{"id":19542,"date":"2016-11-18T17:11:21","date_gmt":"2016-11-18T22:11:21","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/"},"modified":"2016-11-18T17:11:21","modified_gmt":"2016-11-18T22:11:21","slug":"if-it-aint-broke-dont-fix-it-think-again","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/","title":{"rendered":"If It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026"},"content":{"rendered":"

If It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026<\/strong><\/span><\/p>\n

According to the World Economic Forum, the next 10 years will bring digital transformation to the industrial sector.[i]<\/a> One way that this will occur is through the power of predictive analytics to improve the maintenance and reliability of industrial equipment. According to ABI Research, the maintenance analytics market is growing with a CAGR of 22% and is expected to reach a market size of $24.7 billion by 2019.[ii]<\/a><\/p>\n

Traditionally, industrial maintenance is driven in two ways: reactive\/unplanned maintenance as a result of a breakdown, and preventative\/planned maintenance as a result of time-based factors.[iii]<\/a> Digital transformation offers a new mechanism of determining when to do preventative maintenance by assessing the conditions of the equipment in real-time with sensors rather than periodic checks by people, and then using predictive analytics to determine the expected failure points of the equipment and the optimal time to invest in maintenance. This transformation could improve asset performance, up-time, and reliability, while also lowering operating and maintenance costs.[iv]<\/a><\/p>\n

KONUX, a Munich-based start-up, has developed advanced sensor technology and a software platform to enable predictive maintenance in the industrial sector, including applications for railway infrastructure, industrial pumps, and pipeline monitoring.[v]<\/a> These monitoring and maintenance tasks have often involved dangerous conditions and challenging environments, as a result KONUX offers not only improvements to operations and maintenance but also fewer risks.[vi]<\/a><\/p>\n

KONUX has approached this problem by developing a holistic package, customized for each client, including sensors, analytics, and a user-friendly software interface. For example, KONUX developed a sensor system in conjunction with the German railway, Deutsche Bahn, to provide remote evaluation of their infrastructure. This is expected to reduce their maintenance costs by up to 25%.[vii]<\/a>\u00a0 Their collaborative approach working with key partners is a compelling choice that will facilitate their entry into this market, since in many cases the sensor technology needs to be integrated into existing infrastructure.\u00a0 Additionally, I think it was a good choice to make their first move in an industry that only has a few key players, such as railways.\u00a0 Track-ownership is typically nationalized or privatized with a small number of players, this offers KONUX broad reach once they have developed a partnership.\u00a0 For example, Deutsche Bahn operates in over 130 countries, and manages 1,054 million kilometers of railway.[viii]<\/a><\/p>\n

\"konux-anglesensor\"<\/a>\u00a0 \u00a0 \u00a0\u00a0\"konux-torque-sensor\"\u00a0 \u00a0 \u00a0\u00a0\"konux-positionsensor\"<\/a><\/p>\n

Although KONUX has been focused on an integrated solution, I believe that going forward they should focus on the hardware-side to further develop their competitive advantage of cutting-edge sensor technology, rather than diluting their efforts by also investing in advanced analytics and software.\u00a0 Many industrial giants, such as IBM, Siemens, and GE are investing heavily in analytics and software capabilities, as a result I believe KONUX\u2019s unique value lies in their sensor technology and ability to generate useful input data. For example, Siemens Mobility Data Services has also launched a one year pilot with Deutche Bahn to provide algorithms and a user-friendly interface to make better maintenance decisions. [ix]<\/a>\u00a0These larger players are integrating their solutions into the existing business processes and software tools used in industry, compared to KONUX’s stated-alone software.<\/p>\n

