy that would fairly raise it and make the study more realistic, concerning the use cases studied. These mistakes include the posture prediction of the neck and some minor issues with the performance of the use cases. The number of resources vs. development was also studied and it showed that fixing the minor mistakes would raise accuracy close to 80% in the use cases. Adding a chest tracker could make it close to 100% compared to manual simulations in IPS IMMA. Conclusions: The strategy steps were tested and concluded that worked fine, because of the accuracy reached. However, further development of all the parts concerning the strategy is needed. The aim reached was to achieve rough results that could democratize physical ergonomics assessments.

Future manufacturing will be characterized by the complementarity between humans and automation (human-robot collaboration). This requires new methods and tools for the design and operation of optimized manufacturing workplaces in terms of ergonomics, safety, efficiency, complexity management and work satisfaction. There have been some efforts in the recent years to propose a tool for determining optimal human-automation levels for load balancing. Although the topic is quite new, it shares some similarities with some of the existing research in the area of robotic assembly line balancing. Therefore, it is crucial to review the existing literature and find the most similar models and methods to facilitate the development of new optimization models and algorithms. One of the two contributions that this thesis gives to the research world in the RALBP context is a literature review that involves high quality articles from 1993 to beginning 2018. This literature review includes visual and comprehensive tables—and a label system— where previous research patterns and trends are highlighted. Visualization of data and results obtained by assembly line optimization tools is a very important topic that has rarely been studied. Data visualization would provide a: 1. better comprehension of patterns, trends and qualitative data 2. more constructive information absorption 3. better visualization of relationships and patterns between operations, and 4. better contribution to data manipulation and interaction. The second contribution to research found in this thesis is the use of a human modelling (DHM) tool (called IPS), which is proposed as an assessment to the ergonomic risk that a robotic assembly line may involve. This kind of studies are necessary in order to reduce one of the most frequent reasons of work absence in our today society i.e. musculoskeletal disorders (MSDs). MSDs are often the result of poor work environments and they lead to reduced productivity and quality losses at companies. In view of the above, IPS was used in order to resolve the load handling problem between human and robot, depending on their skills and availability, while fulfilling essential ISO standards i.e. 15066 and 10218:1 and :2. The literature review made it possible to select highly useful documents in developing assumptions for the experiment and contributed to consider real features detected in the industry. Results show that even though IPS is not capable of calculating an entire robotic assembly with human-robot collaboration, it is able to simulate a workstation constituted of one robot and one human. Finite and assembly motions for both human and robot are expected to be implemented in future versions of the software. Finally, the main advantages of using DHM tools in assessing ergonomic risks in RALB can be extracted from the results of this thesis. This advantages include 1. ergonomic evaluation for assembly motions 2. ergonomic evaluation for a full working day (available in future version) and 3. essential ISO standard testing (available in future version).

Contemporary product and production development is typically carried out with the support of computer tools where the design of products and workstations are originated and evaluated within virtual environments. Ergonomics addresses factors important to consider in the product and production development process to ensure a good fit between humans and the items being designed. Digital human modelling (DHM) tools enable simulations and analyses of ergonomics in virtual environments. Anthropometry is central when using DHM tools for product and production development to ensure that the design fits the intended proportion of the targeted population from a physical perspective. Several methods have been prescribed to consider the anthropometric diversity that exists within human populations. Still many DHM based simulations in product and production development processes are done with approaches that are poor in representing anthropometric diversity. Hence, there is a need for better tools and methods that would support DHM tool users to more effectively and efficiently consider anthropometric diversity in the design process. In this thesis current methods for anthropometric diversity considerations have been reviewed and new methods and functionality have been developed and implemented in a DHM tool. Mathematical models have been developed to consider three specific parts important to the consideration of anthropometric diversity: generation of suitable test cases, prediction of missing anthropometric data and implementation of more diverse anthropometric variables such as strength and flexibility. Results show that the proposed methods are accurate and advantageous compared to approaches often used in industry today. The mathematical models for generation of suitable test cases and prediction of missing anthropometric data have been implemented in an anthropometric software module. The module has undergone usability testing with industry DHM tools users. The developed anthropometric module is shown to answer to relevant needs of DHM tool users and fit into the work processes related to DHM simulations and ergonomics analyses utilised in industry today.

