{"id":16533,"date":"2020-07-22T08:00:05","date_gmt":"2020-07-22T06:00:05","guid":{"rendered":"https:\/\/zema.de\/?post_type=dt_portfolio&#038;p=16533"},"modified":"2020-07-22T12:12:56","modified_gmt":"2020-07-22T10:12:56","slug":"easy-ml","status":"publish","type":"dt_portfolio","link":"https:\/\/zema.de\/en\/projekt\/easy-ml\/","title":{"rendered":"EaSy ML"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><div class=\"vc_row wpb_row vc_row-fluid\"><div class=\"wpb_column vc_column_container vc_col-sm-12\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8da09e\" data-id=\"69e0b5d8da09e\" data-height=\"30\" data-height-mobile=\"30\" data-height-tab=\"30\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><div class=\"hr-thin style-line\" style=\"width: 100%;border-top-width: 1px;\"><\/div><div class=\"ult-spacer spacer-69e0b5d8da0d0\" data-id=\"69e0b5d8da0d0\" data-height=\"30\" data-height-mobile=\"30\" data-height-tab=\"30\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><div class=\"dt-fancy-separator h1-size\" style=\"width: 100%;\"><div class=\"dt-fancy-title\"><span class=\"separator-holder separator-left\"><\/span>EaSy ML - Assistance Evaluation System for Machine Learning<span class=\"separator-holder separator-right\"><\/span><\/div><\/div><\/div><\/div><\/div><\/div><div class=\"vc_row wpb_row vc_row-fluid\"><div class=\"wpb_column vc_column_container vc_col-sm-12\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8da6d7\" data-id=\"69e0b5d8da6d7\" data-height=\"30\" data-height-mobile=\"30\" data-height-tab=\"30\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><div class=\"hr-thin style-line\" style=\"width: 100%;border-top-width: 1px;\"><\/div><\/div><\/div><\/div><\/div><div class=\"vc_row wpb_row vc_row-fluid wpb_animate_when_almost_visible wpb_slideInUp slideInUp\"><div class=\"right wpb_column vc_column_container vc_col-sm-8\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8dab33\" data-id=\"69e0b5d8dab33\" data-height=\"30\" data-height-mobile=\"30\" data-height-tab=\"30\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><style type=\"text\/css\" data-type=\"the7_shortcodes-inline-css\">.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon {\n  width: 128px;\n  height: 128px;\n  line-height: 128px;\n  font-size: 64px;\n  border-radius: 200px;\n  margin: 45px 0px 0px 60px;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon .icon-inner {\n  min-width: 128px;\n  min-height: 128px;\n  border-radius: 200px;\n}\n@media all and (-ms-high-contrast: none) {\n  .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon .icon-inner {\n    height: 128px;\n  }\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon .dt-hover-icon {\n  line-height: 128px;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon:before,\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon:after,\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon .icon-inner:before,\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon .icon-inner:after {\n  min-width: 100%;\n  min-height: 100%;\n  padding: inherit;\n  border-radius: inherit;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-on:before {\n  border-width: 2px;\n  border-style: solid;\n}\n.dt-icon-border-dashed.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-on:before {\n  border-style: dashed;\n}\n.dt-icon-border-dotted.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-on:before {\n  border-style: dotted;\n}\n.dt-icon-border-double.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-on:before {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-dashed.dt-icon-border-on:before {\n  border-style: dashed;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-dotted.dt-icon-border-on:before {\n  border-style: dotted;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-double.dt-icon-border-on:before {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-border-on:after {\n  border-width: 2px;\n  border-style: solid;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-dashed.dt-icon-hover-border-on:after {\n  border-style: dashed;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-dotted.dt-icon-hover-border-on:after {\n  border-style: dotted;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-border-double.dt-icon-hover-border-on:after {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-on:hover {\n  font-size: 64px;\n}\n#page .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-on:hover .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-on:hover .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-on:hover .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-on:hover .soc-icon {\n  color: #fff;\n  background: none;\n}\n#page .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-on:not(:hover) .