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Evaluation of Industrial Pilots of Low-Cost Digital (Shoestring) Solutions

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Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future (SOHOMA 2023)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1136))

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Abstract

The Shoestring approach represents a methodology for systematically specifying, design and deploying industrial digital solutions based on very low-cost components and limited development time. A key characteristic of the Shoestring approach is the direct involvement of personnel from the end user company in the specification and deployment process. This paper presents an evaluation of the first pilot deployments of Shoestring solutions which took place between 2019 and 2022 in SME manufacturers in the UK. Although only a handful of pilots were planned for this period, in fact 20 industrial pilot deployments took place. The approach taken for deployments in described and qualitative evaluation of the pilot presented. Some of the key findings are that the direct involvement of end user personnel ensures an effective engagement and all but one pilot was successfully deployed and trialled - each with significant involvement from the end user. In evaluation, most of the pilots achieved the benefits expected, and interestingly a number of the companies retrospectively identified additional benefits from their pilot that were not initially anticipated. Finally, it is noted that many of these deployments occurred when COVID-19 restrictions were in place. Ironically, the enforced restrictions may well have contributed to a greater number of pilots being undertaken and an acceleration of remote-support capabilities for the approach.

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Correspondence to Duncan McFarlane .

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McFarlane, D., Hawkridge, G., de Silva, L., Salter, L. (2024). Evaluation of Industrial Pilots of Low-Cost Digital (Shoestring) Solutions. In: Borangiu, T., Trentesaux, D., Leitão, P., Berrah, L., Jimenez, JF. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2023. Studies in Computational Intelligence, vol 1136. Springer, Cham. https://doi.org/10.1007/978-3-031-53445-4_25

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