Introduction: External support behaviours, which include leaning (supporting with the non-task hand) or bracing (supporting with the body), are frequently employed by workers in manufacturing settings. However, current ergonomic assessment tools are limited by our limited understanding of these behaviours. Recent studies have investigated these behaviours, however, the designs of these studies are limited in their applicability to real-world scenarios. The purpose of this study was to assess how different task parameters affect the prediction of external support behaviours, as well as the effect of support on task hand, and body, kinematics and kinetics, in a minimally constrained experimental design. Methods: Female participants (n = 18) performed a series of one-handed maximal exertions (in the six orthogonal directions), and one precision task, in four hand Locations. Trials either featured support (as chosen by the participant), or no support. Results & Discussion: Three logistic regression models were developed, with inputs from individual and task characteristics, and they correctly predicted the occurrence of leaning, bracing, or simultaneous leaning and bracing, 74-86% of the time. Leaning and/or bracing were found to provide: 1) oppositional forces to increase task hand force generation, 2) balance, by countering destabilizing moments about the feet, and 3) a reduction in moment arm of the task hand force, with respect to the upper body joints, by bringing the shoulder closer to the task hand. Participants were able to exert 64.8% more force at the task hand as a result of support. Leaning hand placement depended on the task force direction and location. However, the positioning of the leaning hand varied very little. Finally, the precision condition showed that fine motor demands may also affect external support choice. / Thesis / Master of Science in Kinesiology

Nowadays virtual simulations are commonly used to solve problems regarding worker well-being or productivity in manufacturing companies. However, when it comes to finding a solution to one of these two objectives, the other usually tends to be secondary. In order to solve this problem, the Ergonomics in Production Platform (EPP) has been developed within research efforts at University of Skövde, which through the use of optimizations is able to obtain solutions where both objectives are taken into account. In turn, in order to address worker well-being, EPP makes use of the digital human modelling (DHM) tool. DHM tools are often used to evaluate simulations focused on studying human-machine interaction. However, as these software evolve and start to be able to reproduce complete motions, before they were only considering frames, new methods are needed to be able to assess risk factors such as time and prevent the occurrence of musculoskeletal disorders (MSDs). In order to assist in the development of EPP optimizations for simulations carried out in DHM tools, the time-based observational method RAMP was implemented, specifically the posture-related criteria of RAMP II. Using the Design and Creation research methodology, a welding gun case study located in China offered by Volvo Cars was used to evaluate the results of the optimizations carried out with EPP. For the evaluation of this case study, a manikin family of 10 members representing key cases of the Asian population was created for this task. Later, this task was recreated in IPS IMMA, where the 10 cases interacted with 3 welding guns to weld different spots on a piece. The analysis of this case study consisted of two distinct phases where the results of RAMP II implemented in EPP could be evaluated. The first phase focused on analyzing initial results of three different trajectories for all members of the family. The second phase consisted of optimizing one of the trajectories analyzed in the previous phase in such a way as to find the best welding angle of the gun to improve the results of the worst case in the first analysis. Three different factors were evaluated in this phase: RAMP II results versus the new angle, RAMP II results versus the results of other methods and the effect of productivity versus worker well-being. The results showed that welding angles of 116º and 80º were able to improve the values of the RAMP II criteria for the most disadvantaged manikin in the welding task. At the same time, it was observed that the higher the percentage of value added time, the higher the risk obtained in the analysis, worsening the worker's well-being.

