{"id":272,"date":"2019-01-07T07:55:20","date_gmt":"2019-01-07T15:55:20","guid":{"rendered":"https:\/\/blogs.plm.automation.siemens.com\/t5\/Digital-Transformations\/Condition-based-maintenance-the-crystal-ball-you-need\/ba-p\/554974"},"modified":"2026-03-26T11:56:37","modified_gmt":"2026-03-26T15:56:37","slug":"condition-based-maintenance-the-crystal-ball-you-need","status":"publish","type":"post","link":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/condition-based-maintenance-the-crystal-ball-you-need\/","title":{"rendered":"Condition-based maintenance: the crystal ball you need"},"content":{"rendered":"<p><P>Gazing into a crystal ball to know the future has a long, storied past that dates before the Middle Ages.<\/P><br \/>\n<P><BR \/>Today, condition-based maintenance, or maintenance performed on industrial assets only when needed, is taking the guesswork out of global manufacturers\u2019 maintenance, repair and operations strategies by helping eliminate downtime before it occurs.<\/P><\/p>\n<p><P>That\u2019s good news for manufacturers as more than 80 percent report they are <a href=\"https:\/\/bin95.com\/news\/Whats_True_Downtime_Cost.htm\" target=\"_blank\" rel=\"noopener nofollow noreferrer\">unable to calculate their true downtime costs correctly<\/A>, driving an estimated $20 billion in losses annually.<\/P><\/p>\n<p><P>Condition-based maintenance (CBM) technology uses real-time data to prioritize and optimize maintenance resources. It\u2019s part of the growing <a href=\"https:\/\/community.plm.automation.siemens.com\/t5\/Digital-Transformations\/Industry-4-0-the-result-of-centuries-of-manufacturing-innovation\/ba-p\/354448\" target=\"_blank\" rel=\"noopener nofollow noreferrer\">Industry 4.0<\/A> trend in which cyber-physical systems, the Internet of Things (IoT), cloud computing and cognitive systems are connected to increase automation and data exchange in physical manufacturing assets.<\/P><br \/>\n<P><BR \/>Because the <a href=\"https:\/\/www.iofficecorp.com\/blog\/cost-of-iot-sensors\" target=\"_blank\" rel=\"noopener nofollow noreferrer\">cost of IoT sensors has steadily dropped<\/A> by more than two-thirds since 2004, from $1.30 to a forecast of 38 cents in 2020, CBM is poised to usher in a veritable maintenance, repair and overhaul (MRO) \u201crenaissance\u201d by optimizing the tradeoff between maintenance costs and performance.&nbsp;Still, to fully appreciate CBM\u2019s value, it\u2019s important to understand how MRO practices have evolved.<\/P><\/p>\n<p><H3>How condition-based maintenance can help you<\/H3><br \/>\n<P>MRO looks at the typical operational lifespan of an industrial asset such as an aircraft, ship or a power plant and aims to effectively maintain it over time and lower the asset\u2019s total cost of ownership (TCO).<\/P><br \/>\n<P><BR \/>Traditionally, maintenance has been performed on a scheduled or reactive basis with manual or paper-based processes. These often resulted in costly overages such as overstocking of spare parts or productivity loss associated with assets taken offline for repairs.<\/P><\/p>\n<p><P>As technology automation evolved, manufacturers adopting enterprise resource planning (ERP) systems tried to extend their systems\u2019 capabilities to address MRO processes such as materials planning and maintenance scheduling. But since ERP systems are designed to view assets through a piece-part financial lens and not TCO, costly customization and additional resources were required.<\/P><\/p>\n<p><P>By contrast, CBM overcomes these challenges by providing maintenance only when it\u2019s need araises. With the help of IoT sensors, the system constantly collects data on the operational status of assets and fed to machine-learning and data-analytics systems that predict maintenance requirements in real time.<\/P><br \/>\n<P><BR \/>Not only does this minimize downtime and lower TCO, but the same data helps manufacturers build better machines with longer lifespans. Procurement and productivity also benefit: companies reduce spare-parts inventories, and technicians are ready for repairs fully equipped with the information and parts they need to perform the operation successfully.<\/P><\/p>\n<p><P>This has already made CBM broadly accepted as the best practice for monitoring and preventing industrial equipment failure. According to numerous industry benchmarks, CBM can help cut maintenance costs by as much as 12 percent in the first year, and drastically improve machine availability by as much as 92 percent. CBM also helps to reduce unexpected failures by about 25 percent, and repair and overhaul time is almost trimmed in half.<\/P><br \/>\n<P><BR \/>Today, manufacturers don\u2019t need a crystal ball to predict the future of industrial MRO. The decreased cost of sensors is fueling a boom in Industrial IoT spending, with manufacturing companies estimated to spend <a href=\"https:\/\/www.ennomotive.com\/industrial-iot-sensor-prices\/\" target=\"_blank\" rel=\"noopener nofollow noreferrer\">$500 billion a year<\/A> on the technology. This will bring CBM mainstream, offering deeper performance insights, reduced costs and increased operational efficiency to manufacturers worldwide.<\/P><\/p>\n<p><P><span class=\"lia-inline-image-display-wrapper lia-image-align-center\" style=\"width: 400px;\"><img decoding=\"async\" src=\"http:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/19\/2019\/09\/Condition-based-maintenance-1.png\" alt=\"Condition-based maintenance.png\" title=\"Condition-based maintenance.png\" \/><\/span><\/P><\/p>\n<p><P><EM>This concludes part one of our series on condition-based maintenance. In part two, we discuss <a href=\"https:\/\/community.plm.automation.siemens.com\/t5\/Digital-Transformations\/Condition-based-maintenance-a-boost-against-the-competition\/ba-p\/562885\" target=\"_blank\" rel=\"noopener nofollow noreferrer\">how CBM gives industries a leg up on the competition<\/A>.&nbsp;<\/EM><\/P><\/p>\n<p><P><STRONG>About the author <\/STRONG><BR \/><STRONG>Senthil Kumar<\/STRONG><EM> is a digital enterprise business development consultant working in the Asia-Pacific presales and consulting group within Siemens PLM Software. He has been with Siemens for 18 years playing numerous roles within business consulting, presales and implementing PLM solutions. He has worked with several companies in the machinery, energy, automotive, aerospace and defense, and HTE industries across many countries.<\/EM><\/P><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Gazing into a crystal ball to know the future has a long, storied past that dates before the Middle Ages.<br \/>\n   Today, condition-based maintenance, or maintenance performed on industrial assets only wh&#8230;<\/p>\n","protected":false},"author":56793,"featured_media":276,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spanish_translation":"","french_translation":"","german_translation":"","italian_translation":"","polish_translation":"","japanese_translation":"","chinese_translation":"","footnotes":""},"categories":[1],"tags":[13],"industry":[],"product":[],"coauthors":[],"class_list":["post-272","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-industry-4-0"],"featured_image_url":"https:\/\/blogs.sw.siemens.com\/wp-content\/uploads\/sites\/19\/2019\/09\/Condition-based-maintenance-1.png","_links":{"self":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts\/272","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/users\/56793"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/comments?post=272"}],"version-history":[{"count":2,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts\/272\/revisions"}],"predecessor-version":[{"id":277,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/posts\/272\/revisions\/277"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/media\/276"}],"wp:attachment":[{"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/media?parent=272"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/categories?post=272"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/tags?post=272"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/industry?post=272"},{"taxonomy":"product","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/product?post=272"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/blogs.sw.siemens.com\/thought-leadership\/wp-json\/wp\/v2\/coauthors?post=272"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}