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- Berlin, Cecilia, 1981, et al.
(author)
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Production Ergonomics: Designing Work Systems to Support Optimal Human Performance
- 2017
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Book (other academic/artistic)abstract
- Production ergonomics – the science and practice of designing industrial workplaces to optimize human well-being and system performance – is a complex challenge for a designer. Humans are a valuable and flexible resource in any system of creation, and as long as they stay healthy, alert and motivated, they perform well and also become more competent over time, which increases their value as a resource. However, if a system designer is not mindful or aware of the many threats to health and system performance that may emerge, the end result may include inefficiency, productivity losses, low working morale, injuries and sick-leave.To help budding system designers and production engineers tackle these design challenges holistically, this book offers a multi-faceted orientation in the prerequisites for healthy and effective human work. We will cover physical, cognitive and organizational aspects of ergonomics, and provide both the individual human perspective and that of groups and populations, ending up with a look at global challenges that require workplaces to become more socially and economically sustainable. This book is written to give you a warm welcome to the subject, and to provide a solid foundation for improving industrial workplaces to attract and retain healthy and productive staff in the long run.
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| 3. |
- Liu, Yuanhua, 1971, et al.
(author)
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Considering the importance of user profiles in interface design
- 2009
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In: User Interfaces. ; , s. 23-
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Book chapter (other academic/artistic)abstract
- User profile is a popular term widely employed during product design processes by industrial companies. Such a profile is normally intended to represent real users of a product. The ultimate purpose of a user profile is actually to help designers to recognize or learn about the real user by presenting them with a description of a real user’s attributes, for instance; the user’s gender, age, educational level, attitude, technical needs and skill level. The aim of this chapter is to provide information on the current knowledge and research about user profile issues, as well as to emphasize the importance of considering these issues in interface design. In this chapter, we mainly focus on how users’ difference in expertise affects their performance or activity in various interaction contexts. Considering the complex interaction situations in practice, novice and expert users’ interactions with medical user interfaces of different technical complexity will be analyzed as examples: one focuses on novice and expert users’ difference when interacting with simple medical interfaces, and the other focuses on differences when interacting with complex medical interfaces. Four issues will be analyzed and discussed: (1) how novice and expert users differ in terms of performance during the interaction; (2) how novice and expert users differ in the perspective of cognitive mental models during the interaction; (3) how novice and expert users should be defined in practice; and (4) what are the main differences between novice and expert users’ implications for interface design. Besides describing the effect of users’ expertise difference during the interface design process, we will also pinpoint some potential problems for the research on interface design, as well as some future challenges that academic researchers and industrial engineers should face in practice.
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| 4. |
- Lind, Carl Mikael, et al.
(author)
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Prevention of Work: Related Musculoskeletal Disorders Using Smart Workwear – The Smart Workwear Consortium
- 2019
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In: Human Systems Engineering and Design. - Cham : Springer. - 9783030020521 - 9783030020538 ; 876, s. 477-483
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Conference paper (peer-reviewed)abstract
- Adverse work-related physical exposures such as repetitive movements and awkward postures have negative health effects and lead to large financial costs. To address these problems, a multi-disciplinary consortium was formed with the aim of developing an ambulatory system for recording and analyzing risks for musculoskeletal disorders utilizing textile integrated sensors as part of the regular workwear. This paper presents the consortium, the Smart Workwear System, and a case study illustrating its potential to decrease adverse biomechanical exposure by promoting improved work technique.
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| 5. |
- Neumann, W. Patrick, et al.
(author)
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Innovation and employee injury risk in automotive disassembly operations
- 2018
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In: International Journal of Production Research. - : Taylor & Francis. - 0020-7543 .- 1366-588X. ; 56:9, s. 3188-3203
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Journal article (peer-reviewed)abstract
- Engineering innovations in car disassembly systems are studied for affects on system operators’ risk of repetitive strain injury (RSI). Objective instrumented measures of injury risk factors with synchronized video-based task analyses were used to examine changes in operators’ RSI risk during two cases of engineering innovation: 1) a shift in industrial model from traditional extracting saleable parts to line-based full material recovery, and 2) the prospective effects of a simulated “Lean” inspired process improvement in the line system.Both cases of innovation showed significantly increased movement speeds and reduced muscular recovery opportunities, implying increased RSI risk. This case study reveals a mechanism by which innovation may increase RSI risks for operators. Managers responsible for engineering innovation should ensure their teams have the tools and mandate necessary to control injury hazards as part of the development and design process. These cases suggest how failure to manage RSI hazards in the innovation process may allow increases of injury risks that can compromise operational performance. This “innovation pitfall” has implications for operator health and organizational sustainability. Alternative pathways are discussed.
