{"id":29606,"date":"2025-06-27T09:30:00","date_gmt":"2025-06-27T08:30:00","guid":{"rendered":"https:\/\/www.engineernewsnetwork.com\/blog\/?p=29606"},"modified":"2025-06-25T10:42:09","modified_gmt":"2025-06-25T09:42:09","slug":"predictive-maintenance-using-iiot-data-in-manufacturing","status":"publish","type":"post","link":"https:\/\/www.engineernewsnetwork.com\/blog\/predictive-maintenance-using-iiot-data-in-manufacturing\/","title":{"rendered":"Predictive maintenance using IIoT data in manufacturing"},"content":{"rendered":"\n<p><strong>Predictive maintenance and virtual twins are no longer future aspirations. They are necessities for manufacturers who want to stay competitive. Louis Columbus reports<\/strong><\/p>\n\n\n\n<p>Manufacturing is entering a transformative era where technology-driven solutions are redefining how factories operate. Efficiency is no longer about merely maintaining production quotas \u2014 it is about predictive insight, sustainability, and operational resilience. Predictive maintenance technologies, powered by the Industrial Internet of Things (IIoT), is a cornerstone of this transformation. It turns real-time data into actionable strategies that keep machines running efficiently and sustainably.<\/p>\n\n\n\n<p>At the heart of this shift lies&nbsp;<a href=\"https:\/\/www.3ds.com\/virtual-twin\"><strong>virtual twins<\/strong><\/a>; these dynamic digital replicas bridge the gap between the physical and virtual worlds, enabling manufacturers to simulate, optimize, and refine their operations like never before.<\/p>\n\n\n\n<p><strong>Understanding MOM and MES<\/strong><\/p>\n\n\n\n<p><a href=\"https:\/\/www.3ds.com\/products\/delmia\/manufacturing-operations\/manufacturing-operations-management\"><strong>Manufacturing Operations Management (MOM) software<\/strong><\/a>\u00a0encompasses a broad range of activities that support production, including quality management, logistics, materials management,\u00a0time and labor management, and maintenance. MES is a key component of a MOM strategy.<\/p>\n\n\n\n<p>MOM and\u00a0<a href=\"https:\/\/www.3ds.com\/products\/delmia\/manufacturing-operations\/manufacturing-execution-system\"><strong>Manufacturing Execution Systems (MES) softwar<\/strong>e<\/a>\u00a0are critical to modern manufacturing but serve distinct roles. MES operates on the shop floor, directing labor and materials, collecting real-time data, and ensuring production efficiency. MOM, however, takes a broader view, integrating MES with functions like quality, logistics, and maintenance, driving enterprise-wide optimization.<\/p>\n\n\n\n<p>Think of MES as the tactical arm, handling immediate production needs, while MOM provides strategic oversight, leveraging MES data to streamline the entire manufacturing lifecycle. Together, they deliver a unified approach, balancing shop-floor precision with enterprise-level coordination to enhance efficiency, compliance, and overall performance.<\/p>\n\n\n\n<p><strong>The future of maintenance with virtual twins<\/strong><\/p>\n\n\n\n<p>Virtual twins take the concept of digital twins \u2013 which provide virtual models of physical assets and processes \u2013 to the next level by ensuring they are model-based, dynamic, connected, reusable in multiple contexts, and by adding a 4<sup>th<\/sup>\u00a0dimension \u2013 time. The best-in-class virtual twins are capable of integrating with\u00a0MOM software, enabling real-time feedback between the virtual and real worlds and allowing manufacturers to visualize, predict, and optimize their operations in unparalleled ways.<\/p>\n\n\n\n<p><strong>Key benefits of virtual twins:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Real-Time Monitoring:<\/strong>\u00a0Virtual twins provide a continuous, live view of equipment performance, ensuring that any anomalies or inefficiencies are immediately flagged.<\/li>\n\n\n\n<li><strong>Predictive Analytics Integration:<\/strong>\u00a0By coupling virtual twins with predictive maintenance algorithms, manufacturers can pre-empt equipment failures and schedule maintenance activities efficiently.<\/li>\n\n\n\n<li><strong>Scenario Simulation:<\/strong>\u00a0Manufacturers can run \u2018what-if\u2019 scenarios to understand the impact of operational adjustments, new production schedules, or unexpected demand surges.<\/li>\n\n\n\n<li><strong>Sustainability Insights:<\/strong>\u00a0Optimise energy use with the help of virtual twins to reduce material waste, and align operations with sustainability targets.<\/li>\n\n\n\n<li><strong>Seamless Integration with MOM Systems:<\/strong>\u00a0Modern MOM platforms\u00a0integrates with virtual twins directly into broader manufacturing workflows, creating a closed-loop system that continuously improves processes based on real-time data.<\/li>\n<\/ul>\n\n\n\n<p><strong>Navigating challenges in implementation<\/strong><\/p>\n\n\n\n<p>Despite the transformative potential of predictive maintenance, manufacturers often face hurdles when adopting IIoT-enabled solutions. Key challenges include:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Data Overload and Management:\u00a0<\/strong>IIoT generates massive amounts of data, often overwhelming traditional systems. The solution lies in edge computing, which processes data locally, reducing latency and ensuring real-time insights. Additionally, scalable data platforms such as MOM aggregate and contextualise this data, turning it into actionable intelligence.<\/li>\n\n\n\n<li><strong>Integration Complexities:<\/strong>\u00a0Many manufacturers operate legacy systems that don\u2019t easily integrate with modern IIoT technologies. MOM bridges this gap by creating a unified architecture that connects operational technology (OT) with IT systems, ensuring seamless data flow across the enterprise.