In addition to focusing on their sensor technology, I believe KONUX can take a two-pronged approach to developing future strategic partnerships. They can continue to\u00a0expand in consolidated industries such as railways to upgrade existing infrastructure. Additionally, I believe KONUX should work to build partnerships with equipment manufacturers.\u00a0 This will allow them to integrate their sensor technology into the next generation of industrial equipment. For example, Caterpillar\u2019s Innovation Lab is aiming to embed sensing technologies in their equipment to provide advanced maintenance solutions for their customers.[x]<\/a> However, to-date Caterpillar has invested in building an analytics platform through an investment in start-up Upstart which relies on existing data sources, rather than building out additional sensing technology.[xi]<\/a> As a result, the opportunity is open for organizations like KONUX to continue improving and integrating new sensors to provide the data necessary for predictive maintenance to be effective.<\/p>\n

Word Count:<\/strong><\/span>\u00a0651<\/p>\n

References:<\/strong><\/span><\/p>\n

[i]<\/a> World Economic Forum. Industrial Internet of Things: Unleashing the Potential of Connected Products and Service.<\/em> Accessed from: http:\/\/reports.weforum.org\/industrial-internet-of-things\/<\/a><\/p>\n

[ii]<\/a> ABI Research. Maintenance Analytics to Generate $24.7 Billion in 2019, Driven by Predictive Maintenance and the Internet of Things. <\/em>(Mar 28 2014). Accessed from: https:\/\/www.abiresearch.com\/press\/maintenance-analytics-to-generate-247-billion-in-2\/<\/a><\/p>\n

[iii]<\/a> Maintenance Assistant. Preventative vs Predictive Maintenance <\/em>(2013). Accessed from: https:\/\/www.maintenanceassistant.com\/blog\/short-guide-preventive-predictive-maintenance\/<\/a><\/p>\n

[iv]<\/a> US Department of Energy. Operations & Maintenance Best Practice Guide: Chapter 6. <\/em>http:\/\/energy.gov\/sites\/prod\/files\/2013\/10\/f4\/OM_6.pdf<\/a><\/p>\n

[v]<\/a> KONUX. Company History & Philosophy.<\/em> https:\/\/www.konux.com\/company\/<\/a><\/p>\n

[vi]<\/a> Gaskell, A. New Startup Aims to Bring Rail Maintenance to the 21st<\/sup> Century. <\/em>Forbes (April 27 2016). http:\/\/www.forbes.com\/sites\/adigaskell\/2016\/04\/27\/new-start-up-aims-to-bring-rail-maintenance-into-the-21st-century\/#37a9ddc21429<\/a><\/p>\n

[vii]<\/a> KONUX. Digitizing Railway. <\/em>Accessed from: https:\/\/www.konux.com\/applications\/sensors-digital-railway\/<\/a><\/p>\n

[viii]<\/a> Deutche Bahn. At a glance: Facts and Figures in 2015.<\/em> Accessed from: http:\/\/www.deutschebahn.com\/en\/group\/ataglance\/facts_figures.html<\/a><\/p>\n

[ix]<\/a> Briginshaw, D. ICE predictive maintenance trial launched. <\/em>International Railway Journal (Oct. 25 2016). Accessed from: http:\/\/www.railjournal.com\/index.php\/technology\/db-and-siemens-launch-predictive-maintenance-trial.html<\/a><\/p>\n

[x]<\/a> Construction Equipment. Three Questions with Gwenne Henricks, Chief Technology Officer, Caterpillar<\/em>. (Feb 20 2015). Accessed from: http:\/\/www.constructionequipment.com\/blog\/three-questions-gwenne-henricks-chief-technology-officer-caterpillar<\/a><\/p>\n

[xi]<\/a> Fortune. Caterpillar digs in to data analytics \u2013 investing in hot startup Uptake<\/em>. (Mar 15 2015). Accessed from: http:\/\/fortune.com\/2015\/03\/05\/caterpillar-digs-in-to-data-analytics-investing-in-hot-startup-uptake\/<\/a><\/p>\n

Images: Sourced from KONUX website – http:\/\/www.konux.com<\/p>\n","protected":false},"excerpt":{"rendered":"