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-on:not(:hover) .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-on:not(:hover) .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-on:not(:hover) .soc-icon,\n#page .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-off .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-off .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-off .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .text-icon.dt-icon-hover-off .soc-icon {\n  color: #ffffff;\n  background: none;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b.layout-1 {\n  grid-template-columns: 128px minmax(0,1fr);\n  grid-column-gap: 60px;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b.layout-2 {\n  grid-template-columns: minmax(0,1fr) 128px;\n  grid-column-gap: 60px;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b.layout-2 .text-icon {\n  margin-left: 0;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b.layout-3 {\n  grid-template-columns: 128px minmax(0,1fr);\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b.layout-3 .dt-text-title {\n  margin-left: 0px;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .dt-text-title,\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .dt-text-title a {\n  color: #558398;\n  background: none;\n  font-weight: bold;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .dt-text-title {\n  margin-bottom: 10px;\n}\n.icon-with-text-shortcode.icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b .dt-text-desc {\n  margin-bottom: 30px;\n}<\/style><div class=\"icon-with-text-shortcode  icon-text-id-6bdc12c082e0e3c0d3b01a5ff7e2091b layout-2\" ><span   class=\"text-icon dt-icon-bg-on dt-icon-hover-off\" ><span class=\"icon-inner\"><i class=\"dt-regular-icon soc-icon Defaults-exclamation\"><\/i><i class=\"dt-hover-icon soc-icon Defaults-exclamation\"><\/i><\/span><\/span><h3 class=\"dt-text-title\"  >problem<\/h3><div class=\"dt-text-desc\">Cost-optimized production combined with high process and product quality is a central promise of Industry 4.0 and the associated digitalization.<br \/>\nThere are numerous examples of how machine learning (ML) techniques help to analyze data, gain new insights into production, and optimize production.<br \/>\nHowever, a superficial understanding of the algorithms and procedures is often not enough to draw meaningful conclusions from the production data.<\/div><\/div><div class=\"hr-thin style-dotted\" style=\"width: 100%;border-top-width: 1px;\"><\/div><\/div><\/div><\/div><div class=\"wpb_column vc_column_container vc_col-sm-4\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8dae11\" data-id=\"69e0b5d8dae11\" data-height=\"105\" data-height-mobile=\"105\" data-height-tab=\"105\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><\/div><\/div><\/div><\/div><div class=\"vc_row wpb_row vc_row-fluid wpb_animate_when_almost_visible wpb_slideInUp slideInUp\"><div class=\"wpb_column vc_column_container vc_col-sm-4\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8db244\" data-id=\"69e0b5d8db244\" data-height=\"95\" data-height-mobile=\"95\" data-height-tab=\"95\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><\/div><\/div><\/div><div class=\"wpb_column vc_column_container vc_col-sm-8\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8db3e1\" data-id=\"69e0b5d8db3e1\" data-height=\"30\" data-height-mobile=\"30\" data-height-tab=\"30\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><style type=\"text\/css\" data-type=\"the7_shortcodes-inline-css\">.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon {\n  width: 128px;\n  height: 128px;\n  line-height: 128px;\n  font-size: 64px;\n  border-radius: 200px;\n  margin: 15px 60px 0px 0px;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon .icon-inner {\n  min-width: 128px;\n  min-height: 128px;\n  border-radius: 200px;\n}\n@media all and (-ms-high-contrast: none) {\n  .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon .icon-inner {\n    height: 128px;\n  }\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon .dt-hover-icon {\n  line-height: 128px;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon:before,\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon:after,\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon .icon-inner:before,\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon .icon-inner:after {\n  min-width: 100%;\n  min-height: 100%;\n  padding: inherit;\n  border-radius: inherit;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-on:before {\n  border-width: 2px;\n  border-style: solid;\n}\n.dt-icon-border-dashed.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-on:before {\n  border-style: dashed;\n}\n.dt-icon-border-dotted.