{"id":2689,"date":"2024-06-10T11:59:13","date_gmt":"2024-06-10T11:59:13","guid":{"rendered":"https:\/\/bhaviklogistics.com\/happisigns\/product\/digital-twins-for-production-simulation\/"},"modified":"2024-08-12T05:00:23","modified_gmt":"2024-08-12T05:00:23","slug":"achieve-integrated-operations-and-real-time-oversight","status":"publish","type":"product","link":"https:\/\/networkscience.ai\/case-genie\/product\/achieve-integrated-operations-and-real-time-oversight\/","title":{"rendered":"Achieve Integrated Operations and Real-Time Oversight"},"content":{"rendered":"\n\n\n\n\n
Role<\/th>\nDeep Tech Used<\/th>\nIndustry<\/th>\nPotential Vector<\/th>\nPotential Vector Benefit<\/th>\n<\/tr>\n<\/thead>\n
CIO<\/p>\n

COO<\/td>\n

Digital Twins
\nArtificial Intelligence (AI)<\/td>\n		\u00a0Manufacturing<\/td>\nRisk<\/td>\n39%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Use Case Description <\/strong><\/h3>\n

Creating digital twins of production facilities involves replicating physical assets digitally to simulate and assess their operation and performance. This technology allows for real-time monitoring, predictive maintenance, and risk assessment, leading to optimised processes, reduced downtime, and improved manufacturing and industrial operations decision-making.<\/span><\/p>\n

 <\/p>\n

Case Study: Chemical Manufacturer Optimizes Production with Digital Twin Technology<\/span><\/b>\u00a0<\/span><\/h2>\n

 <\/p>\n

Challenges<\/span><\/b><\/h3>\n

A leading chemical manufacturer faced challenges with complex production processes and fragmented tools. Traditional approaches included:<\/span>\u00a0<\/span><\/p>\n

    \n
  • Disconnected Tools:<\/span><\/b> Process design, training simulation, hydraulics, and other aspects relied on separate, incompatible tools.<\/span>\u00a0<\/span><\/li>\n
  • Limited Problem-Solving:<\/span><\/b> Existing tools couldn’t handle the complexity of highly recycled flowsheets within the chemical production process.<\/span>\u00a0<\/span><\/li>\n
  • Inefficient Workflow:<\/span><\/b> Learning and using multiple tools throughout the production lifecycle hindered efficiency.<\/span>\u00a0<\/span><\/li>\n
  • Vendor Dependence:<\/span><\/b> Limited support and reliance on specific vendors created a disadvantageous relationship.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n

    Solution<\/span><\/b><\/h3>\n

    The chemical manufacturer implemented a digital twin technology solution for process simulation and risk assessment. This involved:<\/span>\u00a0<\/span><\/p>\n

      \n
    • Comprehensive Digital Twin:<\/span><\/b> A digital replica of the entire production facility, including machinery, processes, and material flow, was created.<\/span>\u00a0<\/span><\/li>\n
    • Real-Time Data Integration:<\/span><\/b> The digital twin is integrated with factory sensors and equipment, providing real-time production data.<\/span>\u00a0<\/span><\/li>\n
    • Unified Simulation Platform:<\/span><\/b> A single, user-friendly platform facilitates process design, training simulation, and performance monitoring within one environment.<\/span>\u00a0<\/span><\/li>\n
    • Advanced Modelling Capabilities:<\/span><\/b> The platform offered powerful tools to handle complex chemical processes with high recycling levels.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n

      Benefits\/Outcomes<\/span><\/b><\/h3>\n
        \n
      • Enhanced Problem-Solving:<\/span><\/b> The digital twin’s capabilities enabled tackling previously unsolvable issues, particularly in complex flowsheets with high recycling.<\/span>\u00a0<\/span><\/li>\n
      • Improved Efficiency:<\/span><\/b> A unified platform streamlined workflows by eliminating the need for multiple, disconnected tools.<\/span>\u00a0<\/span><\/li>\n
      • Reduced Vendor Dependence:<\/span><\/b> The chosen solution offered robust support and ongoing development, reducing reliance on specific vendors.<\/span>\u00a0<\/span><\/li>\n
      • Optimized Production Processes:<\/span><\/b> Simulation capabilities allowed process optimisation, increasing efficiency and reducing downtime.<\/span>\u00a0<\/span><\/li>\n
      • Improved Decision-Making:<\/span><\/b> Real-time data and risk assessment capabilities facilitated data-driven decision-making for improved production and operations.<\/span>\u00a0<\/span><\/li>\n
      • Collaboration:<\/span><\/b> A unified platform enabled better control and process engineers’ collaboration.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n

        Overall, digital twin technology empowered the chemical manufacturer to overcome challenges with complex processes and fragmented tools. The solution improved problem-solving capabilities, streamlined workflows, and fostered better collaboration by providing a comprehensive and unified platform. This led to optimised production processes, reduced downtime, and improved decision-making across the chemical manufacturing operations.<\/p>\n

        \u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

        Digital twins simulate production for better risk assessment, efficiency and maintenance.<\/p>\n","protected":false},"featured_media":6028,"template":"","meta":[],"etheme_brands":[],"product_cat":[46,45],"product_tag":[79],"class_list":{"0":"post-2689","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-cio-cto-cdo","7":"product_cat-coo","8":"product_tag-manufacturing","10":"first","11":"instock","12":"shipping-taxable","13":"product-type-simple"},"_links":{"self":[{"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/product\/2689","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/types\/product"}],"version-history":[{"count":13,"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/product\/2689\/revisions"}],"predecessor-version":[{"id":5905,"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/product\/2689\/revisions\/5905"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/media\/6028"}],"wp:attachment":[{"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/media?parent=2689"}],"wp:term":[{"taxonomy":"brand","embeddable":true,"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/etheme_brands?post=2689"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/product_cat?post=2689"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/networkscience.ai\/case-genie\/wp-json\/wp\/v2\/product_tag?post=2689"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}