Search

The manufacturing factory layout planning process is commonly supported by the use of digital tools, enabling creation and testing of potential layouts before being realised in the real world. The process relies on engineers’ experience and inputs from several cross-disciplinary functions, meaning that it is subjective, iterative and prone to errors and delays. To address this issue, new tools and methods are needed to make the planning process more objective, efficient and able to consider multiple objectives simultaneously. This work suggests and demonstrates a simulation-based multi-objective optimisation approach that assists the generation and assessment of factory layout proposals, where objectives and constraints related to safety regulations, workers’ well-being and walking distance are considered simultaneously. The paper illustrates how layout planning for a logistics area can become a cross-disciplinary and transparent activity, while being automated to a higher degree, providing objective results to facilitate informed decision-making., CC BY 4.0CONTACT Andreas Lind andreas.lind@his.se Global Industrial Development, Scania CV AB, Södertälje, SwedenThe authors appreciatively thank the support of Scania CV AB, the research school Smart Industry Sweden (20200044) and the research project Virtual Factories with Knowledge-Driven Optimisation (2018-0011) funded by the Knowledge Foundation via the University of Skövde. With this support the research was made possible.The work was supported by the Stiftelsen för Kunskaps- och Kompetensutveckling [20200044]; Stiftelsen för Kunskaps- och Kompetensutveckling [2018-0011].

CC BY-NC-ND 4.0The present work was financially supported by the Swedish innovation agency Vinnova through the research and innovation programme Produktion2030, grant #2022-01279: Empowering Human Workers for Assembly of Wire Harnesses (EWASS), Empowering Human Workers for Assembly of Wire Harnesses (EWASS)

OCCUPATIONAL APPLICATIONS In the context of Industry 5.0, our study advances manufacturing factory layout planning by integrating multi-objective optimization with nature-inspired algorithms and a digital human modeling tool. This approach aims to overcome the limitations of traditional planning methods, which often rely on engineers’ expertise and inputs from various functions in a company, leading to slow processes and risk of human errors. By focusing the multi-objective optimization on three primary targets, our methodology promotes objective and efficient layout planning, simultaneously considering worker well-being and system performance efficiency. Illustrated through a pedal car assembly station layout case, we demonstrate how layout planning can transition into a transparent, cross-disciplinary, and automated activity. This methodology provides multi-objective decision support, showcasing a significant step forward in manufacturing factory layout design practices. TECHNICAL ABSTRACT Rationale: Integrating multi-objective optimization in manufacturing layout planning addresses simultaneous considerations of productivity, worker well-being, and space efficiency, moving beyond traditional, expert-reliant methods that often overlook critical design aspects. Leveraging nature-inspired algorithms and a digital human modeling tool, this study advances a holistic, automated design process in line with Industry 5.0. Purpose: This research demonstrates an innovative approach to manufacturing layout optimization that simultaneously considers worker well-being and system performance. Utilizing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Particle Swarm Optimization (PSO) alongside a Digital Human Modeling (DHM) tool, the study proposes layouts that equally prioritize ergonomic factors, productivity, and area utilization. Methods: Through a pedal car assembly station case, the study illustrates the transition of layout planning into a transparent, cross, CC BY 4.0Taylor & Francis Group an informa businessCONTACT Andreas Lind andreas.lind@scania.com, alt. andreas.lind@his.se Scania CV AB, Södertälje, SwedenThe authors appreciatively thank the support of Scania CV AB, the research school Smart Industry Sweden (20200044) and the research project Virtual Factories with Knowledge-Driven Optimization (2018-0011) funded by the Knowledge Foundation via the University of Skövde. With this support the research was made possible.