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-on:before {\n  border-style: dotted;\n}\n.dt-icon-border-double.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-on:before {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-dashed.dt-icon-border-on:before {\n  border-style: dashed;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-dotted.dt-icon-border-on:before {\n  border-style: dotted;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-double.dt-icon-border-on:before {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-border-on:after {\n  border-width: 2px;\n  border-style: solid;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-dashed.dt-icon-hover-border-on:after {\n  border-style: dashed;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-dotted.dt-icon-hover-border-on:after {\n  border-style: dotted;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-border-double.dt-icon-hover-border-on:after {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-on:hover {\n  font-size: 64px;\n}\n#page .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-on:hover .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-on:hover .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-on:hover .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-on:hover .soc-icon {\n  color: #fff;\n  background: none;\n}\n#page .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-on:not(:hover) .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-on:not(:hover) .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-on:not(:hover) .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-on:not(:hover) .soc-icon,\n#page .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-off .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-off .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-off .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .text-icon.dt-icon-hover-off .soc-icon {\n  color: #ffffff;\n  background: none;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f.layout-1 {\n  grid-template-columns: 128px minmax(0,1fr);\n  grid-column-gap: 60px;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f.layout-2 {\n  grid-template-columns: minmax(0,1fr) 128px;\n  grid-column-gap: 0px;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f.layout-2 .text-icon {\n  margin-left: 0;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f.layout-3 {\n  grid-template-columns: 128px minmax(0,1fr);\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f.layout-3 .dt-text-title {\n  margin-left: 60px;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .dt-text-title,\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .dt-text-title a {\n  color: #558398;\n  background: none;\n  font-weight: bold;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .dt-text-title {\n  margin-bottom: 10px;\n}\n.icon-with-text-shortcode.icon-text-id-908ee9d39fc6defb0faffe03cbf2157f .dt-text-desc {\n  margin-bottom: 30px;\n}<\/style><div class=\"icon-with-text-shortcode  icon-text-id-908ee9d39fc6defb0faffe03cbf2157f layout-1\" ><span   class=\"text-icon dt-icon-bg-on dt-icon-hover-off\" ><span class=\"icon-inner\"><i class=\"dt-regular-icon soc-icon icomoon-the7-font-the7-map-02\"><\/i><i class=\"dt-hover-icon soc-icon icomoon-the7-font-the7-map-02\"><\/i><\/span><\/span><h3 class=\"dt-text-title\"  >objective<\/h3><div class=\"dt-text-desc\">The aim of the EaSyML project is now to significantly reduce the high costs of production optimization using machine learning for SMEs by empowering the workers themselves to apply the methods and algorithms of machine learning to the collected data.<\/div><\/div><div class=\"hr-thin style-dotted\" style=\"width: 100%;border-top-width: 1px;\"><\/div><\/div><\/div><\/div><\/div><div class=\"vc_row wpb_row vc_row-fluid wpb_animate_when_almost_visible wpb_slideInUp slideInUp\"><div class=\"right wpb_column vc_column_container vc_col-sm-8\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8db92b\" data-id=\"69e0b5d8db92b\" data-height=\"30\" data-height-mobile=\"30\" data-height-tab=\"30\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><style type=\"text\/css\" data-type=\"the7_shortcodes-inline-css\">.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon {\n  width: 128px;\n  height: 128px;\n  line-height: 128px;\n  font-size: 64px;\n  border-radius: 200px;\n  margin: 120px 0px 0px 60px;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon .icon-inner {\n  min-width: 128px;\n  min-height: 128px;\n  border-radius: 200px;\n}\n@media all and (-ms-high-contrast: none) {\n  .