“A lot of machine shops are stuck in the 20th century,” Lou Zhang, chief data scientist at MachineMetrics, recently told MD+DI. “Basically, they have machines sitting on their floors that are running and they’re making parts, but nobody really knows, besides the operators, what they’re doing on an hour-to-hour basis, and this is how manufacturing has worked for the last hundred years or so.”
Zhang said that this is one of the biggest problems hindering efficiency in manufacturing. But by implementing the Industrial Internet of Things (IIoT), a manager would be able to see in one centralized display—whether it be a computer, iPad, or phone—whether machines are on or off, whether they are running efficiently, and how many parts they have made, as well as if there are any errors, alarms, or warnings on them, he explained.
In his presentation at the upcoming MD&M Minneapolis show, “Automation Challenges Slowing the Advance of IIoT in Manufacturing,” Zhang said he will focus on the first step of what he calls the analytics journey. “The first step towards that analytics journey is getting your machines connected, getting some basic dashboards up, and having that descriptive analytics component enabled.” After the descriptive stage, diagnostic analytics and finally predictive and prescriptive analytics can be enabled.
https://www.mddionline.com/implementing-industrial-internet-things-iiot-medical-device-manufacturing
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