Wire harnesses are vital for any modern automotive vehicle. They control the basic functions in a vehicle, for example, windshield wipers and critical functions such as sensors, cameras, and autopilot functions. Thus, the quality of wire harness assembly is highly important. Today, wire harnesses are usually assembled manually, which creates unergonomic and tedious working conditions for operators. Traditional and collaborative industrial robots have been identified as possible solutions to overcome challenges faced by operators in this type of assembly. The international research community has proposed many solutions for automating the assembly of wire harnesses in automotive vehicles but despite these solutions, the industry has not been able to adopt a method to automate this assembly process fully or partially. This paper presents a review of findings on robot-assisted wire harness assembly processes based on a systematic literature review. Specifically, the assembly of wire harnesses in Electric Vehicles (EVs). The state-of-the-art review focuses on solutions to improve unergonomic work situations and ensure the quality of assembly operations. Best practices and reasons for the lack of extensive implementation in automotive final assembly systems are described. Further, the paper presents suggestions based on success stories where the automation of the wire harness assembly in automotive vehicles has been realised by leveraging human-centred automation solutions. Based on the findings, this paper identifies the research for future study. The findings also indicate that there is already technology that can support the automation of wire harness assembly processes in EVs but it is crucial to identify the human aspects and the role of humans in the assembly of wire harness assembly process., CC BY-NC-ND 4.0 DEED© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 56th CIRP International Conference on Manufacturing Systems 2023.Correspondence Address: O. Salunkhe; Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, Hörsalsvägen 7A, SE-412 96, Sweden; email: omkar.salunkhe@chalmers.seThis research is part of the EWASS project (grant number 2022-01279) funded by Produktion2030 through VINNOVA, the Swedish Innovation Agency, their and our Industrial partners’ support is gratefully acknowledged., EWASS

Factory layouts are frequently planned and designed in virtual environments, based on the experience of the layout planner. This planning and design process depends on information from several cross-disciplinary activities performed by several functions and experts, e.g., product development, manufacturing process planning, resource descriptions, ergonomics, and safety. Additionally, the layout planner also needs to consider applicable rules and regulations. This experience-based and manual approach to plan and design factory layouts, considering a multitude of inputs and parameters, is a cumbersome iterative process with a high risk of human error and faulty inputs and updates. The general trend in industry is to automate and assist users with their tasks and activities, deriving from concepts such as Industry 4.0 and Industry 5.0. This paper presents and demonstrates how digital support for rules and regulations can assist layout planners in factory layout work. The objective is to support the layout planner in accounting for area/volume reservations required to comply with rules and regulations for workers and equipment in the factory layout. This is a step in a wider initiative to provide enhanced digital support to layout planners, making the layout planning and design process more objective and efficient, and bridge gaps between cross-disciplinary planning and design activities., CC BY-NC-ND 4.0 DEEDCorresponding author: E-mail address: andreas.lind@scania.comThe authors appreciatively thank the support from Scania CV AB, the research school Smart Industry Sweden, and the VF-KDO (Virtual Factories with Knowledge-Driven Optimization) project funded by the Knowledge Foundation in Sweden; this support made the research possible.

The planning and design process of manufacturing factory layouts is commonly performed using digital tools, enabling engineers to define and test proposals in virtual environments before implementing them physically. However, this approach often relies on the experience of the engineers involved and input from various cross-disciplinary functions, leading to a time-consuming and subjective process with a high risk of human error. To address these challenges, new tools and methods are needed. The Industry 5.0 initiative aims to further automate and assist human tasks, reinforcing the human-centric perspective when making decisions that influence production environments and working conditions. This includes improving the layout planning process by making it more objective, efficient, and capable of considering multiple objectives simultaneously. This research presents a demonstrator solution for layout planning using digital support, incorporating a virtual multi-objective optimization approach to consider safety regulations, area boundaries, workers’ well-being, and walking distance. The demonstrator provides a cross-disciplinary and transparent approach to layout planning for an assembly station in the context of battery production. The demonstrator solution illustrates how layout planning can become a cross-disciplinary and transparent activity while being automated to a higher degree, providing results that support decision-making and balance cross-disciplinary requirements., CC BY 4.0Correspondence: andreas.lind@scania.comThis research was funded by Scania CB AB and the Knowledge Foundation via the University of Skövde, the research project Virtual Factories with Knowledge-Driven Optimization (2018-0011), and the industrial graduate school Smart Industry Sweden (20200044).