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon .icon-inner {\n    height: 128px;\n  }\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon .dt-hover-icon {\n  line-height: 128px;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon:before,\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon:after,\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon .icon-inner:before,\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon .icon-inner:after {\n  min-width: 100%;\n  min-height: 100%;\n  padding: inherit;\n  border-radius: inherit;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-on:before {\n  border-width: 2px;\n  border-style: solid;\n}\n.dt-icon-border-dashed.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-on:before {\n  border-style: dashed;\n}\n.dt-icon-border-dotted.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-on:before {\n  border-style: dotted;\n}\n.dt-icon-border-double.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-on:before {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-dashed.dt-icon-border-on:before {\n  border-style: dashed;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-dotted.dt-icon-border-on:before {\n  border-style: dotted;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-double.dt-icon-border-on:before {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-border-on:after {\n  border-width: 2px;\n  border-style: solid;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-dashed.dt-icon-hover-border-on:after {\n  border-style: dashed;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-dotted.dt-icon-hover-border-on:after {\n  border-style: dotted;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-border-double.dt-icon-hover-border-on:after {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-on:hover {\n  font-size: 64px;\n}\n#page .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-on:hover .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-on:hover .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-on:hover .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-on:hover .soc-icon {\n  color: #fff;\n  background: none;\n}\n#page .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-on:not(:hover) .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-on:not(:hover) .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-on:not(:hover) .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-on:not(:hover) .soc-icon,\n#page .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-off .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-off .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-off .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .text-icon.dt-icon-hover-off .soc-icon {\n  color: #ffffff;\n  background: none;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202.layout-1 {\n  grid-template-columns: 128px minmax(0,1fr);\n  grid-column-gap: 60px;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202.layout-2 {\n  grid-template-columns: minmax(0,1fr) 128px;\n  grid-column-gap: 60px;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202.layout-2 .text-icon {\n  margin-left: 0;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202.layout-3 {\n  grid-template-columns: 128px minmax(0,1fr);\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202.layout-3 .dt-text-title {\n  margin-left: 0px;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .dt-text-title,\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .dt-text-title a {\n  color: #558398;\n  background: none;\n  font-weight: bold;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .dt-text-title {\n  margin-bottom: 10px;\n}\n.icon-with-text-shortcode.icon-text-id-2615030b9fba76daa29861cb7f169202 .dt-text-desc {\n  margin-bottom: 30px;\n}<\/style><div class=\"icon-with-text-shortcode  icon-text-id-2615030b9fba76daa29861cb7f169202 layout-2\" ><span   class=\"text-icon dt-icon-bg-on dt-icon-hover-off\" ><span class=\"icon-inner\"><i class=\"dt-regular-icon soc-icon icomoon-font-awesome-14x14-map-signs\"><\/i><i class=\"dt-hover-icon soc-icon icomoon-font-awesome-14x14-map-signs\"><\/i><\/span><\/span><h3 class=\"dt-text-title\"  >approach<\/h3><div class=\"dt-text-desc\">Thanks to artificial intelligence, an analysis system that complements ODION GmbH's machine data acquisition provides an intelligent tutor who supports the worker in the selection and application of machine learning methods and thus in the analysis of production data.<br \/>\nAs an expert in production, the worker can easily identify interesting questions and scenarios and check the plausibility of the analysis results provided. Insights can then be incorporated into a further, more differentiated or completely different question or evaluation by means of the AI tutor.