{"id":1166,"date":"2026-07-30T12:52:02","date_gmt":"2026-07-30T12:52:02","guid":{"rendered":"https:\/\/hub10.eks-intec.de\/?post_type=research_project&#038;p=1166"},"modified":"2026-07-30T13:00:45","modified_gmt":"2026-07-30T13:00:45","slug":"bap","status":"publish","type":"research_project","link":"https:\/\/eks-intec.com\/de\/research-projects\/bap\/","title":{"rendered":"BAP"},"content":{"rendered":"<p class=\"wp-block-paragraph\">Banana Process Optimization<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The industry is facing a growing number of challenges: shorter planning and commissioning times, market fluctuations, supply chain problems, an ever-increasing number of product variants, rising competitive cost pressure, new technologies or high complexity due to new\/little-known products. Two current examples are the mass production of electrolysers and high-voltage batteries, where complex and little-known processes and expensive elements are used. However, the omnipresent issue of sustainability in everyday life also drives industry and science. This is another dimension in the complex web of requirements, target values and possibilities in highly automated complex production systems. Plant planners can therefore hardly specify production processes completely and without errors now or in the future. These so-called banana processes therefore enter the start-up and operation phase immature and must continue to mature there. Information from virtual commissioning should continue to be used as the basis for this. The dynamic digital twin of the plant, which is created during virtual commissioning, becomes a digital shadow during the start-up phase and during operation. The information collected in this way from the engineering and production process is to be processed and overlaid with further information in order to carry out smart analyses for the optimization of the electrolyser production facilities with regard to sustainability criteria. The data is to be presented visually in order to support and facilitate analytical conclusions through interactive visual interfaces. The combined information (plant topology, time series data, CO2 footprint) will be exported based on standards (e.g. AutomationML and Asset Administration Shell) to make it usable for other approaches and methods.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The research and development project BAP is funded by the German Federal Ministry of Education and Research under the funding code 03SF0761.<\/p>","protected":false},"excerpt":{"rendered":"<p>Banana Process Optimization The industry is facing a growing number of challenges: shorter planning and commissioning times, market fluctuations, supply chain problems, an ever-increasing number of product variants, rising competitive cost pressure, new technologies or high complexity due to new\/little-known products. Two current examples are the mass production of electrolysers and high-voltage batteries, where complex [&hellip;]<\/p>\n","protected":false},"featured_media":1145,"menu_order":0,"template":"","research_project_category":[42],"class_list":["post-1166","research_project","type-research_project","status-publish","has-post-thumbnail","hentry","research_project_category-completed"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.6 (Yoast SEO v28.6) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>BAP - EKS InTec GmbH<\/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:\/\/eks-intec.com\/de\/research-projects\/bap\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"BAP\" \/>\n<meta property=\"og:description\" content=\"Banana Process Optimization The industry is facing a growing number of challenges: shorter planning and commissioning times, market fluctuations, supply chain problems, an ever-increasing number of product variants, rising competitive cost pressure, new technologies or high complexity due to new\/little-known products. 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