<\/li>\n\n\n\n<li><strong>Skills Shortages:<\/strong>\u00a0The shift to predictive maintenance requires both IT and OT expertise, which many manufacturers lack. Cross-functional training programs and targeted recruitment efforts can help bridge this gap. Tools also support this transition by providing intuitive tools and platforms that simplify adoption.<\/li>\n\n\n\n<li><strong>Cybersecurity Risks:<\/strong>\u00a0As IIoT expands, so do potential vulnerabilities. Manufacturers must implement robust security protocols, including encryption, regular audits, and compliance with industry standards to safeguard their systems.<\/li>\n<\/ol>\n\n\n\n<p><strong>Sustainability at the core of predictive maintenance<\/strong><\/p>\n\n\n\n<p>Predictive maintenance contributes to sustainability by reducing waste, optimizing resource use, and minimizing energy consumption. MOM solutions integrate sustainability metrics into core operations, enabling manufacturers to track, measure, and improve their environmental performance.<\/p>\n\n\n\n<p><strong>Enhanced sustainability practices:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Energy Optimisation:<\/strong>\u00a0Real-time monitoring and predictive insights reduce unnecessary energy usage by aligning production schedules with energy-efficient practices.<\/li>\n\n\n\n<li><strong>Waste Reduction:<\/strong>\u00a0Predictive algorithms identify inefficiencies, enabling manufacturers to reduce scrap and recycle materials effectively.<\/li>\n\n\n\n<li><strong>Circular Economy Support:<\/strong>\u00a0MOM supports closed-loop systems, allowing manufacturers to reuse materials and minimize landfill contributions.<\/li>\n\n\n\n<li><strong>Lifecycle Assessments:<\/strong>\u00a0Simulate environmental impacts with virtual twins across a product\u2019s lifecycle, enabling manufacturers to make informed decisions about design and production.<\/li>\n\n\n\n<li><strong>Real-World Impact:<\/strong>\u00a0For example, manufacturers using MOM have reported up to a 25% reduction in their environmental footprint by leveraging IIoT for sustainability initiatives. These savings stem not only from operational efficiencies but also from smarter logistics and material sourcing strategies.<\/li>\n<\/ul>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><a href=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2025\/06\/LColumbus-1-scaled.jpg\"><img loading=\"lazy\" decoding=\"async\" width=\"683\" height=\"1024\" src=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2025\/06\/LColumbus-1-683x1024.jpg\" alt=\"\" class=\"wp-image-29608\" srcset=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2025\/06\/LColumbus-1-683x1024.jpg 683w, https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2025\/06\/LColumbus-1-200x300.jpg 200w, https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2025\/06\/LColumbus-1-768x1152.jpg 768w, https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2025\/06\/LColumbus-1-1024x1536.jpg 1024w, https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2025\/06\/LColumbus-1-1365x2048.jpg 1365w, https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2025\/06\/LColumbus-1-scaled.jpg 1707w\" sizes=\"auto, (max-width: 683px) 100vw, 683px\" \/><\/a><figcaption class=\"wp-element-caption\">Louis Columbus is Senior Industry Marketing Manager at DELMIA<\/figcaption><\/figure>\n<\/div>\n\n\n<p><strong>A vision for the future<\/strong><\/p>\n\n\n\n<p>Predictive maintenance and virtual twins are no longer future aspirations. They are necessities for manufacturers who want to stay competitive.&nbsp;Manufacturing and Operations solutions&nbsp;exemplify how these technologies can be harnessed to drive efficiency, resilience, and sustainability. By embracing these innovations, manufacturers can ensure their operations are not only prepared for today\u2019s challenges but also poised to lead in the smart factory revolution.<\/p>\n\n\n\n<p>Bottom line: the\u00a0<strong><a href=\"https:\/\/www.3ds.com\/factory-of-the-future\">factory of the future<\/a>\u00a0<\/strong>is not a concept; it is a reality taking shape today. With tools like predictive maintenance and virtual twins, the possibilities are limitless.<\/p>\n\n\n\n<p>Louis Columbus is Senior Industry Marketing Manager at <a href=\"https:\/\/www.3ds.com\/products\/delmia\"><strong>DELMIA<\/strong><\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Predictive maintenance and virtual twins are no longer future aspirations. They are necessities for manufacturers who want to stay competitive. Louis Columbus reports Manufacturing is entering a transformative era where technology-driven solutions are redefining how factories operate. Efficiency is no longer about merely maintaining production quotas \u2014 it is about predictive insight, sustainability, and operational &hellip;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[13123,7132,352],"class_list":["post-29606","post","type-post","status-publish","format-standard","","category-process","tag-delmia","tag-digital-twins","tag-predictive-maintenance"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Predictive maintenance using IIoT data in manufacturing - Engineer News Network<\/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:\/\/www.engineernewsnetwork.com\/blog\/predictive-maintenance-using-iiot-data-in-manufacturing\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Predictive maintenance using IIoT data in manufacturing - Engineer News Network\" \/>\n<meta property=\"og:description\" content=\"Predictive maintenance and virtual twins are no longer future aspirations. 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