{"id":11955,"date":"2018-04-07T11:00:02","date_gmt":"2018-04-07T19:00:02","guid":{"rendered":"http:\/\/www.palada.net\/index.php\/2018\/04\/07\/news-5724\/"},"modified":"2018-04-07T11:00:02","modified_gmt":"2018-04-07T19:00:02","slug":"news-5724","status":"publish","type":"post","link":"http:\/\/www.palada.net\/index.php\/2018\/04\/07\/news-5724\/","title":{"rendered":"Science vs the senses: where predictive analytics and intuition converge"},"content":{"rendered":"

Credit to Author: Greg Johnson| Date: Fri, 06 Apr 2018 20:08:46 +0000<\/strong><\/p>\n

\u00a0\u201cElectrical science has disclosed to us the more intimate relation existing between widely different forces and phenomena and has thus led us to a more complete comprehension of Nature and its many manifestations to our senses.\u201d – Nikola Tesla<\/em><\/strong><\/p>\n

When talking about digitization, Industry 4.0 and the IIOT<\/a>, the conversation can quickly turn to predictive analytics<\/a>. After all, simply collecting reams of data made possible by those technologies is not the objective, whereas doing something productive and meaningful with it is.\u00a0 And predictive analytics is the poster child of putting data to work for you. \u00a0There are some really impressive use cases<\/a> that demonstrate this, especially in industries like power generation where a very small issue at 3000 RPMs can quickly turn into a very expensive one.<\/p>\n

Predictive analytics models come in several varieties.\u00a0 They can be based on experience (empirical), physics (e.g. wear rates) or data. Data modelling is the newest technique brought by digitization which adds data science, such as pattern matching, to the many streams of data available from equipment. Data science truly does give us a far more \u201ccomplete comprehension of Nature\u201d (and of our industrial world) than our senses alone.<\/p>\n

\"\"But predictive analytics is not all knowing, all seeing, or all doing however. In fact, it is really only part of the solution. The well-known Asset Management expert Terry Wireman used to have a slide deck in which he showed a pyramid representing good maintenance practices. Predictive was just one part of the pyramid, and close to the top. \u00a0At the bottom were the basics like good stores management, routine scheduled preventive maintenance, etc. After talking about the basics, he would always say, \u201cif you haven\u2019t done these, then STOP!\u201d<\/p>\n

And while Tesla understood that science enabled a more complete understanding of the world around us, he also believed that science alone wasn\u2019t the answer. He trusted in the human ability to sense things that science could not.<\/p>\n

\u201cInstinct is something which transcends knowledge. We have, undoubtedly, certain finer fibres that enable us to perceive truths when logical deduction, or any other wilful effort of the brain, is futile.\u201d \u2013 Nikola Tesla<\/em><\/strong><\/p>\n

That same philosophy can also be found in the highly admired Japanese concept of Total Productive Maintenance (TPM). TPM recognizes that operators are often in the best position to understand and assess the equipment they operate, and one of the ways they achieve this is by identifying equipment condition using their 5 senses (sight, hearing, smell, touch, taste\u2026though I don\u2019t recommend tasting too many machines!). \u00a0In Japanese, this is called\u4e94\u611f\u3067\u306e\u70b9\u691c(Gokan de no tenken).<\/p>\n

It\u2019s like driving your car.\u00a0 You know long before anyone else if it\u2019s starting to make a funny new sound (bad bearing? low on oil?), if it feels differently when you apply the brakes (worn brake shoes?), or even if it might smell differently (overheating?).\u00a0 Industrial equipment operators enjoy the same level of familiarity with their machines and are also very attuned to the nuances of their condition.<\/p>\n

The interesting part to me is that now, with digitization and all of the IIOT data made available to us, the two methods, the human and the scientific, are actually converging rather than getting farther apart as you might suspect.\u00a0 More data does not mean less human input.<\/p>\n

Why?\u00a0 Because data can be used in a very natural way to augment the 5 human senses through technology such as Augmented Reality.\u00a0 Why wait to get back to your office to check on the condition of a machine when you can have all of this real-time information available \u2013 on throughput, energy consumption, temperature, pressure, safety incidents and more \u2013 it can all be delivered in context just by viewing that piece of equipment using an app and the camera of an industrial tablet?<\/p>\n

Augmented Reality, via a solution like EcoStruxure Augmented Operator Advisor<\/a>, can now actually provide this capability. \u00a0It lets you blend both your intuition and senses with the science and technology made possible by our digital world.<\/p>\n

And if you combine that with a financial tool like EcoStruxure Profit Advisor<\/a>, which factors in the monetary implications of different paths of action, you have a powerful new way to improve your business from the plant floor on up.<\/p>\n

The human senses and technology.\u00a0 It might seem like an unlikely match, but it is actually more like a match made in heaven.<\/p>\n

The post Science vs the senses: where predictive analytics and intuition converge<\/a> appeared first on Schneider Electric Blog<\/a>.<\/p>\n

http:\/\/blog.schneider-electric.com\/feed\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Credit to Author: Greg Johnson| Date: Fri, 06 Apr 2018 20:08:46 +0000<\/strong><\/p>\n

\u00a0\u201cElectrical science has disclosed to us the more intimate relation existing between widely different forces and phenomena and has thus led us to a more complete comprehension of Nature and… Read more »<\/a><\/p>\n

The post Science vs the senses: where predictive analytics and intuition converge<\/a> appeared first on Schneider Electric Blog<\/a>.<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"colormag_page_container_layout":"default_layout","colormag_page_sidebar_layout":"default_layout","footnotes":""},"categories":[12389,12388],"tags":[13245,12581,18043,17843,12539,12512,12508,12438,12547,4229],"class_list":["post-11955","post","type-post","status-publish","format-standard","hentry","category-scadaics","category-schneider","tag-automation-and-control","tag-digitization","tag-ecostruxure-augmented-operator","tag-ecostruxure-profit-advisor","tag-food-and-beverage","tag-iiot","tag-machine-and-process-management","tag-miningmetalsminerals","tag-predictive-analytics","tag-water"],"_links":{"self":[{"href":"http:\/\/www.palada.net\/index.php\/wp-json\/wp\/v2\/posts\/11955","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.palada.net\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.palada.net\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.palada.net\/index.php\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"http:\/\/www.palada.net\/index.php\/wp-json\/wp\/v2\/comments?post=11955"}],"version-history":[{"count":0,"href":"http:\/\/www.palada.net\/index.php\/wp-json\/wp\/v2\/posts\/11955\/revisions"}],"wp:attachment":[{"href":"http:\/\/www.palada.net\/index.php\/wp-json\/wp\/v2\/media?parent=11955"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.palada.net\/index.php\/wp-json\/wp\/v2\/categories?post=11955"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.palada.net\/index.php\/wp-json\/wp\/v2\/tags?post=11955"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}