Spremljanje delovanja proizvodne linije z obdelavo podatkov na robu in vizualizacijo v oblaku

BLAŽUN, ALJAŽ (author), Mušič, Gašper (mentor), Tomažič, Simon (co-mentor)

Magistrsko delo predstavlja sistem za spremljanje in analizo modularnega proizvodnega sistema, ki deluje na robni napravi. Povezuje dva Siemensova izdelka, krmilnik S7-1200 na eni strani in oblačno platformo MindSphere na drugi. Raspberry Pi 3B + predstavlja robno napravo, na kateri se dogaja vse izračunavanje. Zbira podatke iz petih krmilnikov, jih analizira in reducirane podatke pošilja na strežnik v oblaku. Robna naprava zaznava nepravilno delovanje sistema, ob pojavu napak lahko proizvodnjo ustavi ter opozori operaterja. Dodatna funkcionalnost je možnost razvrščanja obdelovancev po barvi in njihovo usmerjanje v določeno skladišče, odvisno od vnaprej določenih pogojev. Vse procese je mogoče spremljati in opazovati na uporabniškem vmesniku, zgrajenem v okolju Node-Red. Obdelani podatki se hranijo v oblačnem strežniku, ki ima zmožnost interaktivnega prikazovanja le teh.

• Language: Slovenian
• Keywords: MindShpere, IoT, robna naprava, Siemens, računalništvo na robu, Node-Red, Raspberry Pi
• Work type: Master's thesis/paper
• Organization: FE - Faculty of Electrical Engineering
• Year: 2022
• PID: 20.500.12556/RUL-135856
• COBISS.SI-ID: 104477187
• Publication date in RUL: 30.03.2022

Secondary language

• Language: English
• Title: Production line operation monitoring with edge processing and visualization in the cloud

Abstract

Master's thesis presents a system for monitoring and analyzing the modular production system running on the edge device. It connects two Siemens products, controller S7-1200 on one side and cloud platform MindSphere on the other. Raspberry Pi 3B + presents the edge device, where all the computing happens. It collects data from five controllers, analyzes them, and sends reduced data to the cloud server. Edge device has also implemented error alerts, which can stop the production and alert the operator in case of malfunction. Additional functionality is the ability to classify the workpiece by color and direct it to the specific warehouse, depending on predefined conditions. All processes can be monitored and observed on the dashboard, built-in Node-Red environment. Processed data are stored on cloud server MindSphere, which has abillity to display them interactively.

• Keywords: MindSphere, Siemens, IoT, edge device, edge computing, Node-Red, Raspberry Pi