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Maintenance with IoT: Real Gains for Manufacturing",{"rendered":430,"protected":431},"\n\u003Cp>In manufacturing today, operational efficiency and reliability are critical to maintaining competitiveness. Increasingly, manufacturers are adopting predictive maintenance to reduce unexpected downtime, maximize asset utilization, and improve Overall Equipment Effectiveness (OEE). This article examines how CBTW, in partnership with SAS Viya, uses AI-driven IoT analytics to make predictive maintenance an effective operational strategy. \u003C\u002Fp>\n\n\n\n\u003Cdiv class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-1 wp-block-group-is-layout-flex\">\u003Ch2 class=\"wp-block-heading\" id=\"h-predictive-strategies-to-overcome-manufacturing-maintenance-challenges\">Predictive Strategies to Overcome Manufacturing Maintenance Challenges\u003C\u002Fh2>\n\n\n\u003Cp>Manufacturing faces several complex challenges with \u003Ca href=\"https:\u002F\u002Fstaging.cbtw.tech\u002Finsights\u002Fpredictive-maintenance-solutions\">maintenance\u003C\u002Fa>. Machine data comes from diverse vendors and systems, often siloed and lacking real-time visibility. This leads to a reliance on reactive maintenance, which causes high costs due to unplanned downtime, lost productivity, and inefficient resource use. Decisions based on out-of-date or incomplete information restrict timely operational control. \u003C\u002Fp>\n\n\n\n\u003Cp>The maintenance approach has evolved through stages: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Reactive maintenance addresses failures only after they occur. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Preventive maintenance schedules tasks based on fixed intervals but can result in unnecessary actions or missed risks. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Predictive maintenance uses real-time data and AI to detect early warning signs and plan interventions accordingly. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>Moving from reactive to predictive maintenance is essential for faster and more informed decision-making and operational optimization in modern manufacturing environments. \u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\n\n\u003Cdiv class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-2 wp-block-group-is-layout-flex\">\u003Ch2 class=\"wp-block-heading\" id=\"h-how-cbtw-and-sas-viya-enable-predictive-maintenance-nbsp\">\u003Cstrong>How CBTW and SAS Viya Enable Predictive Maintenance\u003C\u002Fstrong> \u003C\u002Fh2>\n\n\n\u003Cp>CBTW supports manufacturers by integrating IoT sensor data and operational histories into a centralized and scalable platform, using technologies such as MongoDB. On top of this foundation, customized AI models are deployed to forecast equipment failures with accuracy. \u003C\u002Fp>\n\n\n\n\u003Cp>This approach includes: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>\u003Cstrong>Data consolidation:\u003C\u002Fstrong> All sensor and machine data are centrally collected and standardized to provide a single source of truth. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>\u003Cstrong>Continuous monitoring:\u003C\u002Fstrong> Real-time data streams are analyzed for anomalies and early alerts. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>\u003Cstrong>Cloud-native platform:\u003C\u002Fstrong> SAS Viya’s containerized microservices architecture enables scalable AI operations, allowing rapid deployment and efficient model governance. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>\u003Cstrong>Actionable insights:\u003C\u002Fstrong> Maintenance is scheduled based on model predictions, leading to optimal resource allocation. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>The business benefits from this approach include reduced unplanned downtime, lower emergency repair costs, extended machine lifespan, and enhanced OEE. \u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"683\" src=\"https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002Fview-male-engineer-work-engineers-day-celebration-1-1024x683.jpg\" alt=\"Predictive-lowcost\" class=\"wp-image-10422\" srcset=\"https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002Fview-male-engineer-work-engineers-day-celebration-1-1024x683.jpg 1024w, https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002Fview-male-engineer-work-engineers-day-celebration-1-800x533.jpg 800w, https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002Fview-male-engineer-work-engineers-day-celebration-1-100x67.jpg 