Arbeitsgestaltung

Bokranz, Rainer

doi:10.1007/978-3-322-87423-8_42

Cited by 6 publications

(14 citation statements)

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“…Our investigations are structured in accordance with the highly reliable stress/strain concept [27][28][29][30][31][32][33][34]. All influences arising from the work task and the work environment were examined for strains affecting the worker.…”

Section: Methodsmentioning

confidence: 99%

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Ergonomic Time and Motion Studies of Aircraft De-icing Work

Landau¹,

Nadeau²,

Floch³

et al. 2017

J Ergonomics

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Section: Methodsmentioning

confidence: 99%

“…We have compared the energy turnovers calculated by the abovementioned methods with the generally recognized upper limits [33]:…”

Section: Work Form Of Test Personmentioning

confidence: 99%

Ergonomic Time and Motion Studies of Aircraft De-icing Work

Landau¹,

Nadeau²,

Floch³

et al. 2017

J Ergonomics

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“…Our dataset (IfM-CHLab2019) covers 18 of the 19 MTM-1 movements [25]. The activity apply pressure was omitted because the selected sensors are inherently not capable of measuring pressure.…”

Section: A Data Collectionmentioning

confidence: 99%

“…Before the data collection, we successfully sought ethical approval from the University of Cambridge's ethics commission. The detailed explanation of the tasks where derived from established MTM standards [25]. Exemplary extracts of the 18 MTM-1 activities are documented in Figure 4.…”

Section: A Data Collectionmentioning

confidence: 99%

Context-Aware Cyber-Physical Assistance Systems in Industrial Systems: A Human Activity Recognition Approach

Roth

Möncks

Bohné

et al. 2020

2020 IEEE International Conference on Human-Machine Systems (ICHMS)

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The increasing demand for product customisation is leading to higher complexities within industrial systems. This imposes new challenges for the workforce. One way to support operators' productivity may be context-aware, human-centred cyber-physical assistance systems. Human Activity Recognition (HAR) is a promising approach to enable context-awareness. However, standardised approaches to integrate HAR into existing industrial environments are rare. Particularly, there is a lack of available datasets of industrial activities. Moreover, comparative studies of inertial and visual HAR approaches are still rare. This work therefore proposes Methods-Time Measurement (MTM) as a standardised foundation for creating an industrial activity dataset. Subsequently, five different machine learning algorithms are tested for their recognition performance based on the dataset captured with an inertial sensor suit and an RGB-D sensor. A proof-of-concept is delivered for both sensor categories applied to the scope of 18 MTM-1 activities, whereas inertial data outperformed depth data. K-Nearest Neighbour and Bagged Tree algorithms revealed the best classification accuracy results in this context.

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“…The interpretation of their results was also primarily aimed at productivity, not humanity. Only in the last two decades, at least for MTM, a determined focus on ergonomic design and support in solving the conflict of objectives between economy and humanity is noticed [4]. If the metaphor "quantum leap" is to be used, the development of the Ergonomic Assessment Worksheet (EAWS) [5] and its integration into the MTM process under the caption "Human Work Design" [6] is an innovation.…”

Section: Introductionmentioning

confidence: 99%

Development of the Ergonomic Activity Sampling (EAS) Method to Analyse Video - Documented Work Processes with Activity Sampling

Landau¹

2018

EOIJ

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Ergonomics analyses examine design parameters of work processes, e.g. postures and movements or action forces, with the aim of assessing work systems or work processes with regard to feasibility and long-term tolerability. Numerous applications of ergonomics analysis at "normal" industrial and service workplaces can be found in the relevant literature as well as in practical field studies. In contrast, there are only a few methodical presentations of ergonomics analysis under critical working and environmental conditions, e.g. in fire brigade and medical emergency operations, in heat and cold environments, in radioactive contamination of workplaces, etc. With the EAS, a procedure for video-supported activity sampling analysis is presented. Based on case studies from aircraft de-icing, it is shown that video-based activity sampling studies allow a well-founded analysis of postures and movements with a cost-benefit ratio that is acceptable to the analyst.

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Arbeitsgestaltung

Cited by 6 publications

References 0 publications

Ergonomic Time and Motion Studies of Aircraft De-icing Work

Ergonomic Time and Motion Studies of Aircraft De-icing Work

Context-Aware Cyber-Physical Assistance Systems in Industrial Systems: A Human Activity Recognition Approach

Development of the Ergonomic Activity Sampling (EAS) Method to Analyse Video - Documented Work Processes with Activity Sampling

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