Arun Santhebennur's guest appearances

Arun Santhebennur

The Early Stage Podcast

Rooted in Reliability: The Plant Performance Podcast

Maintenance Disrupted

Peter Horsburgh

Adam Stredel

Fred Schenkelberg

Alan Ross

Jeff Shiver

Simon Jagers

Paul Daoust

Doug Waetjen

Suzane Greeman

Calvin Williams

Sanya Mathura

Doug Plucknette

Adrian Messer

Blair Fraser

Jesus Sifonte

OwlTail

Pilot to Full Scale Adoption of iIoT with Arun Santhebennur The Industrial Internet of Things is not an initiative. It is now a real-world application. For organizations that are data-driven, IIoT is where rubber meets the road. The fourth industrial revolution being hallmarked by growing networks around people and things. As the internet becomes more mature, we re seeing a new era of innovations building on to the influence created by social media. It is the Internet of Things (IoT) which aims to connect people to smart devices. Industry players are seeking ways of leaner and smarter production to remain competitive. Industrial IoT (IIoT) comes in with provisions of monitoring and preventive maintenance to improve productivity. The end goal is optimizing the life of production assets.  In this episode, Arun shares his insights on:  How people can pilot and bring full-scale adoption of IIoT What improvement IIoT can bring The critical steps in adopting IIoT solutions Challenges and ways to overcome successful shift to IIoT   IIoT has made sensor technologies and data harvesting simpler by having internet integration. Profitability is one of the beneficiaries of more affordable sensors and real-time data. Engineers and executives can now get a bird s eye view of the facility s health. They can even drill down to one machine, all through dashboards connected to IIoT devices. Improved visibility into operations translates to increased safety. IIoT tools are empowering managers about plant health through a predictive approach. Symptoms that spell danger to staff and other operators on-site can be addressed well in advance. There is still relatively low awareness of IIoT. Plant managers still don’t know where or how to start implementing these solutions. For such prospects, the validation process should go through three steps:  Validating the technology. This implies researching and testing the sensors to see what valuable insights can be derived from its collected data Validating the business.  This focuses on the improvement in performance or safety. The bottom line is its contribution to more productivity for the company Validating change management which underpins the other two. With new technology, it becomes important to get the staff support to make it effective. The value created from IIoT solutions needs to be packaged and communicated effectively.  It is not so much a technology change as it is a cultural one.  Without a clear validation process, companies risk having another  good technology  idling.  Common telltale signs start with a lack of network planning and communication. This could be as a result of making an investment decision without seeking opinion from end-use operators. Another pitfall is lacking the right combo of data analysis and engineering. Without this expertise, it becomes difficult to extract insights from the available sensor data.  To overcome hurdles on the road to IIoT integration, it starts with having the right culture. Across the organization, support towards improved technologies should be clear and well communicated. That way, solutions will have one less dimension of challenges in their implementation. Understanding the technologies and available skills is another ingredient of successful implementation. Skilled personnel implement these solutions at scale and take advantage of their full functionality. These people will also be key in choosing high visibility, high ROI projects that validate adoption. All in all, if the culture isn t right, you shouldn t expect the outcome to be. Eruditio Links:  Eruditio HP Reliability James Kovacevic s LinkedIn Reliability Report  Arun Santhebennur Links:  Petasense LinkedIn page Petasense website Arun Santhebennur LinkedIn ERPI.org SMRP.org Engineering Mindset Youtube Channel  Download RSS iTunesStitcher Rooted In Reliability podcast is a proud member of Reliability.fm network. We encourage you to please rate and review this podcast on iTunes and Stitcher. It ensures the podcast stays relevant and is easy to find by like-minded professionals. It is only with your ratings and reviews that the Rooted In Reliability podcast can continue to grow. Thank you for providing the small but critical support for the Rooted In Reliability podcast! The post 181-Pilot to Full Scale Adoption of iIoT with Arun Santhebennur appeared first on Accendo Reliability.