<br \/>\nThe system should thus offer every SME the opportunity to use the know-how of the workers about their own production and machines in such a way that this knowledge is used to uncover even difficult and, due to the complex data burden for people, incomprehensible relations and facts within the production.<\/div><\/div><div class=\"hr-thin style-dotted\" style=\"width: 100%;border-top-width: 1px;\"><\/div><\/div><\/div><\/div><div class=\"wpb_column vc_column_container vc_col-sm-4\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8dbbe3\" data-id=\"69e0b5d8dbbe3\" data-height=\"140\" data-height-mobile=\"140\" data-height-tab=\"140\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><\/div><\/div><\/div><\/div><div class=\"vc_row wpb_row vc_row-fluid wpb_animate_when_almost_visible wpb_slideInUp slideInUp\"><div class=\"wpb_column vc_column_container vc_col-sm-4\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8dc04f\" data-id=\"69e0b5d8dc04f\" data-height=\"145\" data-height-mobile=\"145\" data-height-tab=\"145\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><\/div><\/div><\/div><div class=\"wpb_column vc_column_container vc_col-sm-8\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><div class=\"ult-spacer spacer-69e0b5d8dc20e\" data-id=\"69e0b5d8dc20e\" data-height=\"30\" data-height-mobile=\"30\" data-height-tab=\"30\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"\" style=\"clear:both;display:block;\"><\/div><style type=\"text\/css\" data-type=\"the7_shortcodes-inline-css\">.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon {\n  width: 128px;\n  height: 128px;\n  line-height: 128px;\n  font-size: 64px;\n  border-radius: 200px;\n  margin: 150px 60px 0px 0px;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon .icon-inner {\n  min-width: 128px;\n  min-height: 128px;\n  border-radius: 200px;\n}\n@media all and (-ms-high-contrast: none) {\n  .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon .icon-inner {\n    height: 128px;\n  }\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon .dt-hover-icon {\n  line-height: 128px;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon:before,\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon:after,\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon .icon-inner:before,\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon .icon-inner:after {\n  min-width: 100%;\n  min-height: 100%;\n  padding: inherit;\n  border-radius: inherit;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-on:before {\n  border-width: 2px;\n  border-style: solid;\n}\n.dt-icon-border-dashed.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-on:before {\n  border-style: dashed;\n}\n.dt-icon-border-dotted.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-on:before {\n  border-style: dotted;\n}\n.dt-icon-border-double.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-on:before {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-dashed.dt-icon-border-on:before {\n  border-style: dashed;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-dotted.dt-icon-border-on:before {\n  border-style: dotted;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-double.dt-icon-border-on:before {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-border-on:after {\n  border-width: 2px;\n  border-style: solid;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-dashed.dt-icon-hover-border-on:after {\n  border-style: dashed;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-dotted.dt-icon-hover-border-on:after {\n  border-style: dotted;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-border-double.dt-icon-hover-border-on:after {\n  border-style: double;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-on:hover {\n  font-size: 64px;\n}\n#page .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-on:hover .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-on:hover .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-on:hover .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-on:hover .soc-icon {\n  color: #fff;\n  background: none;\n}\n#page .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-on:not(:hover) .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-on:not(:hover) .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-on:not(:hover) .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-on:not(:hover) .soc-icon,\n#page .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-off .soc-font-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-off .soc-font-icon,\n#page .