The factory layout is frequently planned in virtual environments, based on the experience of software tool users. This planning process is cumbersome and iterative to collect the necessary information, with a high risk of faulty inputs and updates. The digital twin concept has been introduced in order to speed up information sharing within a company; it relies on connectivity. However, the concept is often misunderstood as just a 3D model of a virtual object, not including connectivity. The aim of this paper is to present an extended virtual and physical engineering communication framework including four concepts: digital model, digital pre-runner, digital shadow, and digital twin. The four concepts are demonstrated and described in order to facilitate understanding how data exchange between virtual and physical objects can work in the future and having up-to date virtual environments enables simulating, analysing, and improving on more realistic and accurate datasets., CC BY 4.0This paper is a revised and expanded version of a paper entitled ‘Evaluating a digital twin concept for an automatic up-to-date factory layout setup’ presented at 10th Swedish Production Symposium (SPS2022), Skövde, Sweden, 26–29 April, 2022.The authors gratefully thank the support of Scania CV AB, the Research School Smart Industry Sweden, and the VF-KDO Project (Virtual Factories with Knowledge-Driven Optimization) funded by the Knowledge Foundation in Sweden; this support made the research possible.

This article provides a systematic literature review of computer vision applications in robotized wire harness assembly., Comment: This paper has been published in Advanced Engineering Informatics. Please refer to the published version

Wire harnesses are essential hardware for electronic systems in modern automotive vehicles. With a shift in the automotive industry towards electrification and autonomous driving, more and more automotive electronics are responsible for energy transmission and safety-critical functions such as maneuvering, driver assistance, and safety system. This paradigm shift places more demand on automotive wire harnesses from the safety perspective and stresses the greater importance of high-quality wire harness assembly in vehicles. However, most of the current operations of wire harness assembly are still performed manually by skilled workers, and some of the manual processes are problematic in terms of quality control and ergonomics. There is also a persistent demand in the industry to increase competitiveness and gain market share. Hence, assuring assembly quality while improving ergonomics and optimizing labor costs is desired. Robotized assembly, accomplished by robots or in human-robot collaboration, is a key enabler for fulfilling the increasingly demanding quality and safety as it enables more replicable, transparent, and comprehensible processes than completely manual operations. However, robotized assembly of wire harnesses is challenging in practical environments due to the flexibility of the deformable objects, though many preliminary automation solutions have been proposed under simplified industrial configurations. Previous research efforts have proposed the use of computer vision technology to facilitate robotized automation of wire harness assembly, enabling the robots to better perceive and manipulate the flexible wire harness. This article presents an overview of computer vision technology proposed for robotized wire harness assembly and derives research gaps that require further study to facilitate a more practical robotized assembly of wire harnesses., Comment: Presented at the 56th CIRP Conference on Manufacturing Systems (CIRP CMS 2023), Cape Town, South Africa, 24-26 October 2023. Published in Procedia CIRP

Today, manufacturing factory layout setups are most often manually designed and kept up-to-date during their lifecycle with computer-aided design software’s, so that analyses, verification simulations, and decisions can continuously be done. This manual approach is a cumbersome iterative process to collect the necessary information, with a high risk of faulty inputs and updates. Often the virtual descriptions do not match the physical version of the factory setup. This research presents a digital twin solution where physical equipment is connected to a virtual representation of the same equipment and automatically updates the virtual environment with the spatial position of the physical equipment and a proposed way to evaluate it. The physical equipment either has inbuilt sensors or has been equipped with external wireless sensors to track the spatial position. The metadata are distributed via Node-RED (a tool to visualize Internet of Things) to the simulation software Industrial Path Solutions, where the virtual equipment is repositioned based on data from the physical equipment. The result shows that it is possible to send spatial position information from a physical equipment and update the corresponding virtual description of the equipment in its virtual environment. The accuracy of the updates has been evaluated with manual measurements. Hence, the virtual environment of the factory setup, i.e., the digital twin, updates automatically based on the data sent by the physical equipment. With an up-to-date virtual environment, more accurate simulations and optimizations of the factory setup can be achieved. Examples of such possibilities are to evaluate ergonomic conditions or to optimize robot paths for robot cells in realistic and up-to-date virtual environments. Also, one could imagine making virtual reality visits to hazardous or sensitive factory environments in a safe way or studying things that otherwise would be hard or impossible in the real world., CC BY-NC 4.0Andreas Lind [andreas.lind@scania.com]This research was realized with the support of Scania CV AB’s Global Industrial Development and the VF-KDO profile (Virtual Factories with Knowledge-Driven Optimization) at the University of Skövde, funded by the Knowledge Foundation.

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., CC BY 4.0Correspondence: aitor.iriondo.pascual@his.seFunding: This work has received support from ITEA3/Vinnova in the project MOSIM (2018-02227), and from Stiftelsen för Kunskaps- och Kompetensutveckling within the Synergy Virtual Ergonomics (SVE) project (2018-0167) and the Virtual Factories–Knowledge-Driven Optimization (VF-KDO) research profile (2018-0011). This support is gratefully acknowledged.