<h1>Pilot to Full Scale Adoption of iIoT with Arun Santhebennur</h1> The Industrial Internet of Things is not an initiative. It is now a real-world application. For organizations that are data-driven, IIoT is where rubber meets the road. The fourth industrial revolution being hallmarked by growing networks around people and things. As the internet becomes more mature, we re seeing a new era of innovations building on to the influence created by social media. It is the Internet of Things (IoT) which aims to connect people to smart devices. Industry players are seeking ways of leaner and smarter production to remain competitive. Industrial IoT (IIoT) comes in with provisions of monitoring and preventive maintenance to improve productivity. The end goal is optimizing the life of production assets. In this episode, Arun shares his insights on: <ul> <li>How people can pilot and bring full-scale adoption of IIoT</li> <li>What improvement IIoT can bring</li> <li>The critical steps in adopting IIoT solutions</li> <li>Challenges and ways to overcome successful shift to IIoT</li> </ul> IIoT has made sensor technologies and data harvesting simpler by having internet integration. Profitability is one of the beneficiaries of more affordable sensors and real-time data. Engineers and executives can now get a bird s eye view of the facility s health. They can even drill down to one machine, all through dashboards connected to IIoT devices. Improved visibility into operations translates to increased safety. IIoT tools are empowering managers about plant health through a predictive approach. Symptoms that spell danger to staff and other operators on-site can be addressed well in advance. There is still relatively low awareness of IIoT. Plant managers still don’t know where or how to start implementing these solutions. For such prospects, the validation process should go through three steps: <ol> <li>Validating the technology. This implies researching and testing the sensors to see what valuable insights can be derived from its collected data</li> <li>Validating the business.  This focuses on the improvement in performance or safety. The bottom line is its contribution to more productivity for the company</li> <li>Validating change management which underpins the other two. With new technology, it becomes important to get the staff support to make it effective. The value created from IIoT solutions needs to be packaged and communicated effectively.  It is not so much a technology change as it is a cultural one.</li> </ol> Without a clear validation process, companies risk having another good technology idling.  Common telltale signs start with a lack of network planning and communication. This could be as a result of making an investment decision without seeking opinion from end-use operators. Another pitfall is lacking the right combo of data analysis and engineering. Without this expertise, it becomes difficult to extract insights from the available sensor data.  To overcome hurdles on the road to IIoT integration, it starts with having the right culture. Across the organization, support towards improved technologies should be clear and well communicated. That way, solutions will have one less dimension of challenges in their implementation. Understanding the technologies and available skills is another ingredient of successful implementation. Skilled personnel implement these solutions at scale and take advantage of their full functionality. These people will also be key in choosing high visibility, high ROI projects that validate adoption. All in all, if the culture isn t right, you shouldn t expect the outcome to be. Eruditio Links: <ul> <li><a href="http://eruditio.com/" rel="noopener nofollow" target="_blank">Eruditio</a></li> <li><a href="https://hpreliability.com/" rel="noopener nofollow" target="_blank">HP Reliability</a></li> <li><a href="https://www.linkedin.com/in/jameskovacevic" rel="noopener nofollow" target="_blank">James Kovacevic s LinkedIn</a></li> <li><a href="https://www.youtube.com/channel/UC88Nfs79n-wN6Io86SQ9B0g" rel="noopener nofollow" target="_blank">Reliability Report</a></li> </ul> Arun Santhebennur Links: <ul> <li><a href="https://www.linkedin.com/company/petasense/" rel="noopener nofollow" target="_blank">Petasense LinkedIn page</a></li> <li><a href="https://petasense.com/" rel="noopener nofollow" target="_blank">Petasense website</a></li> <li><a href="https://www.linkedin.com/in/arunsanthebennur" rel="noopener nofollow" target="_blank">Arun Santhebennur LinkedIn</a></li> <li><a href="https://erpi.org/" rel="noopener nofollow" target="_blank">ERPI.org</a></li> <li><a href="http://smrp.org/" rel="noopener nofollow" target="_blank">SMRP.org</a></li> <li><a href="https://www.youtube.com/channel/UCk0fGHsCEzGig-rSzkfCjMw" rel="noopener nofollow" target="_blank">Engineering Mindset Youtube Channel</a></li> </ul> <a href="http://episodes.reliability.fm/rir/rir-s01-e181-pilot-to-full-scale-adoption-of-iiot-with-arun.mp3" rel="noopener nofollow" target="_blank">Download</a> <a href="https://accendoreliability.com/series/rir/feed/" rel="noopener nofollow" target="_blank">RSS</a> <a href="https://itunes.apple.com/ca/podcast/rooted-in-reliability/id1122844720" rel="noopener nofollow" target="_blank">iTunes</a><a href="http://www.stitcher.com/s?fid=92320&amp;refid=stpr" rel="noopener nofollow" target="_blank">Stitcher</a> Rooted In Reliability podcast is a proud member of <a href="https://accendoreliability.com/reliability-fm/" rel="noopener nofollow" target="_blank">Reliability.fm</a> network. We encourage you to please rate and review this podcast on <a href="https://itunes.apple.com/ca/podcast/rooted-in-reliability/id1122844720" rel="noopener nofollow" target="_blank">iTunes </a>and <a href="http://www.stitcher.com/s?fid=92320&amp;refid=stpr" rel="noopener nofollow" target="_blank">Stitcher</a>. It ensures the podcast stays relevant and is easy to find by like-minded professionals. It is only with your ratings and reviews that the Rooted In Reliability podcast can continue to grow. Thank you for providing the small but critical support for the Rooted In Reliability podcast! The post <a href="https://accendoreliability.com/podcast/rir/181-pilot-full-scale-adoption-iiot-arun-santhebennur/" rel="nofollow" target="_blank">181-Pilot to Full Scale Adoption of iIoT with Arun Santhebennur</a> appeared first on <a href="https://accendoreliability.com" rel="nofollow" target="_blank">Accendo Reliability</a>.