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-off .soc-icon,\n#phantom .icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .text-icon.dt-icon-hover-off .soc-icon {\n  color: #ffffff;\n  background: none;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224.layout-1 {\n  grid-template-columns: 128px minmax(0,1fr);\n  grid-column-gap: 60px;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224.layout-2 {\n  grid-template-columns: minmax(0,1fr) 128px;\n  grid-column-gap: 0px;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224.layout-2 .text-icon {\n  margin-left: 0;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224.layout-3 {\n  grid-template-columns: 128px minmax(0,1fr);\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224.layout-3 .dt-text-title {\n  margin-left: 60px;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .dt-text-title,\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .dt-text-title a {\n  color: #558398;\n  background: none;\n  font-weight: bold;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .dt-text-title {\n  margin-bottom: 10px;\n}\n.icon-with-text-shortcode.icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 .dt-text-desc {\n  margin-bottom: 30px;\n}<\/style><div class=\"icon-with-text-shortcode  icon-text-id-31dfb6f3d018f5d383f8709f73a9d224 layout-1\" ><span   class=\"text-icon dt-icon-bg-on dt-icon-hover-off\" ><span class=\"icon-inner\"><i class=\"dt-regular-icon soc-icon fas fa-industry\"><\/i><i class=\"dt-hover-icon soc-icon fas fa-industry\"><\/i><\/span><\/span><h3 class=\"dt-text-title\"  >Recovery concept:<\/h3><div class=\"dt-text-desc\">The ML methodologies implemented within the project based on the MoSes-Pro algorithms developed by ZeMA, supported by the assistance of an intelligent tutorial system, can be applied to various scenarios within production. Here, SMEs participating in the project can actively influence the decision as to which scenarios or which issues that are important or urgent for them should be considered.<\/p>\n<p>So far, the following application scenarios have been identified:<br \/>\n\u2022 Identify complex relationships in production<br \/>\n\u2022 Anomaly detection<br \/>\n\u2022 Sensor self-monitoring<br \/>\n\u2022 Predictive maintenance<br \/>\n\u2022 Prediction of product quality<\/p>\n<p>Contact person: Titian Schneider<br \/>\nProject management: Prof. Dr. Andreas Sch\u00fctze<br \/>\nDuration: 01.03.2019 \u2013 28.02.2021<\/div><\/div><\/div><\/div><\/div><\/div><div class=\"vc_row wpb_row vc_row-fluid wpb_animate_when_almost_visible wpb_slideInUp slideInUp\"><div class=\"wpb_column vc_column_container vc_col-sm-6\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><style type=\"text\/css\" data-type=\"the7_shortcodes-inline-css\">.shortcode-single-image-wrap.shortcode-single-image-571721de5504bfa48d4c6132f31da384.enable-bg-rollover .rollover i,\n.shortcode-single-image-wrap.shortcode-single-image-571721de5504bfa48d4c6132f31da384.enable-bg-rollover .rollover-video i {\n  background: -webkit-linear-gradient();\n  background: linear-gradient();\n}\n.shortcode-single-image-wrap.shortcode-single-image-571721de5504bfa48d4c6132f31da384 .rollover-icon {\n  font-size: 32px;\n  color: #ffffff;\n  min-width: 44px;\n  min-height: 44px;\n  line-height: 44px;\n  border-radius: 100px;\n  border-style: solid;\n  border-width: 0px;\n}\n.dt-icon-bg-on.shortcode-single-image-wrap.shortcode-single-image-571721de5504bfa48d4c6132f31da384 .rollover-icon {\n  background: rgba(255,255,255,0.3);\n  box-shadow: none;\n}<\/style><div class=\"shortcode-single-image-wrap shortcode-single-image-571721de5504bfa48d4c6132f31da384 alignnone  enable-bg-rollover dt-icon-bg-off\" style=\"margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; width:500px;\"><div class=\"shortcode-single-image\"><div class=\"fancy-media-wrap  layzr-bg\" style=\"\"><img decoding=\"async\" class=\"preload-me lazy-load aspect\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D&#39;http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg&#39;%20viewBox%3D&#39;0%200%20300%2085&#39;%2F%3E\" data-src=\"https:\/\/zema.de\/wp-content\/uploads\/2020\/04\/EFRE-300x86-1.jpg\" data-srcset=\"https:\/\/zema.de\/wp-content\/uploads\/2020\/04\/EFRE-300x86-1.jpg 300w\" loading=\"eager\" sizes=\"(max-width: 300px) 100vw, 300px\" width=\"300\" height=\"85\"  data-dt-location=\"https:\/\/zema.de\/en\/efre-300x86\/\" style=\"--ratio: 300 \/ 85;\" alt=\"\" \/><\/div><\/div><\/div><\/div><\/div><\/div><div class=\"wpb_column vc_column_container vc_col-sm-6\"><div class=\"vc_column-inner\"><div class=\"wpb_wrapper\"><style type=\"text\/css\" data-type=\"the7_shortcodes-inline-css\">.shortcode-single-image-wrap.shortcode-single-image-2120b55ed4d43de51859e9276fb0d201.enable-bg-rollover .rollover i,\n.shortcode-single-image-wrap.shortcode-single-image-2120b55ed4d43de51859e9276fb0d201.enable-bg-rollover .rollover-video i {\n  background: -webkit-linear-gradient();\n  background: linear-gradient();\n}\n.shortcode-single-image-wrap.shortcode-single-image-2120b55ed4d43de51859e9276fb0d201 .rollover-icon {\n  font-size: 32px;\n  color: #ffffff;\n  min-width: 44px;\n  min-height: 44px;\n  line-height: 44px;\n  border-radius: 100px;\n  border-style: solid;\n  border-width: 0px;\n}\n.dt-icon-bg-on.shortcode-single-image-wrap.shortcode-single-image-2120b55ed4d43de51859e9276fb0d201 .rollover-icon {\n  background: rgba(255,255,255,0.3);\n  box-shadow: none;\n}<\/style><div class=\"shortcode-single-image-wrap shortcode-single-image-2120b55ed4d43de51859e9276fb0d201 alignnone  enable-bg-rollover dt-icon-bg-off\" style=\"margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; width:500px;\"><div class=\"shortcode-single-image\"><div class=\"fancy-media-wrap  layzr-bg\" style=\"\"><img decoding=\"async\" class=\"preload-me lazy-load aspect\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D&#39;http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg&#39;%20viewBox%3D&#39;0%200%20300%20120&#39;%2F%3E\" data-src=\"https:\/\/zema.de\/wp-content\/uploads\/2020\/07\/Saarland-300x121-1.jpg\" data-srcset=\"https:\/\/zema.de\/wp-content\/uploads\/2020\/07\/Saarland-300x121-1.jpg 300w\" loading=\"eager\" sizes=\"(max-width: 300px) 100vw, 300px\" width=\"300\" height=\"120\"  data-dt-location=\"https:\/\/zema.de\/en\/projekt\/auto-ibn%c2%b2\/saarland-300x121-1\/\" style=\"--ratio: 300 \/ 120;\" alt=\"\" \/><\/div><\/div><\/div><\/div><\/div><\/div><\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>EaSy ML \u2013 Assistance Evaluation System for Machine LearningProblemsCost-optimised production combined with high process and product quality is a key promise of Industry 4.0 and the associated digitalisation. There are numerous examples of how machine learning (ML) techniques help to analyze data, gain new insights into production, and optimize production.<\/p>","protected":false},"author":14,"featured_media":16537,"comment_status":"closed","ping_status":"closed","template":"","dt_portfolio_category":[42],"dt_portfolio_tags":[],"class_list":["post-16533","dt_portfolio","type-dt_portfolio","status-publish","has-post-thumbnail","hentry","dt_portfolio_category-multimodal-smart-sensing","dt_portfolio_category-42","description-off"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Das Projekt EaSy ML am Forschungszentrum - ZeMA gGmbH Saarbr\u00fccken<\/title>\n<meta name=\"description\" content=\"Hohe Kosten f\u00fcr die Produktionsoptimierung mittels maschinellem Lernen f\u00fcr KMU signifikant reduzieren mit dem Projekt EaSy ML \u25b6 Erfahren Sie mehr!\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/zema.de\/en\/projekt\/easy-ml\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Das Projekt EaSy ML am Forschungszentrum - ZeMA gGmbH Saarbr\u00fccken\" \/>\n<meta property=\"og:description\" content=\"Hohe Kosten f\u00fcr die Produktionsoptimierung mittels maschinellem Lernen f\u00fcr KMU signifikant reduzieren mit dem Projekt EaSy ML \u25b6 Erfahren Sie mehr!\" \/>\n<meta property=\"og:url\" content=\"https:\/\/zema.de\/en\/projekt\/easy-ml\/\" \/>\n<meta property=\"og:site_name\" content=\"fl.zema.de\" \/>\n<meta property=\"article:modified_time\" content=\"2020-07-22T10:12:56+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/zema.de\/wp-content\/uploads\/2020\/07\/ZeMA-16-scaled.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1503\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Estimated reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/zema.de\\\/projekt\\\/easy-ml\\\/\",\"url\":\"https:\\\/\\\/zema.de\\\/projekt\\\/easy-ml\\\/\",\"name\":\"Das Projekt EaSy ML am Forschungszentrum - ZeMA gGmbH Saarbr\u00fccken\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/zema.de\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/zema.de\\\/projekt\\\/easy-ml\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/zema.de\\\/projekt\\\/easy-ml\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/zema.de\\\/wp-content\\\/uploads\\\/2020\\\/07\\\/ZeMA-16-scaled.jpg\",\"datePublished\":\"2020-07-22T06:00:05+00:00\",\"dateModified\":\"2020-07-22T10:12:56+00:00\",\"description\":\"Hohe Kosten f\u00fcr die Produktionsoptimierung mittels maschinellem Lernen f\u00fcr KMU signifikant reduzieren mit dem Projekt EaSy ML \u25b6 Erfahren Sie mehr!