{"id":3364,"date":"2024-10-10T08:20:52","date_gmt":"2024-10-10T08:20:52","guid":{"rendered":"https:\/\/ikv-aachen.de\/rp\/optiplast-regelung-der-dosierphase-beim-spritzgiessen-auf-basis-von-prozesskennzahlen\/"},"modified":"2024-12-18T13:28:49","modified_gmt":"2024-12-18T13:28:49","slug":"optiplast-control-of-the-dosing-phase-in-injection-moulding-based-on-process-parameters","status":"publish","type":"cpt_ikv_rp","link":"https:\/\/ikv-aachen.de\/en\/rp\/optiplast-control-of-the-dosing-phase-in-injection-moulding-based-on-process-parameters\/","title":{"rendered":"OptiPlast &#8211; Control of the dosing phase in injection moulding based on process parameters"},"content":{"rendered":"<style type=\"text\/css\">\n    #single-header-block_391061c4996ed46794545c3b107bd00a .swiperThumbsNavi .swiper-slide {\n        opacity: 0.4;\n    }\n\n    #single-header-block_391061c4996ed46794545c3b107bd00a .swiperThumbsNavi .swiper-slide-thumb-active {\n        opacity: 1;\n    }\n<\/style>\n    <section id=\"single-header-block_391061c4996ed46794545c3b107bd00a\" class=\"block-single-header theGridWrapper \">\n        <div class=\"theGrid12\">\n            <div class=\" col-start-2 col-span-10 md:col-start-3  md:col-span-8\">\n                <h2 class=\"font-serif font-semibold text-blue text-sm w-4\/5\">\n                    Control of the dosing phase in injection molding based on process indicators to optimize melt homogeneity and energy efficiency                <\/h2>\n                                    <div class=\"mt-base text-blue text-sm font border-l-8  border-blue pl-base my-12 leading-normal \">\n                        The research project aims to analyze the relationships between process parameters, material properties, and resulting quality factors such as axial melt temperature distribution, dosing time, and energy demand. Through model-based investigation of the plasticizing and dwell phases, optimization strategies for melt homogeneity, plasticizing performance, and energy consumption are to be developed and implemented in the Paderborn Injection Molding Simulation (PSI).                    <\/div>\n                                            <\/div>\n        <\/div>\n    <\/section>\n\n\n<figure class=\" relative flex flex-col gap-2xs mb-xs md:mb-l xl:mb-xl\"><img decoding=\"async\"  class=\" max-w-[50vh]  md:max-w-screen-sm  \"  src=\"https:\/\/ikv-aachen.de\/wp-content\/uploads\/2024\/10\/HO4776-86-1_Abnahme-der-wirksamen-Schneckenlaenge-waehrend-des-Plastifiziervorgangs.png\" srcset=\"https:\/\/ikv-aachen.de\/wp-content\/uploads\/2024\/10\/HO4776-86-1_Abnahme-der-wirksamen-Schneckenlaenge-waehrend-des-Plastifiziervorgangs-748x515.png 748w, https:\/\/ikv-aachen.de\/wp-content\/uploads\/2024\/10\/HO4776-86-1_Abnahme-der-wirksamen-Schneckenlaenge-waehrend-des-Plastifiziervorgangs-1536x1058.png 1536w, https:\/\/ikv-aachen.de\/wp-content\/uploads\/2024\/10\/HO4776-86-1_Abnahme-der-wirksamen-Schneckenlaenge-waehrend-des-Plastifiziervorgangs-768x529.png 768w\" sizes=\"auto, (max-width: 1536px) 100vw, 1536px\" width=\"1536\" height=\"1058\" alt=\"Optiplast eng\" loading=\"lazy\" \/><span class=\" text-copyright order-3 justify-end text-right w-full  max-w-[50vh]  md:max-w-screen-sm \">&copy; IKV<\/span><figcaption class=\" max-w-[50vh]  md:max-w-screen-sm  text-figcaption justify-end text-right \">Decrease of effective screw length during the plastication prozess<\/figcaption><\/figure>\n\n\n<p class=\"wp-block-paragraph\">Due to the translatory backward movement of the screw during injection moulding, the effective screw length decreases during dosing. In conjunction with the cyclical operation of the injection moulding process, this leads to an inhomogeneous axial temperature profile of the melt in the screw vestibule.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Such temperature inhomogeneity can have a negative effect on the resulting component properties and limits the maximum dosing stroke of the injection moulding screw. In addition to melt homogeneity, there are two other criteria for the dosing phase: the plasticising capacity (mass throughput) and the energy requirement. If the plasticising capacity is too low or the dosing time too long, the cycle time increases. This reduces the economic efficiency of the process. Since a large part of the energy requirement in the injection moulding process is accounted for by plasticising, the dosing phase is also very important in terms of energy.