Adaptive automation and human factors in manufacturing: An experimental assessment for a cognitive approach

Can Complexity-Thinking Methods Contribute to Improving Occupational Safety in Industry 4.0? A Review of Safety Analysis Methods and Their Concepts

“…Automation surprises as identified in the manufacturing industry [106] have a longer research legacy in healthcare and aviation. In some noticeable examples of these domains [107,108], automation surprises have caused or contributed to tragic catastrophes [109][110][111].…”

“…Automation interaction challenges in manufacturing list the same set of problems as the ones described in aviation accident reports. Mode transition surprises whereby "operators may become unaware of changes in the operating mode performed by automation" [106] (p. 455) are described in manufacturing automation. The same authors describe automation-induced errors, whereby more automation can induce new, unexpected forms of human performance or inappropriate distrust in automation from manufacturing environments.…”

“…The same authors describe automation-induced errors, whereby more automation can induce new, unexpected forms of human performance or inappropriate distrust in automation from manufacturing environments. Just as in aviation, healthcare and operation of nuclear plants, manufacturing automation induces 'out-of-the-loop' conditions [106], which have been described as situations in which operators can encounter difficulties achieving a complete picture of the automation processes and comprehending how this may impair the detection of automation failures and the ability to regain manual control. In Table 4 this is defined as 'the transformation of knowledge and expertise' (See Table 4) [99], where new knowledge and skill demands might deprive human operators of sufficient context for making appropriate decisions and as 'the envisioned world problem' (See Table 4), which states that the introduction of autonomous technology transforms practice and coordination across human and machine roles Accompanying impaired detection from technology changes or transient 'out-of-the-loop' conditions can be translated directly in STAMP's reciprocal feedback and control loop mismatches, whereas FRAM identifies the absence of a precondition or control aspect to properly execute a downstream function and identify negative functional resonance.…”

Anthropocentric Approach for Smart Assembly: Integration and Collaboration

“…Towards a fulfilled HCD of workplaces, not only the physical aspects but also the cognitive ergonomic aspects need to be considered during the design processes. Concerning the cognitive workload related to manufacturing operations at different decisional levels, in [24], a human-in-the-loop framework concerning the design of workplaces was proposed to classify the fabrication tasks of production processes according to their cognitive complexity. In the ergonomic analyses phase, unlike traditional methods, which only observe operators in the actual running workplace, the impact of design plans including human actions and reactions can be simulated and verified by immersed vision based approaches.…”

Employee Acceptability of Wearable Mental Workload Monitoring in Industry 4.0: A Pilot Study on Motivational and Contextual Framing

“…Different research fields also investigate the modalities and boundary conditions for applying such technology and other originally clinical technology (cf., fNIRS, EEG) on the shop floor and in office environments to monitor employee's mental workload (cf., Young et al, 2014). In Industry 4.0 in particular, such physiological measurement could be integrated in a cyber-physical system allowing, for instance, assistive technology such as augmented reality and assistive robots to immediately adapt to operator MWL (D'Addona et al, 2018). Indeed, as the smart factory is taking shape through integrating advanced manufacturing techniques with digital infrastructures, the effects of the extensive flexibility expected from operators (Longo et al, 2017) on the mental processing could benefit from mental workload optimization as supported by objective MWL-monitoring.…”