{"id":11418,"date":"2021-05-19T12:02:42","date_gmt":"2021-05-19T12:02:42","guid":{"rendered":"https:\/\/cryptounplugged.ai\/blog\/?p=11418"},"modified":"2021-05-19T12:02:47","modified_gmt":"2021-05-19T12:02:47","slug":"aspentech-expands-application-of-industrial-ai-to-achieve-new-profitability-and-sustainability-goals","status":"publish","type":"post","link":"https:\/\/cryptounplugged.ai\/blog\/aspentech-expands-application-of-industrial-ai-to-achieve-new-profitability-and-sustainability-goals\/","title":{"rendered":"AspenTech Expands Application Of Industrial AI To Achieve New Profitability And Sustainability Goals"},"content":{"rendered":"\n<p><a href=\"http:\/\/www.aspentech.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">Aspen Technology, Inc.<\/a>\u00a0(NASDAQ:AZPN), a global leader in asset optimization software, today announced that it has extended Industrial AI across its leading solutions to drive higher levels of profitability and sustainability in customer\u2019 operations. In addition, the AIoT workbench will enable data scientists to collaborate with domain experts to develop AI apps based on enterprise-wide data.<\/p>\n\n\n\n<p>With First Principles Driven Hybrid Models, AI is directly embedded into Aspen HYSYS and Aspen Plus process simulations, enabling engineers to\u00a0easily\u00a0build operations-ready models calibrated with\u00a0relevant plant data.\u00a0 Reduced Order Hybrid models\u00a0can be shared across engineering, planning and dynamic optimization solutions to improve the accuracy and predictability of these applications. Deep Learning APC can deliver\u00a0more accurate and sustainable models\u00a0that cover a\u00a0broad\u00a0range\u00a0of operating conditions.\u00a0Together, these advanced capabilities deliver the next generation of operational excellence. According to Peter Reynolds, Principal Analyst with ARC Advisory Group, \u201cThe use of First Principles Models acting as guardrails for the use of AI in industrial markets is key for success.\u201d<\/p>\n\n\n\n<p>\u201cUsing the hybrid model, we were able to create a model that can reproduce real plant data more accurately than the conventional reformer model. We were able to create a highly accurate model in a short period of time,\u201d commented Mr. Takuto Nakai, Production Department, Nissan Chemical Corporation.<\/p>\n\n\n\n<p>Also new to this latest version of aspenONE V12.1 are new models that will enable customers to optimize biomass processing, hydrogen production, carbon capture, and carbon emissions more accurately and systematically, focused on reducing environmental impact. In addition, new analysis and visualization capabilities can help to reduce measurable waste and energy use, throughout the process from lab to production.<\/p>\n\n\n\n<p>AI-driven 3D conceptual layouts with the introduction of Aspen OptiPlant and Aspen OptiRouter are now integrated into the AspenTech portfolio.\u00a0 For industries such as pharmaceuticals with pressure for a faster time to market, Aspen Unscrambler, Aspen Unscrambler HSI and Aspen Process Pulse ensures product and process quality by solving complex problems using multivariate analysis to drive more profitable processes, less deviation and higher yield.\u00a0<\/p>\n\n\n\n<p>According to Janice Abel, Principal Analyst with ARC Advisory Group,\u00a0\u201cThe deep domain expertise embedded into the AspenTech V12.1 products and its focus on embedding Industrial AI from design through the entire supply chain offers a powerful solution that will help unlock the untapped business value in industrial data.\u201d<\/p>\n\n\n\n<p>\u201cWe continue to add Industrial AI across our portfolio of solutions to automate greater efficiency across engineering, operations and maintenance, to progress the vision of the Self Optimizing Plant,\u201d commented David Arbeitel, senior vice president of product management at Aspen Technology. \u201cThe AI workbench solution enables operations and data scientists to better collaborate for business-specific needs. The combination of industry specific application knowledge and asset optimization expertise gives AspenTech customers the assurance that their AI initiatives will yield safe, reliable and efficient operations.\u201d<\/p>\n\n\n\n<p>The aspenONE V12.1 release further improves margins, improves asset uptime and reliability, and maximizes utilization of assets with AspenTech\u2019s end-to-end solutions.\u00a0 Companies can accelerate their digitalization journey and leverage Industrial AI to make progress toward the Self-Optimizing Plant while increasing margins, achieving sustainability and reliable, safe operations, and reducing capital cost and time in bringing assets online.\u00a0<\/p>\n\n\n\n<p><strong>New Features of aspenONE\u00ae V12.1 software include:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>Aspen HYSYS\u00ae and Aspen Plus\u00ae:<\/strong>\u00a0Embedded machine learning to easily calibrate models ready to be deployed in operations; Models tuned to reality with improved time-to-value.<\/li><li><strong>Aspen Deep Learning for DMC3\u2122:<\/strong>\u00a0combines linear and nonlinear (deep learning) control variables that are easy to update and augment with new data to generate more accurate and sustainable models to run closer to optimum level across entire lifecycle.