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- 01HMRQKQW97KVGN9KECWBQ5HZS classification C1.
- 01HMRQKQW97KVGN9KECWBQ5HZS date "2023".
- 01HMRQKQW97KVGN9KECWBQ5HZS language "eng".
- 01HMRQKQW97KVGN9KECWBQ5HZS type conference.
- 01HMRQKQW97KVGN9KECWBQ5HZS hasPart 01HMRQMEJBSHHB3DGNG7J6ZS9P.pdf.
- 01HMRQKQW97KVGN9KECWBQ5HZS hasPart 01HMRQMM1TGS1867CANEJA34YM.pdf.
- 01HMRQKQW97KVGN9KECWBQ5HZS subject "Technology and Engineering".
- 01HMRQKQW97KVGN9KECWBQ5HZS doi "10.1007/978-3-031-11150-1_4".
- 01HMRQKQW97KVGN9KECWBQ5HZS isbn "9783031111495".
- 01HMRQKQW97KVGN9KECWBQ5HZS isbn "9783031111501".
- 01HMRQKQW97KVGN9KECWBQ5HZS issn "2731-0221".
- 01HMRQKQW97KVGN9KECWBQ5HZS issn "2731-023X".
- 01HMRQKQW97KVGN9KECWBQ5HZS presentedAt urn:uuid:61832918-3ce2-4389-88fb-129572653888.
- 01HMRQKQW97KVGN9KECWBQ5HZS abstract "In this research, Artificial Intelligence (AI) was used to support the optimization of six bonding process parameters for maximal joint strength and minimal production costs. Two industrial bonding processes were investigated, one from electronic potting and another from the manufacturing industry. The focus was on optimizing the plasma treatment of the substrate materials. Two approaches for optimization were compared, namely the traditional approach where the adhesive expert proposes experiments and interpret the results, and an AI approach with Bayesian optimization and Gaussian process models. Similar joint strengths could be achieved via the Bayesian optimization approach with 40% less budget to find the optimum compared to the traditional approach. Additionally, in the electronic potting process, the AI approach resulted in 18% reduction in production cost, while achieving a similar joint strength, compared to the traditional approach. Ageing of the samples did not result in a significant drop in joint strength nor changes in failure type or mechanism. This indicates that AI can support adhesive experts to find the optimal bonding process settings and manufacture robust and cost-efficient adhesive bonds.".
- 01HMRQKQW97KVGN9KECWBQ5HZS author 17431fb0-1ba1-11ea-b634-e3dc0d189751.
- 01HMRQKQW97KVGN9KECWBQ5HZS author FC259E64-F0ED-11E1-A9DE-61C894A0A6B4.
- 01HMRQKQW97KVGN9KECWBQ5HZS author f11c4ace-d00f-11ed-91ca-a9efd99a8793.
- 01HMRQKQW97KVGN9KECWBQ5HZS author urn:uuid:3cc4a841-cda8-44f6-9b77-60ab8deafb15.
- 01HMRQKQW97KVGN9KECWBQ5HZS author urn:uuid:533fd6c9-a9dc-4c40-b676-905ce4a32548.
- 01HMRQKQW97KVGN9KECWBQ5HZS author urn:uuid:c6d4b2dc-0c70-4dcb-bb81-b34c366e3ec9.
- 01HMRQKQW97KVGN9KECWBQ5HZS author urn:uuid:d884c234-36ba-4f27-b2f8-83ec8751c2e3.
- 01HMRQKQW97KVGN9KECWBQ5HZS dateCreated "2024-01-22T14:01:27Z".
- 01HMRQKQW97KVGN9KECWBQ5HZS dateModified "2024-10-29T18:29:23Z".
- 01HMRQKQW97KVGN9KECWBQ5HZS editor urn:uuid:5688e4b2-0bac-4ee0-b6c8-5225fefcaa35.
- 01HMRQKQW97KVGN9KECWBQ5HZS editor urn:uuid:e2fe9dd0-d35f-44dd-b7f2-6ddff942fd66.
- 01HMRQKQW97KVGN9KECWBQ5HZS editor urn:uuid:f2d20b2a-4038-4e1b-bab3-9489c3f93b8a.
- 01HMRQKQW97KVGN9KECWBQ5HZS name "Optimization of plasma-assisted surface treatment for adhesive bonding via artificial intelligence".
- 01HMRQKQW97KVGN9KECWBQ5HZS pagination urn:uuid:3323a4d2-0565-49e8-b943-aa4ed552e24b.
- 01HMRQKQW97KVGN9KECWBQ5HZS publisher urn:uuid:7e619deb-ab12-4667-87c6-b13d02b69563.
- 01HMRQKQW97KVGN9KECWBQ5HZS sameAs LU-01HMRQKQW97KVGN9KECWBQ5HZS.
- 01HMRQKQW97KVGN9KECWBQ5HZS sourceOrganization urn:uuid:1d717a03-474f-4208-a9c8-163c6c13ff1f.
- 01HMRQKQW97KVGN9KECWBQ5HZS sourceOrganization urn:uuid:dd8b89ed-78e6-4006-a329-ac2ca9943423.
- 01HMRQKQW97KVGN9KECWBQ5HZS type C1.