Högskolan i Skövde

Driver-vehicle interaction analyses are done to ensure a successful vehicle design from an ergonomics perspective. Digital Human Modelling (DHM) tools are often used to support such verifications, particularly at early stages of the product development process. When verifying that a vehicle design accommodates the diversity of users and tasks, a DHM tool needs to be able to represent postures and motions that are likely under certain conditions. This functionality is essential so that the tool user will obtain objective and repeatable simulation results. The DHM tool IMMA (Intelligently Moving Manikins) predicts postures and motions by using computational methods. This offers the possibility to generate postures and motions that are unique for the present design conditions. IMMA was originally developed for simulating manual assembly work, whereas the work presented here is a step towards utilizing the IMMA tool for occupant packaging and related tasks. The objective is a tool for virtual verification of driver-vehicle interaction that supports and automates the simulation work to a high degree. The prediction functionality in IMMA is based on the use of optimization algorithms where one important component is the consideration of comfort level. This paper reports results from an basic investigation of driving postures and available comfort models suitable in a driving context, and shows initial results of seated posture and motion prediction functionality in the IMMA tool.

Driver-vehicle interaction analyses are done to ensure a successful vehicle design from an ergonomics perspective. Digital Human Modelling (DHM) tools are often used to support such verifications, particularly at early stages of the product development process. When verifying that a vehicle design accommodates the diversity of users and tasks, a DHM tool needs to be able to represent postures and motions that are likely under certain conditions. This functionality is essential so that the tool user will obtain objective and repeatable simulation results. The DHM tool IMMA (Intelligently Moving Manikins) predicts postures and motions by using computational methods. This offers the possibility to generate postures and motions that are unique for the present design conditions. IMMA was originally developed for simulating manual assembly work, whereas the work presented here is a step towards utilizing the IMMA tool for occupant packaging and related tasks. The objective is a tool for virtual verification of driver-vehicle interaction that supports and automates the simulation work to a high degree. The prediction functionality in IMMA is based on the use of optimization algorithms where one important component is the consideration of comfort level. This paper reports results from an basic investigation of driving postures and available comfort models suitable in a driving context, and shows initial results of seated posture and motion prediction functionality in the IMMA tool.

Manufacturing corporations sometimes use corporate-internal procedures to evaluate and monitor the ergonomic status of the workplace. This article describes an industrial case study in the Swedish automotive sector, where an internally developed evaluation procedure was compared with a procedure based on a Swedish national standard provision.

It was found that the national standard procedure tended to give more severe ratings and statistical support shows that the two evaluation procedures are not equivalent. The ability of the methods to identify body segments at risk was also compared.

The quantitative comparison was followed up with interviews, where the influence of professional tasks and objectives became evident, as well as the fact that evaluation criteria are quantified differently by the two procedures. The main finding is that unforeseen differences in analysis procedure, criteria of acceptability and levels of detail can cause use-related difficulties for different professional groups when methods are used interchangeably.

Relevance to industry: Industrial corporations wishing to monitor ergonomics consistently are advised by the authors to ensure that ratings from internal evaluations are interpreted the same way by all involved personnel, and that they at least have criteria levels equivalent to those of a national standard.

Anthropometry, the study of human measurements, is central in the design of products and workplaces. This paper describes how Swedish anthropometric data is made available through a web page (www.antropometri.se) intended to be used by designers and engineers when developing new products and workplaces. With the anthropometric web resource it is possible to get mean and standard deviation values, and to calculate percentile values, for a number of anthropometric measurements. Further functionality on the web page enables simultaneous consideration of several anthropometric measurements. The web page also contains guidelines for how to use anthropometric data depending on the design task at hand.

Digital human modelling (DHM) systems are used to simulate production processes and analyse the human-machine interaction, particularly at early development stages. Consideration of anthropometric variation is central in DHM simulations due to the necessity of ensuring intended accommodation levels. This paper describes the process of how digital human models are created and defined within the IMMA software. The process begins with the definition of a number of key measurements, which acts as the basis for the definition of several boundary manikins using a confidence ellipsoid methodology. These manikins represents the appropriate confidence region and hence the anthropometric diversity. Key measurements are then entered into regression equations to define the complete set of measurements for each manikin. These measurements are based on the appropriate ISO-standard. Finally, measurements are used to define the size and alignment of each segment in the biomechanical model of the manikin. The manikins are then used to automatically simulate and analyse human-machine interaction.