100w, https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002Fview-male-engineer-work-engineers-day-celebration-1.jpg 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cdiv class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-3 wp-block-group-is-layout-flex\">\u003Ch2 class=\"wp-block-heading\" id=\"h-case-study-smart-production-minimum-viable-product-mvp-nbsp\">\u003Cstrong>Case Study: Smart Production Minimum Viable Product (MVP)\u003C\u002Fstrong> \u003C\u002Fh2>\n\n\n\u003Cp>A concrete example of this approach is CBTW’s Smart Production MVP, which addresses quality and maintenance challenges using AI and IoT data. Traditionally, high reject and rework rates have increased costs and lowered efficiency, as manual inspections and delayed defect detection hinder consistent quality. Reactive quality controls often miss early defects, leading to wasted materials and dissatisfied customers. \u003C\u002Fp>\n\n\n\n\u003Cp>The solution involved: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Integrating live data from Siemens PLC sensors into an Azure cloud environment. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Applying machine learning and time-series algorithms through SAS Viya and SAS Event Stream Processing. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Creating dashboards that give real-time visibility on production quality status to operational staff. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>Results were impressive, including a \u003Cstrong>30% reduction in product reject rates\u003C\u002Fstrong>, \u003Cstrong>improved machine efficiency\u003C\u002Fstrong>, \u003Cstrong>and empowered employees capable of performing independent data analysis\u003C\u002Fstrong>. The scalable framework was designed for use across multiple production lines and plants. \u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\n\n\u003Cdiv class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-4 wp-block-group-is-layout-flex\">\u003Ch2 class=\"wp-block-heading\" id=\"h-predictive-maintenance-as-a-strategic-business-lever-nbsp\">\u003Cstrong>Predictive Maintenance as a Strategic Business Lever\u003C\u002Fstrong> \u003C\u002Fh2>\n\n\n\u003Cp>For manufacturing leadership, predictive maintenance is more than adopting new technology. When supported by the right AI models and robust data architecture, it becomes an essential strategic tool. \u003C\u002Fp>\n\n\n\n\u003Cp>Key advantages include: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Enabling faster, data-driven decisions through integrated dashboards and AI-generated insights. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Fostering collaboration between production, maintenance, supply chain, and IT functions. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Providing a platform that scales and adapts to evolving business demands using SAS Viya’s cloud infrastructure. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>pporting broader digital transformation initiatives within the manufacturing facility. \u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Fdiv>\n\n\n\n\u003Cp>\u003C\u002Fp>\n\n\n\n\u003Cfigure class=\"wp-block-image size-large\">\u003Cimg loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"683\" src=\"https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002F2149595839-1-1024x683.jpg\" alt=\"Predictive-standard\" class=\"wp-image-10421\" srcset=\"https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002F2149595839-1-1024x683.jpg 1024w, https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002F2149595839-1-800x533.jpg 800w, https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002F2149595839-1-100x67.jpg 100w, https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002F2149595839-1.jpg 1200w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \u002F>\u003C\u002Ffigure>\n\n\n\n\u003Cdiv class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-5 wp-block-group-is-layout-flex\">\u003Ch2 class=\"wp-block-heading\" id=\"h-sas-viya-s-role-in-scalable-ai-for-manufacturing-nbsp\">\u003Cstrong>SAS Viya’s Role in Scalable AI for Manufacturing\u003C\u002Fstrong> \u003C\u002Fh2>\n\n\n\u003Cp>SAS Viya provides a unified, cloud-native platform that enables scalable, automated, and governed AI operations for manufacturing. Its containerized microservices architecture supports rapid deployment, continuous model monitoring, and automated retraining, ensuring sustained accuracy and transparency through explainable AI. Seamless integration with IoT devices and enterprise systems allows real-time data ingestion and analytics, driving predictive quality assurance and