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Organisational enablers and barriers in machine vision system implementation
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School of Science |
Master's thesis
Electronic archive copy is available via Aalto Thesis Database.
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en
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61
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Abstract
This study is a journey of evaluating and analysing implementation of automated machine vision inspection systems for the quality control of passport booklet data pages within a security printing context. While existing literature focuses heavily on technical aspects of machine vision—such as algorithms, lighting, and system design—this case study shifts the focus toward organisational and operational factors influencing successful implementation. It compares three factories using similar inspection equipment but experiencing notably different results, prompting investigation into the role of continuous improvement practices and organisational features.
The study was conducted through site visits, hands-on action research, follow-up meetings, and ongoing communication across three factories. It tries to stay away from technology and keep the focus on organisation and methods. Action research trials focused on identifying degree of false rejects and improving inspection efficiency. Observations from these trials, supported by an anthropological fieldwork approach, were used to identify organisational factors influencing fluency of implementation. The methodology blended case study, continuous improvement tools, and participatory observation to understand both process performance and its organisational context.
The research shows quantitative differences between factories results, but what is more interesting are observations done while measuring the quantitative differences. A concrete improvement mechanism and local learning organisation cluster were identified. Possible approaches to convey best practices to organisational memory and across subsidiaries are proposed as future opportunities to leverage learning organisation becoming global.