{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T15:11:09Z","timestamp":1774883469855,"version":"3.50.1"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Project Data Based Expert System for Process Efficiency (DEEPEN), funded by the Austrian Research Promotion Agency (FFG) through the 41st Call of the Initiative \u201cProduction of the Future,\u201d","award":["891247"],"award-info":[{"award-number":["891247"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3614061","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T17:34:19Z","timestamp":1758735259000},"page":"168344-168360","source":"Crossref","is-referenced-by-count":3,"title":["End-to-End Process Optimization in Polymer Extrusion Lines Using Model Predictive Control and Multi-Task Learning"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6431-2682","authenticated-orcid":false,"given":"Raphael","family":"Hartner","sequence":"first","affiliation":[{"name":"Institute of Industrial Management, University of Applied Sciences FH JOANNEUM, Kapfenberg, Austria"}]},{"given":"Martin","family":"Kozek","sequence":"additional","affiliation":[{"name":"Institute of Mechanics and Mechatronics, Vienna University of Technology, Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7017-4024","authenticated-orcid":false,"given":"Stefan","family":"Jakubek","sequence":"additional","affiliation":[{"name":"Institute of Mechanics and Mechatronics, Vienna University of Technology, Vienna, Austria"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.applthermaleng.2024.124483"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSTCC.2016.7790666"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.polymertesting.2018.06.002"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1021\/ie301036c"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/STA56120.2022.10019045"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-56990-776-4"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3390\/pr8091068"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/S0032-5910(99)00254-5"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.23919\/ECC57647.2023.10178125"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1088\/1757-899X\/1257\/1\/012034"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-025-02647-9"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1002\/pen.21646"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/IEEM.2018.8607816"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-018-1418-7"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2022.12.207"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/AIIM64537.2024.10934491"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3390\/molecules30091879"},{"issue":"1","key":"ref18","article-title":"Machine learning assisted optimization of blending process of polyphenylene sulfide with elastomer using high speed twin screw extruder","volume-title":"Sci. Rep.","volume":"11","author":"Takada","year":"2021"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.ieri.2013.11.029"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-021-01792-1"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1080\/00224065.2021.1903822"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1080\/24725854.2023.2242434"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmsy.2024.03.007"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-025-02616-2"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAE.2010.5451832"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2013.08.084"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2016.03.008"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.23919\/ECC64448.2024.10590713"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CoDIT62066.2024.10708259"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3377467"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2020.3038028"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2021.08.246"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2023.10.1460"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2011.07.001"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2020.03.013"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-024-14061-1"},{"issue":"8","key":"ref37","doi-asserted-by":"crossref","DOI":"10.1002\/adem.202401316","article-title":"Smart rubber extrusion line combining multiple sensor techniques for AI-based process control","volume":"27","author":"Aschemann","year":"2024","journal-title":"Adv. Eng. Mater."},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2020.e04289"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1137\/S1064827595289108"},{"key":"ref40","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2017","journal-title":"arXiv:1412.6980"},{"key":"ref41","article-title":"SGDR: Stochastic gradient descent with warm restarts","author":"Loshchilov","year":"2017","journal-title":"arXiv:1608.03983"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.arcontrol.2021.10.006"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2023.103028"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2021.107291"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3563300"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2023.3326154"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/11177489.pdf?arnumber=11177489","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T05:30:44Z","timestamp":1759296644000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11177489\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3614061","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}