In digital human modelling (DHM), ergonomics evaluations are typically done with few human models. However, humans vary a lot in sizes and shapes. Therefore, few manikins can rarely ensure accommodation of an entire target population. Different approaches exist on how to consider anthropometric diversity. This paper reviews current  DHM  tools  and  clarify  problems  and  opportunities  when  working  with anthropometric diversity. The aim is to suggest  functionality  for a state of the art DHM  module  and  work  process  for  considering  anthropometric  diversity.  The study is done by an analysis of some of the current DHM systems and by interviews of  personnel  at  car  companies  about  their  way  of  working  with  anthropometric diversity. The study confirmed that critical production simulations are often done in early development stages with only one or a few human models. The reason for this is claimed to be time consuming processes, both at the creation of the human model but  mainly  when  correctly  positioning  the  model  in  the  CAD  environment.  The development  of  a  new  method  and  work  process  for  considering  anthropometric diversity is suggested. Necessary features for such a module are that it shall be easy to use and not require expert knowledge about the consideration of anthropometric diversity. It shall also be configurable and transparent, in a sense that it should be possible  to  work  with  own  anthropometric  data  and  ergonomics  evaluation standards. The module has to be flexible and have different entrances depending on the type of anthropometric problem being analyzed. An improved work method is expected to lead to faster and more correct analyses.

In digital human modelling (DHM), ergonomics evaluations are typically done with few human models. However, humans vary a lot in sizes and shapes. Therefore, few manikins can rarely ensure accommodation of an entire target population. Different approaches exist on how to consider anthropometric diversity. This paper reviews current  DHM  tools  and  clarify  problems  and  opportunities  when  working  with anthropometric diversity. The aim is to suggest  functionality  for a state of the art DHM  module  and  work  process  for  considering  anthropometric  diversity.  The study is done by an analysis of some of the current DHM systems and by interviews of  personnel  at  car  companies  about  their  way  of  working  with  anthropometric diversity. The study confirmed that critical production simulations are often done in early development stages with only one or a few human models. The reason for this is claimed to be time consuming processes, both at the creation of the human model but  mainly  when  correctly  positioning  the  model  in  the  CAD  environment.  The development  of  a  new  method  and  work  process  for  considering  anthropometric diversity is suggested. Necessary features for such a module are that it shall be easy to use and not require expert knowledge about the consideration of anthropometric diversity. It shall also be configurable and transparent, in a sense that it should be possible  to  work  with  own  anthropometric  data  and  ergonomics  evaluation standards. The module has to be flexible and have different entrances depending on the type of anthropometric problem being analyzed. An improved work method is expected to lead to faster and more correct analyses.

When evaluating human-machine interaction it is central to consider anthropometric diversity to ensure intended accommodation levels. A well-known method is the use of boundary cases where manikins with extreme but likely measurement combinations are derived by mathematical treatment of anthropometric data. The supposition by that method is that the use of these manikins will facilitate accommodation of the expected part of the total, less extreme, population. In literature sources there are differences in how many and in what way these manikins should be defined. A similar field to the boundary case method is the use of experimental design in where relationships between affecting factors of a process is studied by a systematic approach. This paper examines the possibilities to adopt methodology used in experimental design to define a group of manikins. Different experimental designs were adopted to be used together with a confidence region and its axes. The result from the study shows that it is possible to adapt the methodology of experimental design when creating groups of manikins. The size of these groups of manikins depends heavily on the number of key measurements but also on the type of chosen experimental design.

Boundary manikins, the concept of creating statistically extreme cases to accommodate a big part of the less extreme population has been known for decades. Despite this, many ergonomics simulations are done with few human models. This fact can be explained by the time consuming processes when working with many manikins in current digital human modelling (DHM) tools, but may also be a result of difficulty to understand how these manikins are calculated and defined. This paper focuses on the method of defining boundary manikins and how that functionality can be integrated into a DHM tool. Examples of boundary case methods in the literature often use Principal Component Analysis (PCA) which makes it possible to reduce the dimensions of the problem without much loss of the variance of the analysed data. Using PCA often demands some extent of manual analysis at the critical stage of reducing dimensions. This paper will explain a similar methodology for ceating boundary manikins from any number of variables, i.e. anthropometric variables chosen as key measurements. This method of creating a group of manikins is intended to be used in an automatic simulation feature in the IMMA software being developed in the associated research project. By using the method, a confidence region in the standardized space is created from eigenvectors and scaled eigenvalues of a correlation matrix. Boundary manikins are chosen at the ends of the axes of the enclosing confidence region, and one manikin of mean values is also added to the group of manikins. In the method presented here, the number of manikins created depends directly on the number of variables, which lead to the fact that the decision making of which key measurements to consider has to be done carefully to not create an overwhelming number of manikins. In comparison with one method using PCA, the method presented in this paper creates more manikins with a bigger difference in the max and min values of the chosen key measurements. If a limited number of cases are of crucial interest, then using PCA to reduce the dimensions of the problem is a good method to use. But if it is possible to create automated simulations the limitation of the number of manikins might not be so important. This will, though, depend heavily on the speed of the automated simulations.