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The aim of this project is to investigate the interactions between process variables, material properties, process parameters and the resulting quality variables axial melt temperature distribution in the screw antechamber, dosing time and energy consumption with an accompanying modelling of the plasticising and standstill phase and subsequent implementation in PSI (Parderborn Injection Moulding Simulation). This fundamental investigation is intended to generate important findings for the subsequent development and implementation of a control system based on process parameters in order to dose the melt as homogeneously and energy-efficiently as possible while specifying the dosing time. This is to be achieved in particular for critical conditions such as a large dosing stroke and a short cycle time. This understanding should help to exploit the potential of modern injection moulding machines in terms of dosing volume and plasticising performance and to reduce rejects as well as material and energy costs.<\/p>\n\n\n\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>Project data and funding<\/summary>\n<p class=\"wp-block-paragraph\"><strong>Project duration:<\/strong> 01.2024 &#8211; 12.2026<br><strong>Funding code:<\/strong> HO 4776\/86-1<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><br>We would like to thank all project partners and the DFG for funding the project under grant number HO 4776\/86-1.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Project partners and funding<\/strong><\/h2>\n\n\n<section id=\"logo-bar-block_192952b3565372b0335f4b07b47337b2\" class=\"block-logo-bar py-2xl  clear-both\">\n    <div class=\"theGridWrapper overflow-hidden  \">\n        <div class=\"grid grid-cols-[repeat(auto-fill,minmax(140px,1fr))] gap-base\">\n                            <figure class=\" relative h-full  \"><img decoding=\"async\" fetchpriority=\"low\"  class=\" object-contain w-full h-full mb-base  \"  src=\"https:\/\/ikv-aachen.de\/wp-content\/uploads\/2024\/12\/Logo-DFG.png\" srcset=\"https:\/\/ikv-aachen.de\/wp-content\/uploads\/2024\/12\/Logo-DFG-748x591.png 748w\" sizes=\"auto, (max-width: 748px) 100vw, 748px\" width=\"748\" height=\"591\" alt=\"Logo-DFG\" loading=\"lazy\" \/><\/figure>                                <\/div>\n    <\/div>\n<\/section>\n<\/details>\n\n\n\n<h2 class=\"wp-block-heading\">Keywords<\/h2>\n","protected":false},"excerpt":{"rendered":"<p>The research project aims to analyze the relationships between process parameters, material properties, and resulting quality factors such as axial melt temperature distribution, dosing time, and energy demand. Through model-based investigation of the plasticizing and dwell phases, optimization strategies for melt homogeneity, plasticizing performance, and energy consumption are to be developed and implemented in the Paderborn Injection Molding Simulation (PSI).<\/p>\n","protected":false},"featured_media":3205,"parent":0,"template":"","tags":[857,921,860,923],"research_fields":[625,813],"class_list":["post-3364","cpt_ikv_rp","type-cpt_ikv_rp","status-publish","has-post-thumbnail","hentry","tag-artificial-interlligence","tag-injection-moulding","tag-process-control","tag-simulation","research_fields-digitalisierung","research_fields-injection-moulding"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>OptiPlast - Control of the dosing phase in injection moulding based on process parameters | IKV-Aachen<\/title>\n<meta name=\"description\" content=\"The research project aims to analyze the relationships between process parameters, material properties, and resulting quality factors such as axial melt temperature distribution, dosing time, and energy demand. 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