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| 7. |
- Håkansson, Ebba, et al.
(author)
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Including Human Factors and Ergonomics in Requirements Engineering for Digital Work Environments
- 2020
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In: Proceedings of 1st IEEE International Workshop on Requirements Engineering for Well-being, Aging and Health (REWBAH). - 9781728183541
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Conference paper (peer-reviewed)abstract
- Digital technology plays an important role in our work places, and much time is spent in the virtual environments that technol-ogy provides. However, today’s digital work environments are often cumbersome and hard to use, and contribute to stress and ill-health with subsequent cost to the individual, to their employ-ers and to society. Our long-term aim is to facilitate the develop-ment of IT systems that provide a healthy digital work environ-ment by including a human factors and ergonomics (HFE) per-spective in the requirements engineering (RE) process. IT systems can then be better adapted to professional users, rather than forcing them to adapt work processes to the tools provided. As a first step, we performed an exploratory case study of a recently implemented IT system at a major Nordic bank to identify relevant aspects of HFE to consider within RE. The study consisted of a literature review, observations and interviews. We present eight factors covering user support such as documentation and training, and system characteristics such as understandability, ease of learning, ease of remembering, user satisfaction, system interplay and work-process interplay. These initial results may support non-HFE experts in including these aspects in RE for digital work environments. The results are also a starting point for further research into incorporating HFE in RE.
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| 8. |
- Abtahi, Farhad, 1981-, et al.
(author)
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Big Data & Wearable Sensors Ensuring Safety and Health @Work
- 2017
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In: GLOBAL HEALTH 2017, The Sixth International Conference on Global Health Challenges. - 9781612086040
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Conference paper (peer-reviewed)abstract
- —Work-related injuries and disorders constitute a major burden and cost for employers, society in general and workers in particular. We@Work is a project that aims to develop an integrated solution for promoting and supporting a safe and healthy working life by combining wearable technologies, Big Data analytics, ergonomics, and information and communication technologies. The We@Work solution aims to support the worker and employer to ensure a healthy working life through pervasive monitoring for early warnings, prompt detection of capacity-loss and accurate risk assessments at workplace as well as self-management of a healthy working life. A multiservice platform will allow unobtrusive data collection at workplaces. Big Data analytics will provide real-time information useful to prevent work injuries and support healthy working life
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| 10. |
- Fan, Xuelong, et al.
(author)
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Effects of sensor types and angular velocity computational methods in field measurements of occupational upper arm and trunk postures and movements
- 2021
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In: Sensors. - : MDPI AG. - 1424-8220. ; 21:16
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Journal article (peer-reviewed)abstract
- Accelerometer-based inclinometers have dominated kinematic measurements in previous field studies, while the use of inertial measurement units that additionally include gyroscopes is rapidly increasing. Recent laboratory studies suggest that these two sensor types and the two commonly used angular velocity computational methods may produce substantially different results. The aim of this study was, therefore, to evaluate the effects of sensor types and angular velocity computational methods on the measures of work postures and movements in a real occupational setting. Half-workday recordings of arm and trunk postures, and movements from 38 warehouse workers were compared using two sensor types: accelerometers versus accelerometers with gyroscopes—and using two angular velocity computational methods, i.e., inclination velocity versus generalized velocity. The results showed an overall small difference (<2° and value independent) for posture percentiles between the two sensor types, but substantial differences in movement percentiles both between the sensor types and between the angular computational methods. For example, the group mean of the 50th percentiles were for accelerometers: 71°/s (generalized velocity) and 33°/s (inclination velocity)—and for accelerometers with gyroscopes: 31°/s (generalized velocity) and 16°/s (inclination velocity). The significant effects of sensor types and angular computational methods on angular velocity measures in field work are important in inter-study comparisons and in comparisons to recommended threshold limit values.
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