When evaluating human-machine interaction in a virtual environment using Digital human modelling (DHM) it is important to ensure that the predicted motions lie within the range of behavioural diversity for different people within a population. This paper presents a study in which a comparison is made between motions predicted by the DHM tool IMMA (Intelligently Moving Manikin) and motions from real humans stored in a motion database. Results show similar motions but the predicted motions were in total statistically significantly different compared to the motions performed by real persons. The differences are most likely due to the balance function and joint constraints that the IMMA tool uses for predicting motions. Differences can also be due to other factors, aside of body size, such as age, gender or strength that affects the movement behaviour.

This  paper  study  and  clarify  problems,  needs  and  opportunities  when  working  with anthropometric  diversity  in  digital  human  modelling  (DHM)  systems.  A  comparison between  product  development  and  production  development  in  Swedish  automotive industry is made. Interviews with DHM users and ergonomics specialists about their way of working with anthropometric diversity confirmed that simulations are often done with only one or  a  few  human models.  The reason for  this  is  claimed  to  be  time  consuming processes, both at the creation of the human model but mainly when correctly positioning the model in the CAD environment.

In this paper we present a framework for digital human modelling using discrete mechanics and optimal control. Discrete mechanics is particularly well suited for modelling the dynamics of constrained mechanical systems, which is almost always the case when considering complex human models interacting with the environment. We demonstrate that, by using recently developed recursive dynamics algorithms, we are able to efficiently use discrete mechanics in direct optimal control methods to plan for complex motions. Besides a proper mechanical model, an appropriate objective function is paramount to achieve realistic motions as a solution to an optimal control problem. Hence, several different objective functions, such as for example minimum time or minimum applied torque over the joints, are compared, and the resulting motions are analyzed and evaluated. To further improve the model, we include basic muscular models for the muscles of the shoulder, arm and wrist, and examine how this affects the motions.

The aim of the present case study is to present and evaluate a computer-based standardized procedure to order, perform and document virtual ergonomic analyses. Results showed that the use of the new working methodology increased the number of factors considered during analysis. Participants indicated that the proposed methodology, including task analysis and use of manikin families, would increase the reliability of the results. The increase in numbers of factors considered during analysis and the improved reliability of the results is also likely to reduce the number of iterations needed in the design process to make products meet established requirements, therefore reducing total development time.

Developers, reviewers and users of human simulation tools claim that the use of these tools may reduce development time and development cost. However, before these benefits will be fully visible, there are some barriers to overcome. The aims of this case study are to identify which departments at Saab Automobile use some sort of human simulation tool today, and to identify the information flow and procedure when the tool is used. Four departments crash safety, packaging, production planning and vehicle ergonomics were identified as direct users of human simulation tools. The tools used were finite element with crash dummy representation, SAE human model, Safework and Ramsis. Communications between human simulation tool users are limited. Communications are done through the project management. The crash safety and packaging departments have formal descriptions of the human simulation process, whereas production planning and vehicle ergonomics have no formal process descriptions. To gain from the benefits of human simulation tools, Saab Automobile needs to adapt them to the organization and the organization to the tools. Integration of a working methodology is essential for effective and efficient use in the other human simulation departments where this is currently lacking.

The purpose of the research project described in this paper is to improve the efficiency of product development processes by exchanging knowledge and experiences about user centred design methods and technologies between the two branches: vehicle and health care industries. The health care industry can benefit from visualisation and simulation tools that include computer manikins, a physical representation of the human, and the vehicle industry can benefit from manikins having personal characteristics, which has proven to be successful in the health care industry.

The aim of this study was to identify and measure time-consuming human modelling tool activities. Five human modelling tool users at Volvo were observed for five days each. The results showed a wide distribution of both indirect and direct working tasks, as well as non-value added tasks such as waiting time. Most of the activities identified appear to be necessary to perform human modelling simulations of high quality. However, the time distribution could be questioned to some extent. There are many activities associated with communication, including a variety of contacts and meetings, where there appears to be potential to increase efficiency.

