Design Thinking

Manufacturing companies are currently struggling with the need to deal with ever changing marker requirements and technological advances. They can develop the reconfigurability capability in their factories in order to deal with such context. Moreover, companies can implement shop floor digitalisation to enhance their reconfigurability. This paper sustains two arguments: (i) the possibility to enhance diagnosability as a critical reconfigurability characteristic through shop floor digitalisation; and (ii) the relevance of the human role in reaching diagnosability in a digitalised shop floor. The paper first presents a literature review and based on this, aspects of shop floor digitalisation supporting operators in enhancing the diagnosability are identified and synthesized in a 3-e model (error reduction, ergonomics, and easiness). Secondly, insights from a case study are interpreted through the literature-based model in order to both consolidate the theoretical results and emphasize the implications for practitioners. The findings of this paper indicate that the proposed model can support practitioners in taking specific actions in regard to shop floor digitalisation in order to improve operator-dependent diagnosability and, in turn, the reconfigurability capability.

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Investigating the Performance of the Order-Picking Process by Using Smart Glasses: A Laboratory Experimental Approach

Chondromatidis

Gialos

Zeimpekis

2022

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Background: Order picking process is critical for accurate and efficient order fulfilment. Pick-by-vision is a promising technology that may support order picking process, however there is still a limited amount of research concerning the impact of this technology on the performance of order-picking. The purpose of this paper is to investigate certain operational and technical parameters that affect the performance of pick-by-vision technology in item-level order picking via a series of laboratory tests. Methods: A systematic literature review is conducted for the identification of parameters that affect pick-by-vision performance. Subsequently, the analytical hierarchy process is adopted to rank these parameters, concerning their impact on order picking. Then, the design of experiment and NASA task load index methodology are implemented for assessing pick-by-vision efficiency and perceived workload. Results: The results reveal the parameters that significantly affect the performance of the pick-by-vision system, as well as the best configuration of parameters for the implementation of the proposed system in real environments. Conclusions: The results obtained are encouraging, showing how pick-by-vision technology can support order picking efficiency. Furthermore, practical implications are presented that deal with the organizational culture, process re-engineering, staff resistance to change, and motivation for maintaining the new way of executing order-picking processes.

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Design Thinking

Cited by 4 publications

References 7 publications

Designing a User-Centered Approach to Improve Acceptance of Innovations on the Shop Floor Using Rogers’ ‘Diffusion of Innovations’

Designing a User-Centered Approach to Improve Acceptance of Innovations on the Shop Floor Using Rogers’ ‘Diffusion of Innovations’

Reconfigurable Manufacturing: How Shop Floor Digitalisation Supports Operators in Enhancing Diagnosability

Investigating the Performance of the Order-Picking Process by Using Smart Glasses: A Laboratory Experimental Approach

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