Simulation using virtual models is used widely in industries because it enables efficient creation, testing, and optimization of the design of products and production systems in virtual worlds. Simulation is also used in the design of workstations to assess worker well-being by using digital human modeling (DHM) tools. DHM tools typically include musculoskeletal risk assessment methods, such as RULA, REBA, OWAS, and NIOSH Lifting Equation, that can be used to study, analyze, and evaluate the risk of work-related musculoskeletal disorders of different design solutions in a proactive manner. However, most musculoskeletal risk assessment methods implemented in DHM tools are in essence made to assess static instances only. Also, the methods are typically made to support manual observations of the work rather than by algorithms in a software. This means that, when simulating full work sequences to evaluate manikins’ well-being, using these methods become problematic in terms of the legitimacy of the evaluation results. In addition to that, to consider objectives in optimizations, they should be measurable with real numbers, which most of musculoskeletal risk assessment methods cannot provide when simulating full work sequences. In this study, we implemented the musculoskeletal risk assessment method OWAS in a digital tool connected to the DHM tool IPS IMMA. We applied the Lundqvist index on top of the OWAS whole body risk category score. This gave us an integer of the time-based ergonomic load for a specific simulation sequence, enabling us to qualitatively compare different design solutions. Using this approach, we performed an optimization in a welding gun workstation to improve the design of the workstation. The results show that using time-based musculoskeletal risk assessment methods as objective functions in optimizations in DHM tools can provide valuable decision support in finding solutions for workstation designs that consider worker well-being., Copyright © 2022 the author(s)

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., © 2022This work has been supported by ITEA3 in the project MOSIM, the Knowledge Foundation and the associated INFINIT research environment at the University of Skövde, within the Virtual Factories with Knowledge-Driven Optimization (VF-KDO) research profile and the Synergy Virtual Ergonomics (SVE) project, and by the participating organizations. Their support is gratefully acknowledged.

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 c, CC BY 4.0CONTACT Aitor Iriondo Pascual aitor.iriondo.pascual@his.sePublished online: 09 Nov 2021This work has received support from ITEA3/Vinnova in the project Modular Simulation of Natural Human Motions (MOSIM), and from the Knowledge Foundation and the associated INFINIT research environment at the University of Skövde, within the Virtual Factories–Knowledge-Driven Optimization (VF-KDO) research profile and the Synergy Virtual Ergonomics (SVE) project, and from the participating organizations. This support is gratefully acknowledged.10.1080/24725838.2021.1997834

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., CC BY-NC 4.0This work has been made possible with the support from VINNOVA in the project VIVA - the Virtual Vehicle Assembler, and by the participating organizations. This support is gratefully acknowledged.

QC 20210617

Digital human modelling (DHM) allows ergonomic risk assessment to be performed at early stages of design and development. Such assessment is typically based on observational methods, which do not take advantage of the potential of DHM tools to provide precise posture and motion data. This paper describes and illustrates an alternative assessment approach employing DHM tools, inspired by risk assessment based on direct measurements. A literature survey established a reference database of epidemiological associations between exposure and wrist-related disorders. This approach is illustrated by a DHM simulation of a car assembly task. Wrist posture and motion were simulated and compared to the database, predicting the prevalence of work-related musculoskeletal disorders on the basis of direct measurements, Ingår i dissertation

This paper introduces a Streamlined Modelling and Decision Support (StreaMod) approach in which input data management, simulation model generation/update and simulation-based optimisation are synergistically integrated into a largely automated process. The aim of this automated process is to support decision making related to the optimal maintenance resources allocation that could improve the performance of production/logistics systems. The basic novelty of the StreaMod optimisation methodology lies on the formulation of an optimal maintenance allocation problem of a production/logistic system into a bi-objective optimisation problem, so that optimal resources/changes to improve the throughput of the system can be sought in a single optimisation run. The successful application of this methodology in a real-world automotive factory will also be addressed in this paper.

