{"id":5246,"date":"2022-05-16T19:59:00","date_gmt":"2022-05-16T17:59:00","guid":{"rendered":"https:\/\/i-care.local\/resource\/moving-to-industry-4-0-is-your-organization-ready\/"},"modified":"2025-10-06T09:45:16","modified_gmt":"2025-10-06T07:45:16","slug":"moving-to-industry-4-0-is-your-organization-ready","status":"publish","type":"resource","link":"https:\/\/www.icareweb.com\/es\/recursos\/mantenimiento-predictivo\/moving-to-industry-4-0-is-your-organization-ready\/","title":{"rendered":"Is Your Organization Ready to Move to Industry 4.0?"},"content":{"rendered":"\n\n\n<div class=\"icare-acf-block icare-acf-block--text-column\">\n\n&nbsp;\r\n<h4 class=\"heading-4\">Moving to Industry 4.0 \u2014 Is Your Organization Ready?<\/h4>\r\nWith the Industry 4.0 market expected to grow from $70 billion (in 2019) to $210 billion by 2026<sup>1<\/sup>, there is no doubt the time has arrived for this \u201cnext evolution\u201d in manufacturing. As a result, many facility leaders are ready to enjoy the promise of Industry 4.0 as soon as they can.\r\n\r\nWhile such a desire is sensible, it may also be risky. Industry 4.0 can boost manufacturing outcomes, but it isn\u2019t a guaranteed cure-all. Companies cannot hit the ground running as soon as they \u201cadopt\u201d it. Rather, moving successfully to Industry 4.0 requires a thoughtful, well-executed plan that involves assessments, strategic planning and shifts in company culture. It can also include technology improvements, including data security.\r\n\r\nWill these activities delay the adoption? While this is possible, at I-care we don\u2019t think of it as a delay. We consider it an important step for success \u2014 and one that ensures all bases are covered. Moving to Industry 4.0 with care will reduce the odds of a failed effort. No one, from the board room to the plant floor, wants that outcome.\r\n\r\nAs someone who has been deeply involved with Industry 4.0 for many years \u2014 and as I-care\u2019s designated expert in this area \u2014 I offer you my insights.\r\n<h4 class=\"heading-4\">What Is Industry 4.0?<\/h4>\r\nIndustry 4.0 is not a method or an approach. It is the Fourth Industrial Revolution \u2014 the advance of manufacturing tools to adopt modern methods. It consists of three elements:\r\n<ul>\r\n \t<li>Speed \u2014 affected industries may be displaced at a rapid speed<\/li>\r\n \t<li>Scope and systems impact \u2014 A variety of companies and the systems they use to achieve goals may be affected by companies<\/li>\r\n \t<li>Strong shift in technology plan \u2014 new policies will drive innovation<\/li>\r\n<\/ul>\r\nTechnologies often embraced in Industry 4.0 programs include (but are not limited to) data connectivity, automation, IIoT (the Industrial Internet of things), artificial intelligence (AI), software, robots, and machine-to-machine (M2M) communications.\r\n\r\nThis is a broad definition that doesn\u2019t provide much insight, so let\u2019s go deeper. In short, Industry 4.0 is a fundamental shift in traditional manufacturing and industrial practices to make use of modern, smart technologies. As part of this approach, newer equipment is often self-monitoring and may be equipped to identify, analyze and adjust for problems without human involvement.\r\n\r\nThis ability requires data collection, with the data combined, processed and analyzed. In doing so, it elevates artificial intelligence to what we at I-care call \u201caugmented intelligence\u201d \u2014 insight that has been enhanced with the help of both data scientists and seasoned field experts empowering companies and their staffs to engage in a wide array of decision making.\r\n<h4 class=\"heading-4\">Where Industry 4.0 Can Veer Off-Course<\/h4>\r\nWhile the potential of Industry 4.0 is exciting, the results can be problematic. For many years, data scientists have handled data analysis. Their position has been, \u201cGive me your data and I will provide you with the necessary insights.\u201d Although this offer may seem tempting, it can be a barrier to success, especially when emerging approaches and methods are involved.\r\n\r\nData scientists may be able to interpret the data, but that doesn\u2019t mean they understand industrial production processes, nor are they the most informed about how to apply it in the field. In addition, modern sensors in manufacturing equipment can produce a huge amount of data that must be used properly to valorize it in the field.\r\n\r\nIn my experience, it is essential that executive leaders who plan to apply 4.0 methods either hire or partner with subject-matter experts \u2014 people who know what they are talking about. The options are varied and include reliability engineering specialists, operations and IT managers, statisticians and data scientists.\r\n\r\nThe team should include a range of skillsets, from predictive maintenance to vibration analysts, from Process engineers to Reliability engineers. I cannot stress this last point more firmly. Variety in Industry 4.0 teams will ensure that the right challenges are addressed that, if properly implemented, will lead to business value. If an industrial firm does not have the in-house expertise to cover all these specialties (and few do), they should look for an outside partner that can provide these skillsets and not just the technology.\r\n\r\nIn a future blog, I will drill into a proven data analysis approach that helps business leaders fine-tune their decision-making process at three strategic levels. To be added to our list of blog subscribers, click here.\r\n<h4 class=\"heading-4\">Interested in starting a conversation with Tom? Connect with him <a href=\"https:\/\/www.linkedin.com\/in\/tom-rombouts-91419113\/\"><span style=\"text-decoration: underline;\">here<\/span> <\/a>on LinkedIn.<\/h4>\r\n1 https:\/\/www.globenewswire.com\/news-release\/2021\/09\/22\/2301460\/0\/en\/Industry-4-0-Market-Size-Share-Statistics-Value-Will-Grow-to-USD-210-Billion-by-2026-Global-Estimation-by-Facts-Factors.html\n<\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"featured_media":3153,"menu_order":0,"template":"","meta":{"_acf_changed":false,"_seopress_robots_primary_cat":"0","_seopress_titles_title":"","_seopress_titles_desc":"","_seopress_robots_index":"","content-type":"","inline_featured_image":false},"knowledge-industries":[],"knowledge-topics":[324],"knowledge-types":[92],"class_list":{"0":"post-5246","1":"resource","2":"type-resource","3":"status-publish","4":"has-post-thumbnail","6":"topic-mantenimiento-predictivo","7":"post-cat-blog-es"},"acf":[],"_links":{"self":[{"href":"https:\/\/www.icareweb.com\/es\/wp-json\/wp\/v2\/knowledge\/5246","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.icareweb.com\/es\/wp-json\/wp\/v2\/knowledge"}],"about":[{"href":"https:\/\/www.icareweb.com\/es\/wp-json\/wp\/v2\/types\/resource"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.icareweb.com\/es\/wp-json\/wp\/v2\/media\/3153"}],"wp:attachment":[{"href":"https:\/\/www.icareweb.com\/es\/wp-json\/wp\/v2\/media?parent=5246"}],"wp:term":[{"taxonomy":"industry","embeddable":true,"href":"https:\/\/www.icareweb.com\/es\/wp-json\/wp\/v2\/knowledge-industries?post=5246"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/www.icareweb.com\/es\/wp-json\/wp\/v2\/knowledge-topics?post=5246"},{"taxonomy":"post-cat","embeddable":true,"href":"https:\/\/www.icareweb.com\/es\/wp-json\/wp\/v2\/knowledge-types?post=5246"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}