Vi har genomfört genomgripande förändringar i obligatoriska grundkurser i arbetsvetenskap. Förändringarna har genomförts som en utvecklingsprocess i vilken samtliga lärare som deltagit i kurserna har medverkat. Processen startade med konsulthjälp från Universitetspedagogiskt centrum vid Lunds universitet, fortsatte med kompetensutveckling av oss själva och följdes av några utvecklingsprojekt, varefter från grunden förändrade kurser genomfördes under fyra år. Den nya uppläggningen medförde att vi fick positiva attityder i studentenkäterna när det gällde två av kurserna i årskurs 2 i vilken medodiken genomfördes fullständigt. I en kurs, som gavs i årskurs 1 och i vilken den nya uppläggningen endast delvis genomfördes blev studentattityderna negativa.

Effective simulation of manual assembly operations considering ergonomic load and clearance demands requires detailed modeling of human body kinematics and motions, as well as a tight coupling to powerful algorithms for collision-free path planning. The focus in this paper is a unified solution that automatically creates assembly motions for manikins taking kinematic constraints, balance, contact forces, collision avoidance and comfort into account. The manikin used in this work has 162 degrees of freedom - six exterior fictitious joints determine the position of the lower lumbar and the remaining ones are interior joints. The inverse kinematic problem leads to an underdetermined system allowing us to pick a solution that maximizes a scalar valued comfort function. The comfort function offers a generic way to give preference to certain poses while avoiding others, typically by considering joint limits, forces and moments on joints, and magnitude of contact forces. In order to avoid collisions, poses close to collision are penalized. The method is implemented and demonstrated on two challenging assembly operations taken from the automotive industry.

Simulating manual assembly operations considering ergonomic load and clearance demands requires detailed modeling of human body kinematics and motions, as well as a tight coupling to powerful algorithms for collision-free path planning. The focus in this paper is kinematics including balance and contact forces, and ergonomically preferable motions in free space. A typical manikin has more than 100 degrees of freedom. To describe operations and facilitate motion generation, the manikin is equipped with coordinate frames attached to end-effectors like hands and feet. The inverse kinematic problem is to find joint values such that the position and orientation of hands and feet matches certain target frames during an assembly motion. This inverse problem leads to an underdetermined system of equations since the number of joints exceeds the end-effectors' constraints. Due to this redundancy there exist a set of solutions, allowing us to consider ergonomics aspects and maximizing comfort when choosing one solution.The most common approach to handle both forward and inverse kinematics is building a hierarchy of joints and links where one root must be defined. A popular place to define the root is in a body part, e.g. in a foot. This leads to a two-step procedure; (i) one level determining when to re-root when moving the root part, (ii) then the Penrose pseudoinverse is used to match the end-effectors' constraints.In this paper we propose using a fixed exterior root by introducing six additional parameters positioning the lower lumbar - three rotations and three translations. This makes it possible to reposition the manikin without a series of re-rooting operations. Another important aspect is to keep the manikin, affected by internal and external forces and moments, in balance. However, by utilizing the exterior root and its added degrees of freedom it is possible to solve the balance, positioning, contact force and comfort problems simultaneously in a unified way. A manikin was implemented, and two test cases demonstrate the applicability of the presented method.

This paper presents the development of body-shape-data-based digital human models, i.e. manikins, for ergonomics simulations. In digital human modeling (DHM) tools, it is important that the generated manikin models are accurate and representative for different body sizes and shapes as well as being able to scale and move during motion simulations. The developed DHM models described in this paper are based on body scan data from the CAESAR anthropometric survey. The described development process consists of six steps and includes alignment of body scans, fitting of template mesh through homologous body modeling, statistical prediction of body shape, joint centre prediction, adjustment of posture to T-pose, and, finally, generation of a relation between predicted mesh and manikin mesh. The implemented method can be used to create any type of manikin size that can be directly used in a simulation. To evaluate the results, a comparison was done of original body scans and statistically predicted meshes generated in an intermediary step, as well as the resulting DHM manikins. The accuracy of the statistically predicted meshes are relatively good, even though differences can be seen, mostly related to postural differences and differences around smaller areas with distinct shapes. The biggest differences between the final manikin models and the original scans can be found in the shoulder and abdominal areas, in addition to the significantly different initial posture that the manikin models have. To further improve and evaluate the generated manikin models, additional body scan data sets that include more diverse postures would be useful. DHM tool functionality could also be improved to enable evaluation of the accuracy of the generated manikin models, possibly resulting in DHM tools that are more compliant with standard documents. At the same time, standard documents might need to be updated in some aspects to include more three-dimensional accuracy analysis.

