The operational environment of complex sociotechnical systems is inherently uncertain, demanding constant coordination restructuring to adapt to dynamic situational demands. However, coordination changes in the Human Factors and Ergonomics Field have primarily been studied using static methods, overlooking moment-by-moment adjustments. In the current study, we address coordination restructuring by using THEME, a digital analytical tool capable of visualising and exploring coordination restructuring from a multi-layered perspective. We examine restructuring in coordination patterns during NASA's Apollo 13 Mission, revealing significant shifts from stable, long-duration ‘coordination hubs' in routine operations to shorter-duration patterns during a crisis situation. Additionally, the results highlight the importance of flexible switching between reciprocal and one-directed coordination, along with enhanced role distribution. This study underscores how exploring temporality-sensitive phenomena like coordination through digital technologies such as THEME, advances our understanding of incident analysis and resilient performance within complex systems.

In a previous scoping review, eight categories of interventions in individual work practice were defined. The aim of the present study is to evaluate the relevance and completeness of these eight categories and to increase the clarity of the nomenclature and definitions of each category. An international expert consultation has been carried out for this purpose. Thirty-eight experts from 13 countries participated. Data collection was conducted using a survey design comprising structured questions. Consensus was reached if 75% of the experts answered ‘Strongly agree’ or ‘Agree’ on a 5-point Likert scale. For the topic ‘Relevance’, there was consensus for six of the eight categories (range 78%–86%), the exceptions were the categories: ‘Exercising’ (72%) and ‘Professional manners' (64%). With regard to the topic ‘Nomenclature’, consensus was reached for six categories and for the topic ‘Definition’ this was five categories. The present definitions have been improved based on the expert recommendations. With respect to the topic ‘Completeness’: although a limited number of suggestions were given, this did not lead to one or more categories being added to the existing eight categories. The final ‘Nomenclature’ for the categories is: ‘Variation’, ‘Professional behaviour’, ‘Motoric skills’, ‘Vocational working techniques’, ‘Physical workplace’, ‘Physical training’, ‘Assistive devices and tools’ and ‘Task content and task organisation’. This expert consultation has provided a solid basis for endorsing the categorisation of interventions in IWP and is an important step in building a framework to develop and evaluate interventions in IWP.

Floor inclination can alter hand force production, and lower limb kinetics, affecting control operations, and threatening operator safety in various domains, such as aviation, naval, construction industry, or agriculture. This study investigates the effects of different floor inclinations, on handle push or pull force production. Participants performed maximal isometric contraction tasks requiring to exert a maximal voluntary force either by pulling or pushing a handle, at different floor inclinations from −30° to +30° about the transverse and longitudinal axes. Maximal hand force and Ground Reaction Forces about both feet were recorded. The results revealed non-equivalent variations in hand and feet responses as a function of inclination angle. Specifically, there was a significant reduction in handle push-pull force production, up to 70% (p < 0.001) for extreme inclinations, around both axes. This study provides critical data for design engineers, highlighting the challenge of production forces at steep angles.

The 5.0 industry promotes collaborative robots (cobots). This research studies the impacts of cobot collaboration using an experimental setup. 120 participants realized a simple and a complex assembly task. 50% collaborated with another human (H/H) and 50% with a cobot (H/C). The workload and the acceptability of the cobotic collaboration were measured. Working with a cobot decreases the effect of the task complexity on the human workload and on the output quality. However, it increases the time completion and the number of gestures (while decreasing their frequency). The H/C couples have a higher chance of success but they take more time and more gestures to realize the task. The results of this research could help developers and stakeholders to understand the impacts of implementing a cobot in production chains.