{"id":7555,"date":"2025-05-15T13:09:25","date_gmt":"2025-05-15T11:09:25","guid":{"rendered":"https:\/\/ikv-aachen.de\/rp\/process-variable-control-concept-for-injection-molding-of-thermosets\/"},"modified":"2025-05-15T15:04:39","modified_gmt":"2025-05-15T13:04:39","slug":"process-variable-control-concept-for-injection-molding-of-thermosets","status":"publish","type":"cpt_ikv_rp","link":"https:\/\/ikv-aachen.de\/en\/rp\/process-variable-control-concept-for-injection-molding-of-thermosets\/","title":{"rendered":"Process variable control concept for injection molding of thermosets"},"content":{"rendered":"<style type=\"text\/css\">\n    #single-header-block_92989d2830df83bbb2251ca48d4fd04d .swiperThumbsNavi .swiper-slide {\n        opacity: 0.4;\n    }\n\n    #single-header-block_92989d2830df83bbb2251ca48d4fd04d .swiperThumbsNavi .swiper-slide-thumb-active {\n        opacity: 1;\n    }\n<\/style>\n    <section id=\"single-header-block_92989d2830df83bbb2251ca48d4fd04d\" 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                                    <\/h2>\n                                    <div class=\"mt-base text-blue text-sm font border-l-8  border-blue pl-base my-12 leading-normal \">\n                        In injection moulding, controlling process variables instead of machine variables can improve productivity and quality. In the \u2018Thermoset control\u2019 project, this concept was applied to thermoset processing for the first time &#8211; in collaboration with the IRT and the IKV.                    <\/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=\" w-full  \"  src=\"https:\/\/ikv-aachen.de\/wp-content\/uploads\/2025\/05\/Duroplastregelung.jpg\" srcset=\"https:\/\/ikv-aachen.de\/wp-content\/uploads\/2025\/05\/Duroplastregelung-748x499.jpg 748w, https:\/\/ikv-aachen.de\/wp-content\/uploads\/2025\/05\/Duroplastregelung-1536x1024.jpg 1536w, https:\/\/ikv-aachen.de\/wp-content\/uploads\/2025\/05\/Duroplastregelung-768x512.jpg 768w\" sizes=\"auto, (max-width: 1536px) 100vw, 1536px\" width=\"1536\" height=\"1024\" alt=\"Duroplastregelung\" loading=\"lazy\" \/><span class=\" text-copyright order-3 justify-end text-right w-full  w-full \">&copy; IKV <\/span><figcaption class=\" w-full  text-figcaption justify-end text-right \">The control concept developed is based on a learning, model-predictive control system<\/figcaption><\/figure>\n\n\n<p class=\"wp-block-paragraph\">In injection moulding, process control can increase productivity and part quality by controlling process variables instead of machine variables. In the thermoset control project, such control via process variables, which previously only existed for thermoplastics, was also implemented for thermoset processing. The control system was developed with the Institute for Control Engineering at RWTH Aachen University and was implemented and analyzed in close cooperation at IKV. First, the cavity pressure curve was derived from injection moulding tests as a suitable control variable for real-time control of the process. To this end, the component quality was evaluated in terms of weight, mechanical properties and surface quality and correlated with the process variables.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Model predictive control (MPC) of the cavity pressure according to a specified reference pressure curve was implemented by adjusting the screw speed via an external, analog voltage signal on the servo inverter of the injection molding machine. The reference pressure specified by the operator could be regulated precisely and without overshooting by controlling the screw speed by specifying the control voltage. The injection molding process was described with the special material properties of the thermosets using a physical model, taking into account the volume flows and reaction kinetics, in order to incorporate process knowledge into the control system.  <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">By determining the component mass at three different pressure levels, a Gaussian process regression model (GPR) could be trained without initial process knowledge. The Gaussian process regression model identified a correlation between the cavity pressure reference and the measured component mass. Various phenolic and epoxy resins were tested as materials. Process fluctuations in the injection molding process were simulated by varying the machine settings. The process model was continuously improved through machine learning during production. The MPC achieved good results in the tests and is superior to a simple proportional-integral-differential controller (PID). Measured by the cross-cycle consistency of the cavity pressure integral and the component mass, higher process stability was achieved by controlling the cavity pressure.<\/p>\n\n\n\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\"><summary>Funding and project partners<br><\/summary>\n<p class=\"wp-block-paragraph\">We would like to thank the BMWK for funding the IGF project (funding code 22193 N) and the project partners for their cooperation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Project duration: 1.3.2022 to 30.11.2024<\/p>\n\n\n<section id=\"logo-bar-block_079279b096877b9995cc3d293e8c3548\" 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\/10\/BMWE-Logo.png\" srcset=\"https:\/\/ikv-aachen.de\/wp-content\/uploads\/2024\/10\/BMWE-Logo.png 500w, https:\/\/ikv-aachen.de\/wp-content\/uploads\/2024\/10\/BMWE-Logo-335x335.png 335w\" sizes=\"auto, (max-width: 748px) 100vw, 748px\" width=\"500\" height=\"500\" alt=\"BMWE-Logo\" loading=\"lazy\" \/><\/figure><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-IGF.png\" srcset=\"https:\/\/ikv-aachen.de\/wp-content\/uploads\/2024\/12\/Logo-IGF-748x591.png 748w\" sizes=\"auto, (max-width: 748px) 100vw, 748px\" width=\"748\" height=\"591\" alt=\"Logo-IGF\" loading=\"lazy\" \/><\/figure>                                <\/div>\n    <\/div>\n<\/section>\n<\/details>\n","protected":false},"excerpt":{"rendered":"<p>In injection moulding, control via process variables instead of machine variables can improve productivity and quality. In the &#8220;Thermoset control&#8221; project, this concept was applied to thermoset processing for the first time &#8211; in collaboration with the IRT and the IKV.<\/p>\n","protected":false},"featured_media":7554,"parent":0,"template":"","tags":[838,921,994],"research_fields":[813],"class_list":["post-7555","cpt_ikv_rp","type-cpt_ikv_rp","status-publish","has-post-thumbnail","hentry","tag-regelungsstrategie-en","tag-injection-moulding","tag-simulation-en-2","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>Process variable control concept for injection molding of thermosets | IKV-Aachen<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ikv-aachen.de\/en\/rp\/process-variable-control-concept-for-injection-molding-of-thermosets\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Process variable control concept for injection molding of thermosets | IKV-Aachen\" \/>\n<meta property=\"og:description\" content=\"In injection moulding, control via process variables instead of machine variables can improve productivity and quality. 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