<\/li><li><strong>Aspen OptiPlant\u2122 and OptiRouter\u2122:<\/strong>\u00a0Automatically generate 3D layouts for design, with AI-driven optimum pipeline routing, and broader visibility increasing collaboration for reduced costs, errors, variances and faster concept selection.<\/li><li><strong>Aspen Unscrambler\u2122 and Aspen Process Plus\u2122:\u00a0<\/strong>Accelerate product development and ensure product quality, while maintaining regulatory compliance with Aspen Unscrambler and Aspen Process Pulse. Each provides pharmaceutical companies with full process understanding and control of data from product development to production for more profitable processes, less deviations, reduced cycle times, and higher yields.<\/li><li><strong>Reduced Order Hybrid Models for Aspen Unified PIMS\u2122 and GDOT\u2122:\u00a0<\/strong>Automate workflow for maintaining planning model accuracy and enable optimization of complex process units in closed loop\u00a0with reduced\u00a0order models that provide a consistent workflow spanning process engineering, data science, planning and APC.<\/li><li><strong>Aspen Mtell<\/strong>\u2122: Enables data scientists to collaborate with domain experts with integration\u00a0with Aspen AIoT Hub. In addition, Aspen Mtell native OPC UA support enables broader coverage and easier connections across enterprise deployments.<\/li><li><strong>Aspen Industrial AI Workbench\u2122:\u00a0<\/strong>Enable domain experts with data analytics with a no-code Visual Query Builder and gain fast-time to insights with out-of-the-box Analytics libraries. Empower citizen data scientists with Advanced Analytics libraries such as Anomaly Detection and Scoring and seamlessly share insights through configurable dashboards and application enablement.<\/li><\/ul>\n\n\n\n<p>To learn more, visit our\u00a0<a href=\"https:\/\/www.aspentech.com\/en\/whats-new\" target=\"_blank\" rel=\"noreferrer noopener\">website<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Aspen Technology, Inc.\u00a0(NASDAQ:AZPN), a global leader in asset optimization software, today announced that it has extended Industrial AI across its leading solutions to drive higher levels of profitability and sustainability in customer\u2019 operations. In addition, the AIoT workbench will enable data scientists to collaborate with domain experts to develop AI apps based on enterprise-wide data. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":11420,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_seopress_robots_primary_cat":"none","_seopress_titles_title":"","_seopress_titles_desc":"","_seopress_robots_index":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-11418","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"rttpg_featured_image_url":{"full":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo.png",311,162,false],"landscape":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo.png",311,162,false],"portraits":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo.png",311,162,false],"thumbnail":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo-150x150.png",150,150,true],"medium":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo-300x156.png",300,156,true],"large":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo.png",311,162,false],"1536x1536":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo.png",311,162,false],"2048x2048":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo.png",311,162,false],"post-thumbnail":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo.png",311,162,false],"graptor-sq-xs":["https:\/\/cryptounplugged.ai\/blog\/wp-content\/uploads\/2021\/05\/Aspentech-Logo.png",100,52,false]},"rttpg_author":{"display_name":"admin","author_link":"https:\/\/cryptounplugged.ai\/blog\/author\/admin\/"},"rttpg_comment":0,"rttpg_category":"<a href=\"https:\/\/cryptounplugged.ai\/blog\/category\/uncategorized\/\" rel=\"category tag\">Uncategorized<\/a>","rttpg_excerpt":"Aspen Technology, Inc.\u00a0(NASDAQ:AZPN), a global leader in asset optimization software, today announced that it has extended Industrial AI across its leading solutions to drive higher levels of profitability and sustainability in customer\u2019 operations. In addition, the AIoT workbench will enable data scientists to collaborate with domain experts to develop AI apps based on enterprise-wide data.&hellip;","_links":{"self":[{"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/posts\/11418","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/comments?post=11418"}],"version-history":[{"count":1,"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/posts\/11418\/revisions"}],"predecessor-version":[{"id":11421,"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/posts\/11418\/revisions\/11421"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/media\/11420"}],"wp:attachment":[{"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/media?parent=11418"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/categories?post=11418"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cryptounplugged.ai\/blog\/wp-json\/wp\/v2\/tags?post=11418"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}