Use of digital human modeling (DHM) tools enables early assessment of ergonomic risks in the production development process. This early risk assessment can indicate needs for preventive actions in order to decrease risks for work-related musculoskeletal disorders. A method for the assessment of physical workload has been developed, for the analysis of wrist joint data produced by a DHM tool. The method is tested in a simulation model of an actual manual assembly station in industry where it is assumed that physical workload problems exist. The results show that the method can be successfully applied on an industrial case. In addition, presumptive risks and possible diagnoses are predicted based on the similarity of the simulated task’s motions with motions from other known work class profiles stored in a database based on epidemiological research., CROMM

To simulate human motions in DHM tools, using techniques which are based on real human data is one promising solution. We have presented a solution in this study to connect motion databases with DHM tools. We have showed that using a motion database with MTM-based annotations is a promising way in order to synthesize natural looking motions. A platform consists of a Motion Database, a Motion Generator, and a DHM tool was introduced and tested. The results showed successful application of the presented platform in the designed test case. © 2013 Springer-Verlag.

A unified database platform capable of storing both motion captured data and information about these motions (metadata) is described. The platform stores large motion captured data in order to be used by different applications for searching, comparing, analyzing and updating existing motions. The platform is intended to be used to choose a realistic motion in simulation of production lines. It is capable of supporting and handling different motion formats, various skeleton types and distinctive body regions in a uniform data model. Extended annotating system is also introduced to mark the captured data not only in the time domain (temporal) but also on different body regions (spatial). To utilize the platform, sample tests are performed to prove the functionality. Several motion captured data is uploaded to the database while MATLAB is used to access the data, ergonomically analyze the motions based on OWAS standard, and add the results to the database by automatic tagging of the postures.

The objective of this study was to examine to what extent ergonomics simulations of manual assembly tasks correctly predict the real outcomes in the plants and if recommended measures originating from ergonomics simulations are taken into consideration. 155 ergonomics simulation cases were used in the study and all cases were performed by nine simulation engineers at Volvo Car Corporation in Gothenburg. The evaluations of the ergonomics conditions of the simulated tasks were done by six professional ergonomists working at Volvo Car Corporation in Gothenburg. The results show that digital human modelling tools (DHM-tools) are useful for the purpose of providing designs for standing and unconstrained working postures. Furthermore, the design of various auxiliary devices and their needed space for movements is a prevalent use of DHM-tools. However, the study also identifies areas that require additional development in order to further improve the digital human modelling tools' possibility to correctly predict a work task's real outcome, i.e. hand access, push pressure and pull forces, leaning and balance behaviour and field of vision. Moreover, a better feedback of product and process changes and a more careful order description of simulation cases to the simulation engineers would lead to improved simulation results in current and future projects. Relevance to industry: DHM-tools are increasingly the major means used to perform ergonomics analyses of manual assembly tasks in the automotive industry, but there is still a need for improvements of the tools. It is of great importance to disseminate end users' experiences of the use of different DHM-tools so these can be developed and applied in a more efficient way., This paper is partly a result of the research project 4D Ergonomics which is carried out within Virtual Ergonomics Centre (www.vec.se) and is financially supported by VINNOVA (the Swedish Agency for Innovation Systems) within the MERA (Manufacturing Engineering Research Area) program under the grant no. 2005-01998 and by the participating organizations (Alviva, Dassault Systèmes, Etteplan, SAAB Automobile, Siemens/UGS and Volvo Car Corporation). This support is gratefully acknowledged. The authors also would like to express their gratitude to European Ergonomists Annki Falck and Kristina Troedsson and production ergonomist Sari Rosenström, all at Volvo Car Corporation, for assistance in the selection and evaluation of the ergonomics simulation cases. Thanks also go to the ergonomists from the occupational health service organization in the factories as well as to all participating ergonomics simulation engineers and manufacturing engineers at the manufacturing department at Volvo Car Corporation. Many thanks to Marita Christmansson for useful and constructive comments regarding the contents of the article., 4D Ergonomics

The objective of this study was to examine to what extent ergonomics simulations of manual assembly tasks correctly predict the real outcomes in automotive assembly plants, and if recommended measures originating from ergonomics simulations are considered. 155 ergonomics simulation cases done by nine simulation engineers at Volvo Car Corporation in Gothenburg were used in the study. The evaluations of the ergonomics conditions in reality of the cases were done by six professional ergonomists working in the company. The results show that digital human modelling tools are useful for providing designs for standing and unconstrained working postures as well as for the design of various auxiliary devices and their needed space for movements. The study also identifies areas that require additional development in order to improve the digital human modelling tools’ ability to correctly predict a work task's real outcome. Moreover, a better feedback of product and process changes, and a more careful order description to the simulation engineers, would improve simulation results in current and future projects.

