Predictive Maintenance In Edge - While Others Are Still Discussing, MachineSense Has Been On Edge Since 2016.
2018 marked the year of edge computing in IoT world. Satya Nadela, CEO of Microsoft sent a memo to all Microsoft employees, emphasizing why edge computing and edge cloud were going to be vital to success going ahead. Sundar Pichai, CEO of Google, also emphasized the emerging role of edge computing in the Google I/O conference in May 2018. Siemens and Microsoft delivered a joint demonstration of Edge Cloud capability at Hannover Messe in April this year.
What is Edge Computing?
Edge computing technique makes IIoT-based predictive maintenance more efficient and effective. Here the analytics is done close to the IoT devices and sensors, i.e., done right on the factory floor in real time.
Edge Computing vs Cloud Computing
Edge reduces the burden on networks while keeping other expenses low. It can work with basic infrastructure and low-end gateway devices. Edge computing can deliver full analytics even when there is poor connectivity or no connectivity and since most of the data/analytics are contained within the factory, the security concern is limited. Not just saving companies 80-90% cloud computing costs, edge computing can also deliver high speed, real time analytics on mobiles or tablets.
Cloud computing subscription costs can skyrocket expenses. If network connections are spotty, high speed sensors such as vibration, current can’t be easily connected to cloud. The security concern is also higher because all the devices are dumping data to the cloud and real time analytics is not available.
However, either edge or cloud computing can take a prominent position depending on the situation. Scenarios where there is need for low latency and/or bandwidth constraints, edge computing will be dominant whereas cloud computing will be required for situations where large volume of data needs to be managed and stored across plants, for example.
Predictive Maintenance with Edge Computing
Predictive maintenance solutions that are based on IIoT and edge computing are helping manufacturers in numerous ways. They have been known to reduce downtime, improve equipment efficiency and effectiveness, lower maintenance costs and increase return on assets.
MachineSense and Edge Computing
While the large companies are getting into this now, MachineSense LLC, a start-up in the predictive maintenance space, implemented edge computing in their Electrical Power Quality last year. This year they have added full edge functionality in Vibration Analyzer. In fact, while the world is just waking up to edge, MachineSense started their R&D journey with edge in the beginning of 2016. In the initial days, the company trialed with many single board computers in the industrial environment where ambient temperature can exceed 120F (405C). After many trials and errors of how to cool down the processors of tiny single board computer and its frequent re-booting issues, by end of 2016, the company adopted a refurbished single board computer as its edge device and went on to build edge analytics in it.
Edge computing can unlock the full potential of predictive maintenance. It can yield greater benefits for companies and achieve desired outcomes. MachineSense with their avant garde outlook is the company to watch out for!