Comparing SKF and Erbessd sensor integration for predictivemaintenance

Detta är en Kandidat-uppsats från Linköpings universitet/Institutionen för datavetenskap

Författare: William Sjöström; [2021]

Nyckelord: Predictive Maintenance;

Sammanfattning: The purpose of this thesis was to compare two integration’s of sensors, into a system called Enlight, but could in theoryhave been integrated to most systems. As a pre-study, the specifications and availability of five sensors were researched.From the pre-study, Smart Edge 4.0 and Phantom EPH-V11/10 from Erbessd, were chosen and then integrated. Usability andperformance of the integrations were then compared usingcognitive dimensions and stopwatch. Phantom from Erbessdwas deemed to be more usable, and the integration of SmartEdge 4.0, had better performance.

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