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., This paper is partly a result of the research project 4D Ergonomics which is carried out within Virtual Ergonomics Centre (http://www.vec.se) and is financially supported within the MERA (Manufacturing Engineering Research Area) program under grant no. 2005-01998 by VINNOVA (the Swedish Agency for Innovation Systems) and the participating organizations (Alviva, Dassault Systèmes, Etteplan, SAAB Automobile Siemens/UGS and Volvo Car Corporation). This support is gratefully acknowledged. The authors also would like to express their gratitude to European Ergonomists Ann-Christine Falck, Kristina Troedsson and production ergonomist Sari Rosenström. Thanks also go to the ergonomists from the occupational health service organization in the studied factory.Many thanks to Oscar Person, Marita Christmansson, Lars-Ola Bligård, Annki Falck, Dan Högberg and two anonymous reviewers for useful and constructive insights and comments regarding the contents and structure of the article., 4D Ergonomics

This paper presents the results of a comparison of manikin posturing within and between simulation engineers. Five simulation engineers were asked to simulate four manual assembly cases. They repeated each task six times, three times with a posture prediction tool and three times with manual adjustment of the body angles. The results show that the posture-prediction-tool was not used in an optimal manner. Although the prediction-tool was quick at suggesting a likely posture, the simulation engineers were reluctant to consider a simulation task completed until the manikin's posture was realistic in all aspects. The comparison indicates that if a posture-prediction-tool is to be beneficial, results with postures containing some non-cosmetic elements must be accepted. It is not until such an acceptance is achieved that the successful use of a posture-prediction-tool will become a reality., 4D Ergonomics

Computer aided visualisation and simulation enables earlyevaluation of important design parameters of future products and productionsystems. Typically, humans affect the system performance, and in order toachieve the expected system efficiency ergonomics needs to be considered inthe design process in addition to the more technical or logistical matters.Hence, there is a call for ergonomics to be a natural part of the product andproduction development process, also at virtual stages. Three examples of thedevelopment of Digital Human Modelling-(DHM)-based company-specific

Digital human modelling (DHM) tools have been introduced in industry, mainly in automotive, aerospace and industrial engineering, to facilitate a proactive and efficient consideration of ergonomics in the design process. The employment of DHM tools in the health care sector calls for customisation work to be carried out in order to make the tools fit the design activities. The human model, i.e. the computer manikin, needs to be modified since it has the characteristics and appearance of an able healthy young or middle-aged human, but the resident or patient is frequently an elderly person with impairments of some kind. This paper suggests concepts and structures for assigning the computer manikins characteristics of the elderly. These changes are made by the modification of anthropometric and joint range of motion data in the DHM tool, and by assigning narrative descriptions to the manikins and more age-corresponding appearances. The objective is to define a manageable number of representative manikins that will support a proactive and user-centred design process in the health care industry, and in other types of design processes for the elderly, or in an inclusive design context.

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.

Computer aided visualization and simulation enables early assessment of important design parameters of future products and production systems. Typically, humans affect the system performance, and in order to achieve the expected system efficiency ergonomics needs to be considered in the design process in addition to the more technical or logistical matters. Hence, there is a call for ergonomics to be a natural part of the product and production system design process, also at virtual stages. This paper portrays and discusses two cases where company-specific ergonomics guidelines were implemented into digital human modeling systems for performing static work analyses. Albeit useful, the approach of evaluating static postures gives a reduced picture of the actual situation since the work usually involves a series of movements and tasks. A recently commenced research project aims to enhance knowledge on how to estimate accumulated ergonomic load over time. This knowledge is eventually to be implemented in DHM tools to support objective ergonomics analysis of complete work sequences in virtual environments.

A work method for product and production system development that includes virtual methods for ergonomics analysis is presented and argued.The proposed work method is described and illustrated with an example,which the authors believe shows how a virtual work method can contribute to a better workplace design, and thereby, if utilised, would have prevented some of the design flaws that existed in the actual final product design in the example. This paper will also present the outcome, gain, and setbacks that are connected to the use of virtual work analysis methods within a design process.