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Augmented Workforce Canvas: Towards a Tool for Integrating Operator Assistance Systems in Industry


Type

Thesis

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Authors

Abstract

To remain competitive in an increasingly complex manufacturing landscape, organisations are moving beyond a full automation narrative and considering the empowering role of augmentation. Although technology is an important pillar in industry, people remain essential on shop floors and will continue to be so in the future. Where total automation is not the preferred option, augmentation technologies and operator assistance systems (OAS) have the potential to realise an optimal combination of people and technology, resulting in human-technology integration (HTI). In this study, OAS are conceptualised as socio-technical systems that modify or complement an operator's capabilities. However, despite their promising potential for empowering the workforce, OAS are inadequately understood in industry. For example, there is a distinct lack of knowledge on the applicability of OAS, their value-added, and the most effective way of integrating OAS into production environments. The set of relevant technology management factors that need to be considered to understand and guide technology implementation projects concerning OAS is unknown. Understanding these factors is crucial as the successful adoption of OAS depends on how an application was developed and deployed. Focusing on OAS for execution support, this study therefore (a) explores the relevant technology management factors for integrating OAS into production systems, and (b) strives to understand how to systematically consider these factors during the integration of OAS into human-centric production systems. In technology management research, the use of multiple methods has been advocated to overcome individual methodological weaknesses and to allow for a richer approach to data collection, analysis and interpretation. Following pragmatism and engaged scholarship, this study applies procedural action research. Due to the contextual richness of OAS research, a mixed method research approach was selected, involving: (a) a systematic review of 2,928 papers; (b) 67 semi-structured expert interviews from 45 different manufacturing organisations; (c) 32 survey-guided industry case studies; (d) 108 structured industry workshops and working sessions; (e) ethnography and observations in ten different shop floor environments; (f) three industrial case studies; and (g) two in-depth evaluative industrial case studies over the course of three months each. As a result, this study identifies (a) 11 goal-based application areas for OAS, (b) 11 organisation-based application areas for OAS, (c) the value-added of OAS on shop floors, and (d) a set of 15 technology management factors that need to be considered when integrating OAS. An essential contribution emerging from these findings is the Augmented Workforce Canvas (Canvas) (Figure 1). The Canvas is a framework enabling practitioners to systematically understand and guide activities related to the integration of OAS. Evaluating the Canvas in two end-to-end industry case studies, this research provides evidence that the Canvas can be applied to guide OAS integration activities in industry. Overall, this study contributes to the understanding of industrial socio-technical systems and their integration into production systems by placing both people and the value-added of OAS at the heart of technology management decisions.

Description

Date

2022-12-20

Advisors

Bohné, Thomas
Kristensson, Per-Ola

Keywords

Industry 5.0, Industry 4.0, Human-centric, Augmentation, Automation, Assistance, Worker Support, Cyber-physical Production System, Technology Management, Reference Framework, People-centric

Qualification

Doctor of Philosophy (PhD)

Awarding Institution

University of Cambridge