Discrete event simulation of production flow at Siemens energy: With focus on decision support system for statistical process control considering AI
2022 (Engelska) Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hp
Studentuppsats (Examensarbete)
Abstract [en]
Optimisation of the production workflow is a complicated task, since it is nearly impossible for a person to predict bottlenecks and rising cycle times. Discrete event simulations are built with a purpose of monitoring and predicting such problems occurring. But all information from simulations should be analysed by a final user. In order to create a process for prediction and optimization two automated methods were developed in this project. The first method utilize statistical methods for monitoring separate stations. The second method is using machine learning methods for analysing the whole simulation at once to investigate…
Ort, förlag, år, upplaga, sidor 2022. , s. 35
Nyckelord [en]
Process control, Statistics, Simulation, Artificial Intelligence, Machine learning
Nationell ämneskategori
Robotteknik och automation
Identifikatorer URN: urn:nbn:se:hv:diva-18928 Lokalt ID: EXC915 OAI: oai:DiVA.org:hv-18928 DiVA, id: diva2:1682494
Ämne / kurs Robotteknik
Utbildningsprogram Master i robotik och automation
Handledare
Examinatorer
Anmärkning The study was carried out within the AHIL-project, Artificial and Human Intelligence through Learning, funded by the Swedish Knowledge Foundation and University West
2022-08-242022-07-112023-03-01 Bibliografiskt granskad