\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/zema.de\\\/projekt\\\/easy-ml\\\/#breadcrumb\"},\"inLanguage\":\"en-GB\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/zema.de\\\/projekt\\\/easy-ml\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-GB\",\"@id\":\"https:\\\/\\\/zema.de\\\/projekt\\\/easy-ml\\\/#primaryimage\",\"url\":\"https:\\\/\\\/zema.de\\\/wp-content\\\/uploads\\\/2020\\\/07\\\/ZeMA-16-scaled.jpg\",\"contentUrl\":\"https:\\\/\\\/zema.de\\\/wp-content\\\/uploads\\\/2020\\\/07\\\/ZeMA-16-scaled.jpg\",\"width\":2560,\"height\":1503},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/zema.de\\\/projekt\\\/easy-ml\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Startseite\",\"item\":\"https:\\\/\\\/zema.de\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Portfolio\",\"item\":\"https:\\\/\\\/zema.de\\\/projekt\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"EaSy ML\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/zema.de\\\/#website\",\"url\":\"https:\\\/\\\/zema.de\\\/\",\"name\":\"fl.zema.de\",\"description\":\"Zentrum f\u00fcr Mechatronik und Automatisierungstechnik\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/zema.de\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-GB\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Das Projekt EaSy ML am Forschungszentrum - ZeMA gGmbH Saarbr\u00fccken","description":"Hohe Kosten f\u00fcr die Produktionsoptimierung mittels maschinellem Lernen f\u00fcr KMU signifikant reduzieren mit dem Projekt EaSy ML \u25b6 Erfahren Sie mehr!","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/zema.de\/en\/projekt\/easy-ml\/","og_locale":"en_GB","og_type":"article","og_title":"Das Projekt EaSy ML am Forschungszentrum - ZeMA gGmbH Saarbr\u00fccken","og_description":"Hohe Kosten f\u00fcr die Produktionsoptimierung mittels maschinellem Lernen f\u00fcr KMU signifikant reduzieren mit dem Projekt EaSy ML \u25b6 Erfahren Sie mehr!","og_url":"https:\/\/zema.de\/en\/projekt\/easy-ml\/","og_site_name":"fl.zema.de","article_modified_time":"2020-07-22T10:12:56+00:00","og_image":[{"width":2560,"height":1503,"url":"https:\/\/zema.de\/wp-content\/uploads\/2020\/07\/ZeMA-16-scaled.jpg","type":"image\/jpeg"}],"twitter_card":"summary_large_image","twitter_misc":{"Estimated reading time":"4 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/zema.de\/projekt\/easy-ml\/","url":"https:\/\/zema.de\/projekt\/easy-ml\/","name":"Das Projekt EaSy ML am Forschungszentrum - ZeMA gGmbH Saarbr\u00fccken","isPartOf":{"@id":"https:\/\/zema.de\/#website"},"primaryImageOfPage":{"@id":"https:\/\/zema.de\/projekt\/easy-ml\/#primaryimage"},"image":{"@id":"https:\/\/zema.de\/projekt\/easy-ml\/#primaryimage"},"thumbnailUrl":"https:\/\/zema.de\/wp-content\/uploads\/2020\/07\/ZeMA-16-scaled.jpg","datePublished":"2020-07-22T06:00:05+00:00","dateModified":"2020-07-22T10:12:56+00:00","description":"Hohe Kosten f\u00fcr die Produktionsoptimierung mittels maschinellem Lernen f\u00fcr KMU signifikant reduzieren mit dem Projekt EaSy ML \u25b6 Erfahren Sie mehr!","breadcrumb":{"@id":"https:\/\/zema.de\/projekt\/easy-ml\/#breadcrumb"},"inLanguage":"en-GB","potentialAction":[{"@type":"ReadAction","target":["https:\/\/zema.de\/projekt\/easy-ml\/"]}]},{"@type":"ImageObject","inLanguage":"en-GB","@id":"https:\/\/zema.de\/projekt\/easy-ml\/#primaryimage","url":"https:\/\/zema.de\/wp-content\/uploads\/2020\/07\/ZeMA-16-scaled.jpg","contentUrl":"https:\/\/zema.de\/wp-content\/uploads\/2020\/07\/ZeMA-16-scaled.jpg","width":2560,"height":1503},{"@type":"BreadcrumbList","@id":"https:\/\/zema.de\/projekt\/easy-ml\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Startseite","item":"https:\/\/zema.de\/"},{"@type":"ListItem","position":2,"name":"Portfolio","item":"https:\/\/zema.de\/projekt\/"},{"@type":"ListItem","position":3,"name":"EaSy ML"}]},{"@type":"WebSite","@id":"https:\/\/zema.de\/#website","url":"https:\/\/zema.de\/","name":"fl.zema.de","description":"Zentrum f\u00fcr Mechatronik und Automatisierungstechnik","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/zema.de\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-GB"}]}},"_links":{"self":[{"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/dt_portfolio\/16533","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/dt_portfolio"}],"about":[{"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/types\/dt_portfolio"}],"author":[{"embeddable":true,"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/comments?post=16533"}],"version-history":[{"count":5,"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/dt_portfolio\/16533\/revisions"}],"predecessor-version":[{"id":16649,"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/dt_portfolio\/16533\/revisions\/16649"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/media\/16537"}],"wp:attachment":[{"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/media?parent=16533"}],"wp:term":[{"taxonomy":"dt_portfolio_category","embeddable":true,"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/dt_portfolio_category?post=16533"},{"taxonomy":"dt_portfolio_tags","embeddable":true,"href":"https:\/\/zema.de\/en\/wp-json\/wp\/v2\/dt_portfolio_tags?post=16533"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}