Of Embodied Action and Sensors: Knowledge and Expertise Sharing in Industrial Set-Up

Abstract

Knowledge and expertise sharing has long been an important theme in CSCW and, importantly, one that has frequently challenged a prevailing view concerning knowledge management. This critique focused, initially, on the practical problems associated with issues of Organisational Memory (OM), and in particular the difficulties inherent in an oversimplified ‘repository’ model. Attention then turned to issues of contextuality and communication for expertise sharing, drawing on concepts such as communities of practice and social capital to understand, again, the sharing of knowledge and expertise in practice. Here, we report on how particular kinds of ‘embodied action’ can be identified in relation to the potential of cyber-physical infrastructures for knowledge sharing in an industrial context. We argue that, in a complex industrial domain, both the recording of physical movement – ‘showing’ – and the representation of local knowledge – ‘telling’ – are potentially relevant. Our proposal is that the evolution of cyber-physical infrastructures now offers a way of changing some early assumptions about how knowledge might be captured and displayed. We argue that we are entering a third generation of knowledge and expertise sharing research, where the use of augmented reality (AR) and sensor technology will result in significant new methodological innovations, including the capture and sharing of knowledge, embedded in embodied action.

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Notes

  1. 1.

    This is not to conflate ‘invisible work’ with ‘tacit knowledge’, though it has been argued in the literature that tacit and contextual knowledge is one of the ‘many guises’ that invisible work can take (Nardi and Engeström 1999, p.2). To clarify, invisible work has been discussed in the literature as: work that happens behind the scenes; routine or manual work entailing unacknowledged problem solving; work undertaken by people who remain unaccounted for; or informal work that is outside any job description, yet vital for collective tasks and company organization (Nardi and Engeström 1999). In turn, ‘tacit knowledge’ has been mooted to be: ‘non-codified knowledge’ acquired through learning-by-doing (Roberts 2000); ‘highly personal’ and ‘difficult to formalize’ (Nonaka 1991, p.98); ‘deeply rooted in action’ and ‘context’ (Matthew and Sternberg 2009; Nonaka 1991), ‘not yet … abstracted from practice’ and ‘applied in the state of the flow’ (Spender 1996, p.67). In Argyris (1999) view, constant use of a particular instance of knowledge leads to internalisation and its automatic use. It thus becomes understood or implied without being articulated, and as such, is usually taken for granted and goes unnoticed (Baumard 1999).

  2. 2.

    For an overview of what set-up for bending machines entails, see section 4.1.

  3. 3.

    Presence disparity occurs when remote collaborators are not sufficiently aware of those who are co-located. According to Tang et al. (2007) it happens because embodied action is key for the processes of: feedback and feedthrough, whereby people perceive themselves and one another; consequential communication, where people grasp information by observing the work of others; and gestures, which correspond to ‘bodily movements and postures used for communicative purpose’ (p.5).

  4. 4.

    Note that we do not buy into technological determinism but acknowledge technology’s assistive potential.

  5. 5.

    Industry 4.0 (I4.0), is a movement that has resulted from the German federal government calling for a ‘fourth industrial revolution’, inspired by the use of CPSs in manufacturing contexts (Paelke and Röcker 2015; Wan et al. 2015).

  6. 6.

    We used an eye-tracking technology to record actual set-up sessions in the course of ordinary workdays of our participants. By capturing the exact gaze of participants, we were able to get a better understanding of the operations they carried out. Eye-tracker recordings gave us both a better view of the parts being exchanged and the actions involved in the exchange. We also got participants to use a Think Aloud protocol (Nielsen 1993, pp. 195–198) during the session, so as to gather information about their reasoning as the set-up progressed. Analysis of this data gave us a deeper understanding of what industrial set-up entails and underpinned heat-map analysis of the tools and parts the participants were focusing on.

  7. 7.

    Cold-forming is a process where metals are forged at near room temperature. The contour of the forming is predetermined by tools in a bending machine and the temperature during forming remains below the metal’s recrystallization temperature (VDI 3430, 2014).

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Acknowledgements

The findings in this paper come from the research project ‘Cyberrüsten 4.0: Cyber-physische Unterstützung des Menschen beim Rüstvorgang am Beispiel eines Biegeprozesses zur Klein- serienfertigung auf Basis eines Wissenstransferansatzes’, funded by a grant of the European Union and EFRE.NRW (No. EFRE-0800263).

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Correspondence to Aparecido Fabiano Pinatti de Carvalho.

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de Carvalho, A.F.P., Hoffmann, S., Abele, D. et al. Of Embodied Action and Sensors: Knowledge and Expertise Sharing in Industrial Set-Up. Comput Supported Coop Work 27, 875–916 (2018). https://doi.org/10.1007/s10606-018-9320-6

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Keywords

  • Augmented reality
  • Cyber-physical systems
  • Didactic practices
  • Know how
  • Know that
  • Knowledge and expertise sharing
  • Local knowledge
  • Organisational memory
  • Tacit knowledge
  • Sensor technology