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Machine-to-machine (M2M) learning is an integral apart of the expanding world of Industrial IoT

Machine-to-machine (M2M) learning is an integral apart of the expanding world of Industrial IoT. Over the past few months we have given attention to manufacturing and its current digital disruption, but have failed to show the direct impact smart M2M and IoT technology is having on the industry. So, this week we are diving deeper into the term machine learning and how it connects to manufacturing both today and in the future.

Before we get to our news round up let's start by re-defining M2M, to ensure we are all on the same page with its purpose and meaning. Gartner has defined machine-2-machine communications as "something used for automated data transmission and measurement between mechanical or electronic devices."

Now, that we have defined M2M, its time to check out our top news round up for the week on how M2M applies to both manufacturing and IoT.

10 ways machine learning is revolutionizing manufacturing

Machine Learning M2M Manufacturing

Machine learning is poised to improve manufacturing by streamlining the process of OT and IT, thus increasing efficiency and lowering overall operation costs. Louis Columbus at Forbes believes that "Every manufacturer has the potential to integrate machine learning into their operations and become more competitive by gaining predictive insights into production."

IoT will recharge Machine Manufacturers

Machine Learning - Manufacturing Recharge

Manufacturing can look to software companies as an example of how IoT can implement creating a smarter M2M network. Timothy Chou with CFO.com writes, "Today, manufacturers of machines - whether seed drills, chillers, or CT scanners - can leverage the path paved by the software product companies through three new business models: service and support; assisted services and machine-as-a-service."

Climbing the IoT Mountain-by adding M2M to manufacturing

IoT Mountain - M2M Manufacturing

Manufacturing is only at the beginning of its ascent into IoT and M2M, so there are many more bumps and obstacles a long the way for the industry to fully integrate. Ronnie Garrett with Supply & Demand Chain Executive describes IoT and M2M manufacturing implementation as, "Standing at the foot of Mount Everest, ready to climb the world's tallest mountain. You know you want to get to the top but you aren't really sure how you will get there or what obstacles you'll encounter along the way."

Cybersecurity is manufacturing's biggest risk factor

cybersecurity - M2M manufacturing

Manufacturing needs to continue to add M2M automation and big data analytics to the shop floor, but a threat to the overall industry is manifesting itself in the cybersecurity world. Ian Wright with Engineering.com informs writes, "A new report from BDO indicates that 92 percent of manufacturers cited cybersecurity concerns in their SEC disclosures this year. According to BDO, this represents a 44 percent increase compared to the first Manufacturing Risk Factor report in 2013."

As we wrap up our top news for the week, we realize the need to fully implement advanced machine learning across the manufacturing world will take more than a simple flick of the wrist. With that said, we leave you with a cautionary tale of when automation goes wrong. It was recently discovered an airport in India had an sign translated with automation software which read, "eating carpet strictly prohibited" - of course this was not the translation they had meant to display. Regardless, as we move towards a fully integrated M2M world, we will have to adjust our equations depending our our intended outcome, much like the world is finding with the love/hate of language automation.

Hope you have enjoyed this week's top news, as always tell us your thoughts on M2M and how it might impact your world!

More Stories By Scott Allen

Scott is an executive leader with more than 25 years of experience in product lifecycle management, product marketing, business development, and technology deployment. He offers a unique blend of start-up aggressiveness and established company executive leadership, with expertise in product delivery, demand generation, and global market expansion. As CMO of FreeWave, Scott is responsible for product life cycle/management, GTM execution, demand generation, and brand creation/expansion strategies.

Prior to joining FreeWave, Scott held executive management positions at Fluke Networks (a Danaher Company), Network Associates (McAfee), and several start-ups including Mazu Networks and NEXVU Business Solutions. Scott earned his BA in Computer Information Systems from Weber University.

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