Future manufacturing will be characterized by the complementarity between humans and automation (human-robot collaboration). This requires new methods and tools for the design and operation of optimized manufacturing workplaces in terms of ergonomics, safety, efficiency, complexity management and work satisfaction. There have been some efforts in the recent years to propose a tool for determining optimal human-automation levels for load balancing. Although the topic is quite new, it shares some similarities with some of the existing research in the area of robotic assembly line balancing. Therefore, it is crucial to review the existing literature and find the most similar models and methods to facilitate the development of new optimization models and algorithms. One of the two contributions that this thesis gives to the research world in the RALBP context is a literature review that involves high quality articles from 1993 to beginning 2018. This literature review includes visual and comprehensive tables—and a label system— where previous research patterns and trends are highlighted. Visualization of data and results obtained by assembly line optimization tools is a very important topic that has rarely been studied. Data visualization would provide a: 1. better comprehension of patterns, trends and qualitative data 2. more constructive information absorption 3. better visualization of relationships and patterns between operations, and 4. better contribution to data manipulation and interaction. The second contribution to research found in this thesis is the use of a human modelling (DHM) tool (called IPS), which is proposed as an assessment to the ergonomic risk that a robotic assembly line may involve. This kind of studies are necessary in order to reduce one of the most frequent reasons of work absence in our today society i.e. musculoskeletal disorders (MSDs). MSDs are often the result of poor work environments and they lead to reduced productivity and quality losses at companies. In view of the above, IPS was used in order to resolve the load handling problem between human and robot, depending on their skills and availability, while fulfilling essential ISO standards i.e. 15066 and 10218:1 and :2. The literature review made it possible to select highly useful documents in developing assumptions for the experiment and contributed to consider real features detected in the industry. Results show that even though IPS is not capable of calculating an entire robotic assembly with human-robot collaboration, it is able to simulate a workstation constituted of one robot and one human. Finite and assembly motions for both human and robot are expected to be implemented in future versions of the software. Finally, the main advantages of using DHM tools in assessing ergonomic risks in RALB can be extracted from the results of this thesis. This advantages include 1. ergonomic evaluation for assembly motions 2. ergonomic evaluation for a full working day (available in future version) and 3. essential ISO standard testing (available in future version).

The focus of the present work is natural human like grasping, for realistic performance simulations in digital human modelling (DHM) environment. The performance simulation for grasping in DHM is typically done through high level commands to the digital human models (DHMs). This calls for a natural and unambiguous scheme to describe a grasp which would implicitly accommodate variations due to the hand form, object form and hand kinematics. A novel relational description scheme is developed towards this purpose. The grasp is modelled as a spatio-temporal relationship between the patches (a closed region on the surface) in the hand and the object. The task dependency of the grasp affects only the choice of the relevant patches. Thus, the present scheme of grasp description enables a human like grasp description possible. Grasping can be simulated either in an interactive command mode as discussed above or in an autonomous mode. In the autonomous mode the patches have to be computed. It is done using a psychological concept, of affordance. This scheme is employed to select a tool from a set of tools. Various types of grasps a user may adopt while grasping a spanner for manipulating a nut is simulated. Grasping of objects by human evolves through distinct naturally occurring phases, such as re-oreintation, transport and preshape. Hand is taken to the object ballpark using a novel concept of virtual object. Before contact establishment hand achieves the shape similar to the global shape of the object, called preshaping. Various hand preshape strategies are simulating using an optimization scheme. Since the focus of the present work is human like grasping, the mechanism which drives the DHMs should also be anatomically pertinent. A methodology is developed wherein the hand-object contact establishment is done based on the anatomical observation of logarithmic spiral pattern during finger flexion. The effect of slip in presence of friction has been studied for 2D and 3D object grasping endeavours and a computational generation of the slip locus is done. The in-grasp slip studies are also done which simulates the finger and object response to slip. It is desirable that the grasping performance simulations be validated for diverse hands that people have. In the absence of an available database of articulated bio-fidelic digital hands, this work develops a semi-automatic methodology for developing subject specific hand models from a single pose 3D laser scan of the subject's hand. The methodology is based on the clinical evidence that creases and joint locations on human hand are strongly correlated. The hand scan is segmented into palm, wrist and phalanges, both manually and computationally. The computational segmentation is based on the crease markings in the hand scan, which is identified by explicitly painting them using a mesh processing software by the user. Joint locations are computed on this segmented hand. A 24 dof kinematic structure is automatically embedded into the hand scan. The joint axes are computed using a novel palm plane normal concept. The computed joint axes are rectified using the convergence, and intra-finger constraints. The methodology is significantly tolerant to the noise in the scan and the pose of the hand. With the proposed methodology articulated, realistic, custom hand models can be generated. Thus, the reported work presents a geometric framework for comprehensive simulation of grasping performance in a DHM environment.