IIOT is all about gathering information from everywhere, analyzing it, and using the results to improve operations and manufacturing efficiency. Manufacturing organizations have terrabytes of data already, so what magical powers does the IIOT bring to the table? Do we really need more data? More importantly, what does a FitBit have to do with that?
I wear a FitBit Blaze™ religously, and I use a FitBit Aria™ scale at home that integrates with the FitBit app. Between the two devices, there are four sensors, and from that I get the following:
- Heart Rate
- Body Fat Percentage
- Total steps walked
- Distance walked
- Floors climbed
- BMI (Body Mass Index)
- Minutes of exercise
- Time spent at a cardio level heart rate
- Time spent at a fat burning level heart rate
- Hours of total sleep
- Hours spent in deep sleep
- Hours spent in REM sleep
- Hours spent in light sleep
- Time based trends for almost all of the above
Behavioral Change (Process Improvement)
- Goals for almost all of the above (how can I improve?)
- Encouragement (Award badges for various achievements, update on goal progress)
- Collaboration (Challenges with friends)
That's a lot of information from a scale and a watch! The data presented is useful on some level, but the constant interaction to keep me focussed on improvement is where I derive most of the value from these devices. I exercise more, and I (mostly) keep my weight in check thanks to the constant motivation courtesy of FitBit's software.
Water Distribution Pump
How does this apply to your plant? Take a look at a water distribution pump driven by a VFD.
- Running Status
- Fault Status
- Power consumed
- Pump efficiency
- Running time
- Start/stop cycles
- Pump failure (no flow or pressure, but running feedback)
- Pipe failure (high flow, low pressure)
- Dead headed (no flow, high pressure)
- Pump wear (efficiency falling over time)
- Cost per volume pumped (with input of rate schedule)
- Cost per time of day
- Average, peak, total water demand per timeframe
- Average, minimum, maximum water pressure per timeframe
- Operator response time for pump and instrument failures
- Preventive maintainence based on running time, running cycles, or efficiency loss
- Downtime tracking and resulting improvement objectives
- Operations goals for improving cost/volume or cost/time
- Operations goals for improving system pressure consistency
- Operations goals for improving failure response times
Again, not that much data coming in, but there is alot of additional information that can be derived from the physical sensors. Most importantly, there are plenty of opportunities to influence operator behavior to optimize control systems and drive down operational costs.
The key to receiving benefit from the IIOT is willingness to embrace bottom-up process improvement. The app-driven culture of this decade has provided ample evidence that improvement can be driven by influencing the motivations at the individual level. We already have a wealth of data from our manufacturing facilities filling up our hard drives. The real cost savings will come not from adding additional instruments, but from using the data we already have to incrementally influence operator motivations and behavior.
At the end of the day, it won't be the size of your data that matters, but how you use it.
Learn some practical next steps in our recent IIOT blog post.
Learn more about implemting manufacturing intelligence in your plant.