operational excellence. \u003C\u002Fp>\n\n\n\n\u003Cp>These capabilities empower manufacturers to make faster, data-driven decisions that enhance product quality, optimize operations, and realize the full value of predictive maintenance. By leveraging SAS Viya’s technology foundation, manufacturers can achieve sustainable operational improvements and maintain competitive agility in evolving markets. \u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\n\n\u003Cdiv class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-6 wp-block-group-is-layout-flex\">\u003Ch2 class=\"wp-block-heading\" id=\"h-considerations-for-implementation-nbsp\">\u003Cstrong>Considerations for Implementation\u003C\u002Fstrong> \u003C\u002Fh2>\n\n\n\u003Cp>Manufacturers seeking to implement predictive maintenance successfully should focus on: \u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Establishing effective data governance to ensure quality and accessibility of sensor and operational data. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Leveraging collaborative operating models that combine deep industry knowledge with advanced technology skills. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Providing comprehensive training and change management to support workforce adoption. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Driving continuous improvement by using predictive insights to optimize maintenance and production processes. \u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>CBTW’s managed services cover advisory, implementation, ongoing system management, and support, offering a comprehensive solution throughout the project lifecycle. \u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\n\n\u003Cdiv class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-7 wp-block-group-is-layout-flex\">\u003Ch2 class=\"wp-block-heading\" id=\"h-conclusion-nbsp\">\u003Cstrong>Conclusion\u003C\u002Fstrong> \u003C\u002Fh2>\n\n\n\u003Cp>Predictive maintenance powered by SAS Viya and CBTW’s AI and IoT expertise transforms manufacturing from reactive firefighting to proactive operational excellence. By integrating sensor data, developing accurate AI models, and leveraging scalable cloud platforms, manufacturers improve uptime, lower costs, extend machinery life, and enhance OEE. \u003C\u002Fp>\n\n\n\n\u003Cp>For operations leaders, supply chain professionals, CIOs, and other decision-makers, deploying predictive maintenance with a strong foundation in AI and data architecture is a practical way to drive operational efficiency and maintain a competitive edge in the evolving manufacturing landscape \u003C\u002Fp>\n\n\n\u003Ch3 class=\"wp-block-heading\" id=\"h-discover-how-cbtw-s-smart-production-solutions-can-transform-your-manufacturing-quality-and-efficiency-nbsp\">\u003Cstrong>Discover how CBTW’s Smart Production solutions can transform your manufacturing quality and efficiency.\u003C\u002Fstrong> \u003C\u002Fh3>\n\n\n\u003Cp>Contact our experts today to learn how AI-driven predictive quality and maintenance can reduce costs, minimize downtime, and enhance product consistency. Let’s innovate together to build a smarter, more resilient production line. \u003C\u002Fp>\n\u003C\u002Fdiv>\n\n\n\n\u003Cp>\u003C\u002Fp>\n",false,{"rendered":433,"protected":431},"\u003Cp>In manufacturing today, operational efficiency and reliability are critical to maintaining competitiveness. Increasingly, manufacturers are adopting predictive maintenance to reduce unexpected downtime, maximize asset utilization, and improve Overall Equipment Effectiveness (OEE). This article examines how CBTW, in partnership with SAS Viya, uses AI-driven IoT analytics to make predictive maintenance an effective operational strategy.  Predictive Strategies […]\u003C\u002Fp>\n",42,10423,"open","standard",{"_acf_changed":431,"content-type":8,"inline_featured_image":431,"footnotes":8},[440],46,[],[443],137,[445],129,[447,425,448,449,450,451,452,453,454,455],"post-10420","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-insights","cbtw_industries-manufacturing","cbtw_services-ai-data-platforms",{"authors":8,"article_authors":457,"direct_external_link":8,"post_region":462,"layout_builder":463},[458,461],{"author_name":459,"author_url":460},"Quang Luu","https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fquangluu\u002F",{"author_name":8,"author_url":8},"global",[464,471],{"acf_fc_layout":465,"tag_name":466,"section_title":467,"description":8,"image":431,"cta_link":468,"hubspot_form_id":470,"align_center":431},"block_lets_connect","Predictive Maintenance for Smarter Manufacturing","Drive Smarter Manufacturing with Predictive Maintenance and IoT Insights to Reduce Failures and Maximize Production Performance Now",{"title":469,"url":270,"target":8},"Book a Call","2b771724-6b01-4d7b-aeaa-591dfb86a794",{"acf_fc_layout":472,"title":195,"ui_v2":473,"short_description":474,"cbtw_related_group_filters":475,"items":431,"link":480,"hubspot_form_id":8,"mainPostId":420,"region":462},"block_insights",true,"Access related expert insights",{"cbtw_related_category_filter":476,"cbtw_related_tag_filter":477,"cbtw_related_industry_filter":478,"cbtw_related_service_filter":479},[197,221],[],[],[],{"title":481,"url":194,"target":8},"View all insights","\u003C!