Uppsats

Visualising Manufacturing Data within Life Science Companies : Design Considerations and Impact

Kandidat-uppsats

KTH/Skolan för elektroteknik och datavetenskap (EECS)

Publicerad: 2024

Språk: Engelska

Sammanfattning

Analysing data generated in production processes has the potential to provide insight on areas of improvement. The insights can be used to increase production efficiency, reduce costs and minimise waste. This is beneficial from a business standpoint. Moreover, widening the perspective, companies making these improvements ultimately benefit society at large, contributing to a more sustainable production process. This study aims to identify crucial factors when visualising production data in a usable interface, and the impact of this visualisation on processes within a Life Science company. Considering previous research on Human Computer Interaction and Data Visualisation, a data visualisation tool was designed iteratively and evaluated using usability testing and qualitative interviews. The study concludes multiple crucial design elements to consider when designing a visualisation tool for production data. Colour and graphics largely contributed to a pleasant user experience. Both text-based and graphical elements were used to complement each other, since they serve different purposes when analysing production data. This was an appreciated approach. Icons should be used thoughtfully and terminology should be decided in collaboration with users. In situations where comparisons might be needed, displaying all information necessary should be prioritised over a minimalist design. It was concluded that the introduction of a visualisation tool for production data has multiple positive effects on the organisation. Graphical representations of data facilitate communication with stakeholders. The tool can also help identify areas in need of efficiency improvements. Finally, a visualisation tool standardises the process of analysing production data and thereby makes the company less dependent on key employees.

Information

Lärosäte / institution
KTH/Skolan för elektroteknik och datavetenskap (EECS)
Publiceringsdatum
2024
Uppsatstyp
Kandidat-uppsats
Språk
Engelska

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