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Optimizing automation design: Highlighting key factors with an innovative assessment matrix: Concluded with a case study to validate
University West, Department of Engineering Science.
2023 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Automation is a broad topic with many difficulties. Without extensive knowledge of the subject, it’s easy to forget important aspects when a production line is to be automated. This degree project aims to assist companies with this process by constructing an assessment matrix that will from asking different questions generalize the intended process and give feedback on a suitable strategy for automating it. The assessment matrix is in this degree project tested with Ultramare AB, a Swedish producer of air filters, in one of their manual production lines. To be able to construct the assessment matrix and understand what questions to include and exclude the project started with an extensive literature study. The literature study aimed to distinguish important factors in automation as well as understand what difficulties might arise when going from manual production to automated.

The assessment matrix was capable of predicting a suitable way to continue with their design phase and a crude simulation has been done for all automation parts to showcase the results obtained. While the assessment matrix is at an acceptable level of gaining results it was clear during the literature review that there is much potential to go further with a tool like this. This degree project has scraped the surface on all sub-subjects to create a basis to work with during this time limit. but if one is to delve deeper into the subject much more can be found and constructed to create a larger, more accurate assessment matrix.

Place, publisher, year, edition, pages
2023. , p. 42
Keywords [en]
assessment matrix, automation, production, optimization
National Category
Robotics
Identifiers
URN: urn:nbn:se:hv:diva-20587Local ID: EXC915OAI: oai:DiVA.org:hv-20587DiVA, id: diva2:1783183
Subject / course
Robotics
Educational program
Master i robotik och automation
Supervisors
Examiners
Available from: 2023-07-19 Created: 2023-07-19 Last updated: 2023-07-19Bibliographically approved

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