Digital human modelling (DHM) systems can be used to simulate production processes and analyse the human-machine interaction, particularly at early design stages. The human-machine interaction is affected and limited by factors or characteristics belonging to the human user and the machine or product but also the surrounding environment. DHM systems consider in most cases only physical user capabilities and with focus on consideration of body size related anthropometric diversity. However, the human-machine interaction is not only affected by the size and proportions of a user but for example also the user´s muscle strength and range of motion (ROM). This paper describes a study where diversity in strength and ROM, together with diversity in body size, is implemented in the process of creating data for a group of human arm models. A literature study was done to investigate the diversity of strength and ROM and the correlation between such measurements and body size data. The results from the literature study showed that there is little correlation between body size, strength and ROM. The study also showed that there are few published studies where body size, strength and ROM have been tested at the same time. From the literature study, generic correlation coefficients between body size, strength and ROM were synthesized. Using these correlation coefficients and Principal Component Analysis, data for a group of 14 female arm models with varying body size, strength and ROM were calculated. The results show that it is possible to introduce additional variables such as strength and ROM, but also that data of the correlation between body size and other types of anthropometric measurements are scarce. New measurement studies are important to decrease the uncertainties when predicting correlation coefficients between body size, strength and ROM variables.

In digital human modelling (DHM) systems consideration of anthropometry is central. Important functionality in DHM tools is the regression model, i.e. the possibility to predict a complete set of measurements based on a number of defined independent anthropometric variables. The accuracy of a regression model is measured by how well the model predicts dependent variables based on independent variables, i.e. known key anthropometric measurements. In literature, existing regression models often use stature and/or body weight as independent variables in so-called flat regressions models which can produce estimations with large errors when there are low correlations between the independent and dependent variables. This paper suggests a conditional regression model that utilise all known measurements as independent variables when predicting each unknown dependent variable. The conditional regression model is compared to a flat regression model, using stature and weight as independent variables, and a hierarchical regression model that uses geometric and statistical relationships between body measurements to create specific linear regression equations in a hierarchical structure. The accuracy of the models is assessed by evaluating the coefficient of determination, R² and the root-mean-square deviation (RMSD). The results from the study show that using a conditional regression model that makes use of all known variables to predict the values of unknown measurements is advantageous compared to the flat and hierarchical regression models. Both the conditional linear regression model and the hierarchical regression model have the advantage that when more measurements are included the models will give a better prediction of the unknown measurements compared to the flat regression model based on stature and weight. A conditional linear regression model has the additional advantage that any measurement can be used as independent variable. This gives the possibility to only include measurements that have a direct connection to the design dimensions being sought. Utilising the conditional regression model would create digital manikins with enhanced accuracy that would produce more realistic and accurate simulations and evaluations when using DHM tools for the design of products and workplaces.

This paper describes and evaluates the boundary case methodology for the simultaneous consideration of variance for a number of selected anthropometric variables. The methodology includes the calculation of key dimension values for extreme but likely anthropometric measurement combinations. This data can be applied when utilising digital human modelling (DHM) tools for proactive design work and entered as input data when representative manikins are defined. The mathematical procedure is clearly described and exemplified to demonstrate how to use the methodology in design work. The outcome of the method is illustrated and compared using several different cases where the number of measurements is varied and where principal component analysis (PCA) is used to reduce the number of dimensions in one case. The paper demonstrates that the proposed boundary case method is advantageous compared to approaches based on the use of univariate percentile data in design.

Some anthropometric measurements, such as body weight often show a positively skewed distribution. Different types of transformations can be applied when handling skewed data in order to make the data more normally distributed. This paper presents and visualises how square root, log normal and, multiplicative inverse transformations can affect the data when creating boundary confidence ellipses. The paper also shows the difference of created manikin families, i.e. groups of manikin cases, when using transformed distributions or not, for three populations with different skewness. The results from the study show that transforming skewed distributions when generating confidence ellipses and boundary cases is appropriate to more accurately consider this type of diversity and correctly describe the shape of the actual skewed distribution. Transforming the data to create accurate boundary confidence regions is thought to be advantageous, as this would create digital manikins with enhanced accuracy that would produce more realistic and accurate simulations and evaluations when using DHM tools for the design of products and workplaces.

This paper describes a study where diverse anthropometric data is included in the process of generating data for a group of virtual test persons. Data on body size, strength and ROM were either collected on an individual level or predicted and synthesized and then used in cluster analyses to generate six unique virtual test persons. Results show that the method is able to generate detailed virtual test persons which enables more realistic and accurate simulations, as strength and ROM data is included into the motion prediction algorithms used to generate motions.

