Uppsats

Implementering av OEE på en äldre stansmaskin : Retrofitting med fokus på datakommunikation

Kandidat-uppsats

Högskolan i Halmstad/Akademin för informationsteknologi

Publicerad: 2025

Språk: Svenska

Sammanfattning

Overall Equipment Effectiveness (OEE) is a key performance indicator used to evaluate a machine’s efficiency based on three main components: availability, performance, and quality. A low OEE value indicates that the machine’s capacity is not being fully utilized and should therefore be interpreted in relation to these three factors.The purpose of this work has been to develop an external and non-invasive system for production monitoring and OEE calculation for the older, semi-automatic punching machine GEKA 3217, which lacks any built-in data acquisition capabilities. The system is composed of IO-Link sensors, a safety mat, button and machine signals, an IO-Link master, CloudRail, and cloud-based services. The collected data was processed in Microsoft Fabric, enabling a continuous flow of real-time information. Due to the semi-automatic nature of the machine, the manual handling introduced certain challenges in both data collection and interpretation.The results show that the system performs as intended under normal conditions. Some limitations were observed at high movement speeds and low load on the safety mat, but these are considered marginal in practice. The machine showed an average OEE value of 11.6 %, which is considered low when compared to both established reference levels and the performance of a similar machine studied in previous research. This difference is likely due to the higher machine utilization and degree of automation in the reference case. The results demonstrate that it is possible to extract relevant production data from older machines without replacing equipment or modifying the machine’s internal control system. The general methodology presented in this study can be reused in similar applications, although the choice of sensors should be adapted to the specific machine configuration.

Information

Lärosäte / institution
Högskolan i Halmstad/Akademin för informationsteknologi
Publiceringsdatum
2025
Uppsatstyp
Kandidat-uppsats
Språk
Svenska

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