Pilot to Full Scale Adoption of iIoT with Arun Santhebennur

In this week's episode, I welcome on the co-founder of Petasense, Arun Santhebennur. We talk about why we need to monitor multiple parameters when looking at machine condition and how to apply machine learning correctly. Check out Petasense - www.petasense.com  Thank you for listening and if you enjoy the show, please subscribe to Rob's Reliability Project on your favourite podcast platform and share it with your colleagues.  You can also follow Rob's Reliability Project on LinkedIn and Facebook and check out robsreliability.com as well. If you're looking for a shorter tip, subscribe to Rob's Reliability Tip of the Day on your favorite podcast platform or on your Amazon Alexa as a Flash Briefing. Finally, if there are any topics, guests you'd like to hear from, questions you want answered, or if you'd like to appear on the podcast, email me at robsreliabilityproject@gmail.com Follow Rob's Reliability Project on LinkedIn - https://www.linkedin.com/company/robsreliabilityproject/ Follow Rob's Reliability Project on Facebook - https://www.facebook.com/robsreliabilityproject/ Music by XTaKeRuX, Song: White Crow is licensed under a Creative Commons 4.0 Attribution License.

In this week's episode, I welcome on the co-founder of Petasense, Arun Santhebennur. We talk about why we need to monitor multiple parameters when looking at machine condition and how to apply machine learning correctly. Check out Petasense - <a href="http://www.petasense.com" rel="nofollow" target="_blank">www.petasense.com</a> Thank you for listening and if you enjoy the show, please subscribe to Rob's Reliability Project on your favourite podcast platform and share it with your colleagues.  You can also follow Rob's Reliability Project on LinkedIn and Facebook and check out <a href="http://robsreliability.com/" rel="nofollow" target="_blank">robsreliability.com</a> as well. If you're looking for a shorter tip, subscribe to Rob's Reliability Tip of the Day on your favorite podcast platform or on your Amazon Alexa as a Flash Briefing. Finally, if there are any topics, guests you'd like to hear from, questions you want answered, or if you'd like to appear on the podcast, email me at <a href="mailto:robsreliabilityproject@gmail.com">robsreliabilityproject@gmail.com</a> Follow Rob's Reliability Project on LinkedIn - <a href="https://www.linkedin.com/company/robsreliabilityproject/" rel="nofollow" target="_blank">https://www.linkedin.com/company/robsreliabilityproject/</a> Follow Rob's Reliability Project on Facebook - <a href="https://www.facebook.com/robsreliabilityproject/" rel="nofollow" target="_blank">https://www.facebook.com/robsreliabilityproject/</a> Music by <a href="https://twitter.com/xtakerux_music?lang=en" rel="cc:attributionURL nofollow" target="_blank">XTaKeRuX</a>, Song: White Crow is licensed under a Creative Commons 4.0 <a href="http://creativecommons.org/licenses/by/4.0/" rel="license nofollow" target="_blank">Attribution License</a>.

Machine Condition with Arun Santhebennur

Today, I have the pleasure to sit with Arun Santhebennur, Co-Founder and COO of an industrial IoT (IIoT) startup based in San Jose called PetaSense. Industrial IoT has really come to the forefront through efforts by General Electric (Predix), other large digital industrial companies, and a burgeoning cadre of entrepreneurs. Tons of data is created from manufacturing technologies that are currently not being captured, and old technology is not equipped with sensors that would allow manufacturers to understand what is actually happening with their equipment.Petasense wants to build an experience for manufacturing similar to the FitBit for our health. By retro-fitting manufacturing equipment with sensors to measure vibration, we can capture data to analyze the health of the machines.For every gas turbine, a $1M+ piece of equipment that is already instrumented, there are three or four hundred lower cost machines with rotating parts that aren't being tracked. With low-cost continuous monitoring technology, Petasense provides predictive maintenance to every machine with moving parts.The biggest cost in manufacturing is not necessarily repairing broken machines, rather the lost output from unplanned downtime. Often times, problems with a machine running at 75% efficacy is undetected, which costs the company extra power and lost output. Hidden problems may even cause the machine to break more quickly.If you are interested in the evolution of manufacturing, listen in.

Today, I have the pleasure to sit with Arun Santhebennur, Co-Founder and COO of an industrial IoT (IIoT) startup based in San Jose called PetaSense. Industrial IoT has really come to the forefront through efforts by General Electric (Predix), other large digital industrial companies, and a burgeoning cadre of entrepreneurs. Tons of data is created from manufacturing technologies that are currently not being captured, and old technology is not equipped with sensors that would allow manufacturers to understand what is actually happening with their equipment. Petasense wants to build an experience for manufacturing similar to the FitBit for our health. By retro-fitting manufacturing equipment with sensors to measure vibration, we can capture data to analyze the health of the machines. For every gas turbine, a $1M+ piece of equipment that is already instrumented, there are three or four hundred lower cost machines with rotating parts that aren't being tracked. With low-cost continuous monitoring technology, Petasense provides predictive maintenance to every machine with moving parts. The biggest cost in manufacturing is not necessarily repairing broken machines, rather the lost output from unplanned downtime. Often times, problems with a machine running at 75% efficacy is undetected, which costs the company extra power and lost output. Hidden problems may even cause the machine to break more quickly. If you are interested in the evolution of manufacturing, listen in.

Petasense - Arun Santhebennur, Co-Founder and COO