This paper presents and evaluates an adaptive linear regression model for the prediction of unknown anthropometric data based on a flexible set of known predictive data. The method is based on conditional regression and includes use of principal component analysis to reduce effects of multicollinearity between the predictive variables. Results from the study show that the proposed adaptive regression model produces more accurate predictions compared to a flat regression model based on stature and weight, and also compared to a hierarchical regression model, that uses geometric and statistical relationships between body measurements to create specific linear regression equations in a hierarchical structure. An additional evaluation shows that the accuracy of the adaptive regression model increases logarithmically with the sample size. Apart from the sample size, the accuracy of the regression model is affected by the number of, and on which measurements that are, variables in the predictive dataset.

This paper presents the development of an adaptive linear regression model for synthesizing of missing anthropometric population data based on a flexible set of known predictive data. The method is based on a conditional regression model and includes use of principal component analysis, to reduce effects of multicollinearity between selected predictive measurements, and incorporation of a stochastic component, using the partial correlation coefficients between predicted measurements. In addition, skewness of the distributions of the dependent variables is considered when incorporating the stochastic components. Results from the study show that the proposed regression models for synthesizing population data give valid results with small errors of the compared percentile values. However, higher accuracy was not achieved when the number of measurements used as independent variables was increased compared to using only stature and weight as independent variables. This indicates problems with multicollinearity that principal component regression were not able to overcome. Descriptive statistics such as mean and standard deviation values together with correlation coefficients is sufficient to perform the conditional regression procedure. However, to incorporate a stochastic component when using principal component regression requires raw data on an individual level.

Relevance to industry

When developing products, workplaces or systems, it is of great importance to consider the anthropometric diversity of the intended users. The proposed regression model offers a procedure that gives valid results, maintains the correlation between the measurements that are predicted and is adaptable regarding which, and number of, predictive measurements that are selected.

This paper presents the development of a software module and a graphical user interface which aims to support the definition of anthropometry of manikins in a digital human modelling (DHM) tool. The module is developed from user interviews and literature studies, as well as mathematical methods for anthropometric diversity consideration. The module has functionality to create both single manikins and manikin families, where it is possible to combine or analyse different population datasets simultaneously. The developed module and its interface have been evaluated via focus group interviews and usability tests by DHM tool users. Results from the studies show that the developed module and its interface has relevant functionality, fits well into industrial work processes, and is easy to use. The study also identifies possibilities to further increase usability.

This paper describes a study where diversity in body size, strength and joint range of motion, together with diversity in other capability measurements, is included in the process of generating data for a group of test cases using cluster analysis. Descriptive statistics and correlation data was acquired for 15 variables for different age groups and both sexes. Based on this data, a population of 10,000 individuals was synthesised using correlated random numbers. The synthesised data was used in cluster analyses where three different clustering algorithms were applied and evaluated; hierarchical clustering, k-means clustering and Gaussian mixture distribution clustering. Results from the study show that the three clustering algorithms produce groups of test cases with different characteristics, where the hierarchical and k-means algorithm give the most diverse results and where the Gaussian mixture distribution gives results that are in between the first two.

This paper identifies and describes product development activities where ergonomics issues could be considered and illustrates how that could be done through a number of different approaches. The study is divided into two parts where an interview study is done to identify where in a product development process consideration of ergonomics issues are or could be done. The second part of the study includes an observation, motion capture and simulation study of current manufacturing operations to evaluate and compare three different assessment approaches; observational based ergonomics evaluation, usages of motion capture data and DHM simulation and evaluation. The results shows the importance of consideration of ergonomics in early development phases and that the ergonomics assessment process is integrated in the overall product and production development process.

Although the degree of automation is increasing in manufacturing industries, many assembly operations are performed manually. To avoid injuries and to reach sustainable production of high quality, comfortable environments for the operators are vital. Poor station layouts, poor product designs or badly chosen assembly sequences are common sources leading to unfavorable poses and motions. To keep costs low, preventive actions should be taken early in a project, raising the need for feasibility and ergonomics studies in virtual environments long before physical prototypes are available. Today, in the automotive industries, such studies are conducted to some extent. The full potential, however, is far from reached due to limited software support in terms of capability for realistic pose prediction, motion generation and collision avoidance. As a consequence, ergonomics studies are time consuming and are mostly done for static poses, not for full assembly motions. Furthermore, these ergonomic studies, even though performed by a small group of highly specialized simulation engineers, show low reproducibility within the group.Effective simulation of manual assembly operations considering ergonomic load and clearance demands requires detailed modeling of human body kinematics and motions as well as a fast and robust inverse kinematics solver. In this paper we introduce a stability measure rewarding poses insensitive to variations in contact points and contact forces. Normally this has been neglected and only the balance of moment and forces has been taken into account. The manikin used in this work has 162 degrees of freedom and uses an exterior root. To describe operations and facilitate motion generation, the manikin is equipped with coordinate frames attached to end-effectors like hands and feet. The inverse kinematic problem is to find joint values such that the position and orientation of hands and feet matches certain target frames during an assembly motion. This inverse problem leads to an underdetermined system of equations since the number of joints exceeds the end-effectors’ constraints. Due to this redundancy there exist a set of solutions, allowing us to pick a solution that maximizes a scalar valued comfort function. Many objectives are included in the comfort function, for example in terms of joint angles, joint moments and solid objects’ distance to the manikin. The proposed stability measure complements the earlier balance criterion and is combined into the comfort function. By increasing the importance of this function the digital human model will reposition to a more stable pose. The digital human model will be tested on a set of challenging assembly operations taken from the automotive industry to show the effect of the stability measure.