The Power of Predictive Analytics to Improve Maintenance and Reliability in the Industrial Sector.<\/p>\n","protected":false},"author":2120,"featured_media":19543,"comment_status":"open","ping_status":"closed","template":"","categories":[1479,2161,2677,2629,1015,1343,1502,2045],"class_list":["post-19542","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-industrials","category-maintenance","category-predictive-analytics","category-predictive-maintenance","category-predictive-technology","category-railroads","category-railways","category-sensor"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/digitization-challenge-2016\/","yoast_head":"\nIf It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026 - Technology and Operations Management<\/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:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"If It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026 - Technology and Operations Management\" \/>\n<meta property=\"og:description\" content=\"The Power of Predictive Analytics to Improve Maintenance and Reliability in the Industrial Sector.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/\" \/>\n<meta property=\"og:site_name\" content=\"Technology and Operations Management\" \/>\n<meta property=\"og:image\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/KONUX_SwitchRailwayPicture.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1280\" \/>\n\t<meta property=\"og:image:height\" content=\"400\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/if-it-aint-broke-dont-fix-it-think-again\\\/\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/if-it-aint-broke-dont-fix-it-think-again\\\/\",\"name\":\"If It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026 - Technology and Operations Management\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/if-it-aint-broke-dont-fix-it-think-again\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/if-it-aint-broke-dont-fix-it-think-again\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2016\\\/11\\\/KONUX_SwitchRailwayPicture.jpg\",\"datePublished\":\"2016-11-18T22:11:21+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/if-it-aint-broke-dont-fix-it-think-again\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/if-it-aint-broke-dont-fix-it-think-again\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/if-it-aint-broke-dont-fix-it-think-again\\\/#primaryimage\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2016\\\/11\\\/KONUX_SwitchRailwayPicture.jpg\",\"contentUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2016\\\/11\\\/KONUX_SwitchRailwayPicture.jpg\",\"width\":1280,\"height\":400},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/if-it-aint-broke-dont-fix-it-think-again\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Submissions\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"If It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\",\"name\":\"Technology and Operations Management\",\"description\":\"MBA Student Perspectives\",\"potentialAction\":[{\"@type\":\"性视界Action\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"If It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026 - Technology and Operations Management","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/","og_locale":"en_US","og_type":"article","og_title":"If It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026 - Technology and Operations Management","og_description":"The Power of Predictive Analytics to Improve Maintenance and Reliability in the Industrial Sector.","og_url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/","og_site_name":"Technology and Operations Management","og_image":[{"width":1280,"height":400,"url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/KONUX_SwitchRailwayPicture.jpg","type":"image\/jpeg"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/","url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/","name":"If It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026 - Technology and Operations Management","isPartOf":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website"},"primaryImageOfPage":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/#primaryimage"},"image":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/#primaryimage"},"thumbnailUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/KONUX_SwitchRailwayPicture.jpg","datePublished":"2016-11-18T22:11:21+00:00","breadcrumb":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/#primaryimage","url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/KONUX_SwitchRailwayPicture.jpg","contentUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/KONUX_SwitchRailwayPicture.jpg","width":1280,"height":400},{"@type":"BreadcrumbList","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/if-it-aint-broke-dont-fix-it-think-again\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/d3.harvard.edu\/platform-rctom\/"},{"@type":"ListItem","position":2,"name":"Submissions","item":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/"},{"@type":"ListItem","position":3,"name":"If It Ain\u2019t Broke Don\u2019t Fix It? Think Again\u2026"}]},{"@type":"WebSite","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website","url":"https:\/\/d3.harvard.edu\/platform-rctom\/","name":"Technology and Operations Management","description":"MBA Student Perspectives","potentialAction":[{"@type":"性视界Action","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/d3.harvard.edu\/platform-rctom\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"}]}},"_links":{"self":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/19542","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission"}],"about":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/types\/hck-submission"}],"author":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/users\/2120"}],"replies":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/comments?post=19542"}],"version-history":[{"count":0,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/19542\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media\/19543"}],"wp:attachment":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media?parent=19542"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/categories?post=19542"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}