-- This site is optimized with the Yoast SEO Premium plugin v25.4 (Yoast SEO v25.4) - https:\u002F\u002Fyoast.com\u002Fwordpress\u002Fplugins\u002Fseo\u002F -->\n\u003Ctitle>Predictive Maintenance with IoT: Real Gains for Manufacturing - CBTW\u003C\u002Ftitle>\n\u003Cmeta name=\"description\" content=\"Cut downtime and costs with predictive maintenance. 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CBTW's Claude Code certification program for software engineering teams is one concrete answer: an external standard, set by Anthropic, applied across 320 developers in Europe.","2026-06-09","https:\u002F\u002Fstaging.cbtw.tech\u002Finsights\u002Fwhat-it-means-to-work-with-a-team-certified-by-anthropic","https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002FAILearningPath_Badge_Linkedin_ENG-1.png",{"medium":1001,"large":1002,"full":999},"https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002FAILearningPath_Badge_Linkedin_ENG-1-800x419.png","https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002FAILearningPath_Badge_Linkedin_ENG-1-1024x536.png",{"id":1004,"title":1005,"description":8,"excerpt":1006,"date":1008,"categories":220,"link":1009,"image":1010,"images":1011},15112,"GenAI RfP Processing: A Case Study with Human-in-the-Loop",{"rendered":1007},"This case study shows how we built a GenAI RfP processing solution on Azure that cut matching time by 3x while keeping human experts in control. The Challenge  A single RfP can include dozens of documents: specifications, drawings, forms and clarifications, all referencing each other, easily exceeding 100 pages. The information you need is scattered, and no two tenders are […]","2026-06-03","https:\u002F\u002Fstaging.cbtw.tech\u002Finsights\u002Fgenai-rfp-processing-a-case-study-with-human-in-the-loop","https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002Fgenai-rfp-processing-human-in-the-loop-1.jpg",{"medium":1012,"large":1013,"full":1010},"https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002Fgenai-rfp-processing-human-in-the-loop-1-640x800.jpg","https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002Fgenai-rfp-processing-human-in-the-loop-1-819x1024.jpg",{"id":1015,"title":1016,"description":8,"excerpt":1017,"date":1019,"categories":210,"link":1020,"image":1021,"images":1022},15073,"Fintech App Development in Singapore for Banks and Payment Providers",{"rendered":1018},"Singapore is one of the most demanding environments in the world to build financial software. The market is mature, institution-led, and unforgiving of poor digital experiences, especially when products serve banks, payment networks, fintech platforms, and financial services firms.  This is the context in which CBTW builds fintech apps in Singapore. Mobile app development in Singapore for […]","2026-06-02","https:\u002F\u002Fstaging.cbtw.tech\u002Finsights\u002Ffintech-app-development-in-singapore","https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002FThiet-ke-chua-co-ten-2.webp",{"medium":1023,"large":1024,"full":1021},"https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002FThiet-ke-chua-co-ten-2-800x533.webp","https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002FThiet-ke-chua-co-ten-2-1024x683.webp",[1026,1040,1042],{"region_name":1027,"social_list":1028},"Global",[1029,1033,1036],{"title":1030,"link":1031,"icon":1032},"Instagram","https:\u002F\u002Fwww.instagram.com\u002Fcollaborationbetterstheworld\u002F","https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002FinsAsset-1@2x.png",{"title":1034,"link":574,"icon":1035},"LinkedIn","https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002FlkAsset-2@2x.png",{"title":1037,"link":1038,"icon":1039},"Youtube","https:\u002F\u002Fwww.youtube.com\u002F@collaborationbetterstheworld","https:\u002F\u002Fstaging-admin.cbtw.tech\u002Fwp-content\u002Fuploads\u002FyoutubeAsset-3@2x.png",{"region_name":8,"social_list":1041},[],{"region_name":8,"social_list":1043},[],1786591995470]