The study examined the effects of manual control locations on two groups of randomly selected young and old drivers in relation to visual time off road, steering wheel deviation and safety perception. Measures of visual time off road, steering wheel deviations and safety perception were performed with young and old drivers during real traffic. The results showed an effect of both driver's age and button location on the dependent variables. Older drivers spent longer visual time off road when pushing the buttons and had larger steering wheel deviations. Moreover, the greater the eccentricity between the normal line of sight and the button locations, the longer the visual time off road and the larger the steering wheel deviations. No interaction effect between button location and age was found with regard to visual time off road. Button location had an effect on perceived safety: the further away from the normal line of sight the lower the rating.

Although buttons are a frequently used type of control in car interiors, little research has been undertaken on how the usage of buttons affects the visual behaviour of the driver. In this study, the aim was to analyse the effect of push button location and auditory feedback on drivers' visual time off road and safety perception when driving in a real traffic situation. The effect of six button locations (five on the centre stack, one near the gear stick) was tested. Drivers' visual behaviour was studied in real traffic on a motorway. An eye tracking system recorded the visual behaviour of eight drivers who, in 96 repeated trials each, were instructed to press a specific button. Data analysis focused on the drivers' visual time off road and safety perception in relation to the location of the button to be pressed. Auditory feedback did not show a significant effect on visual time off road. The time off road increased significantly as the angle increased between the normal line of sight and button location for the five buttons placed on the centre stack. Results for the button located close to the gear stick, with the highest eccentricity, produced a short time off road. This unexpected finding is discussed in terms of three potential explanations: 1) the role of perceptual discrimination; 2) risk perception; and 3) motor control.

The convergence of the focus of Industry 5.0 on human well-being and the prevalent problem of work-related musculoskeletal disorders necessitates advanced digital solutions due to limitations in manual risk assessment methods. This research aimed to compare usability of a newly developed video-based awkward posture identification software, the ergonomist assistant for evaluation (ERAIVA) with a conventional manual method. The risk assessment tool utilised in this study, integrated into the ERAIVA digital platform, is the risk management assessment tool for manual handling proactively (RAMP). Four assessors evaluated video-recorded tasks using both methods (manual and ERAIVA). The usability was assessed through the post-study system usability questionnaire, time consumption, number of video replays and video annotation deletions. The impact on identification of awkward posture durations was also studied. ERAIVA exhibited the highest usability score; it showed a higher number of video replays of specific sequences and annotations without significant differences in time consumption.

Observational postural assessment methods which are commonly used in industry are time consuming and have issues of inter- and intra-rater reliability. Computer vision (CV) based methodshave been proposed, but they have mainly been tested inside lab environments. This study aims to develop and evaluate an upper body postural assessment system in a real industry environment using a single depth camera and OpenPose for the task of forklift driving. The results were compared with XSens, an Inertial Measurement Unit (IMU) based system. Data from three forklift drivers performing seven indoor and outdoor tasks were recorded with a depth camera and XSens sensors. The data were then analyzed with OpenPose with additional custom processing. The angles calculated by the computer vision system showed small errors compared to the XSens system and generally followed the trend of the XSens system joint angle values. However, the results after applying ergonomic thresholds were vastly different and the two systems rarely agreed. These findings suggest that the CV system needs further study to improve the robustness on self-occlusion and angle calculations. Also,XSens needs further study to assess its consistency and reliability in industrial environments.

Developing digital dashboards (DD) that support staff in monitoring, identifying anomalies, and facilitating corrective actions are decisive for achieving the benefits of Smart Production Logistics (SPL). However, existing literature about SPL has not sufficiently investigated the characteristics of DD allowing staff to enhance operational performance. This conceptual study identifies the characteristics of DD in SPL for enhancing operational performance of material handling. The study presents preliminary findings from an ongoing laboratory development, and identifies six characteristics of DD. These include monitoring, analysis, prediction, identification, recommendation, and control. The study discusses the implications of these characteristics when applied to energy consumption, makespan, on-time delivery, and status for material handling. The study proposes the prototype of a DD in a laboratory environment involving Autonomous Mobile Robots. 

In the ANNIE project - Applications of Neural Networks to Integrated Ergonomics - BE96-3433, a tool for integrating ergonomics into the design process is developed. This paper presents some features in the current ANNIE as applied to the design of car interiors. A variant of the ERGOMan mannequin with vision is controlled by a hybrid system for neuro-fuzzy simulation. It is trained by using an Elite system for registration of movements. An example of a trajectory generated by the system is shown. A fuzzy model is used for comfort evaluation. An experiment was performed to test its feasibility and it showed very promising results.

Car developers use digital human modeling tools to analyze and visualize car interiors in relation to human characteristics before the vehicles are actually constructed. Developers, reviewers and users of human simulation tools often claim that such tools can reduce development time and costs. In car industry companies today, human simulation tools are used by a single or a few experts in an informal working process with insufficient documentation. To prepare for extensive, effective and efficient use of human simulation modeling tools in industry with several users within a company, the aim of this study was to design and evaluate a digital guide and documentation system to support digital human modeling applications. A participative design approach was used in developing the guide, involving human simulation tool users and managers within the General Motors Group. The system consists of two major parts: a usage guide and database. The usage guide is divided into three sections considering the professionals involved: (1) initiation of human–vehicle interaction analysis, (2) preparation and running of the digital human tool and (3) recommendation formulation and closure. The guide was connected to a database with search and print capabilities for previous and ongoing human simulation analyses. Sixteen subjects from industry and university settings evaluated the support system. Results showed that the users appreciated the guide and documentation system, in particular, the database for storing human simulation work. The guide was perceived as being especially useful for guidance in large analyses, whereas for smaller ones the subjects felt the formalized guide was too lengthy and time consuming. The use of the formalized guide is likely to reduce differences in results, within and between tool users. The support system guides the simulation tool user through an acknowledged process; it documents, stores and keeps track of ongoing and previous analyses, and facilitates the reuse of studies.

This chapter addresses and demonstrates the application of digital human modelling (DHM) tools to consider anthropometric diversity in product and workplace design. A number of additional methods for evaluating ergonomics conditions are also illustrated. Three cases show how DHM tools can be applied in different design settings and for different design undertakings, focusing on user variation in anthropometry. A number of methods for user representation in the DHM tool are briefl y presented. Method selection depends on the design problem at hand, and the chapter exemplifies the use of different methods for different design tasks. Examples are the use of onedimensional percentile based statistics data, the use of predefined collections of manikins, and the creation of representative cases by using multidimensional statistics. The chapter takes a designer’s view of the uses of DHM tools for anthropometry-related issues and illustrates how the tools can be of value in the design process.

The overall rationale and assumption for the research project presented is this paper is that a fast, easy to use, and reliable procedure to predict and validate manual assembly tasks is of major importance in product and production development processes to ensure high and robust product quality and process performance. A basic condition for the research is the belief that tools with such functionality are currently not available for companies to utilise in their development processes. Hence more research and development is needed in the area. This paper describes the basic concepts and initial steps taken in the recently commenced research project IMMA - Intelligently Moving Manikin. © 2011 by Taylor & Francis Group, LLC.

The overall rationale and assumption for the research project presented in this paper is that a fast, easy to use, and reliable procedure to predict and validate manual assembly tasks is of major importance in product and production development processes to ensure high and robust product quality and process performance. A basic condition for the research is the belief that tools with such functionality are currently not available for companies to utilise in their development processes. Hence more research and development is needed in the area. This paper describes the basic concepts and initial steps taken in the recently commenced research project IMMA - Intelligently Moving Manikin.

The overall rationale and assumption for the research project presented in this paper is that a fast, easy to use, and reliable procedure to predict and validate manual assembly tasks is of major importance in product and production development processes to ensure high and robust product quality and process performance. A basic condition for the research is the belief that tools with such functionality are currently not available for companies to utilise in their development process. Hence more research and development is needed in the area. This paper describes the status of the project IMMA - Intelligently Moving Manikins and discusses coming initiatives. The project status is portrayed by a conceivable simulation task of a digital test assembly of a centre console.

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.