"I have lots of data and I don't know what to do with it"
"We collect a lot of data but not sure whether it is accurate or has any value which can be unlocked"
"We have conducted a lot of experiments and proof of concepts but very few of them have resulted in big operational or financial impacts"
These are the most common experiences we hear in our conversations with customers. These are definitely not trivial questions. We call it the Data-to-$-Chasm.The questions themselves not only relate to unidentified problems to solve but also includes unidentified answers to complex questions which needs macro and micro synthesis of large volumes of data.
Now, does this exercise of finding problems to solve, or finding answers to questions which needs large breadth of data worth the effort ? What if these experiments don't yield a BIG return on effort or investment. The short answer is "YES this is worth the effort"
We have been working on solving this problem for sometime now and has resulted in a core product suite within Cerebra called Pre-Diagnostics to aid engineers' maieutic enquiry process.
In the engineering world, first principles based interrogation techniques are still widely adopted, however when Physics + Chemistry + Ambient condition + Operating Procedures + Human behavior is involved, currently first principles based modeling is complex and sometimes unattainable. You never know there might be a day when the "real world" can be expressed with a universal equation !
For the time being let us stick to Pre-Diagnostics, These are some of the "Never before seen insights" our customers discovered using Cerebra Pre-Diagnostics, which enabled operational process changes and modifications to their industrial equipment ,
A leading industrial glove manufacturer discovered unusual changes to sensor behavior affecting product quality with Cerebra's Swarm Algorithm. Pollen pollution in the shop floor was ascertained as the root cause for this issue and extensive changes were done to set right the ambient operating conditions for the plant. Continuous monitoring of ambient conditions has now been institutionalized
A process chemicals manufacturer discovered deviations to the composition of the end product while it was manufactured with a particular industrial mixer. This was a decade old problem which had gone unnoticed. On further investigation it was ascertained that the type of blade used in the industrial mixer was leading to deviations in viscosity of the product. The machine resource allocation process has now been changed to add constraints related to product - machine mix
A gas processing plant had frequent failures on its valves resulting in periodic unplanned downtimes. The discovery process lead to surfacing insights related to non synchronized feedback loop from the control systems to the valves leading to friction. The plant is replacing its control systems architecture to prevent issues
A leading mining company discovered failure patterns on their milling machines when certain load thresholds were breached consistently over a period of time. New alarms were designed and put in place to detect progressive failure paths
Not long ago people could imagine only white swans, because white swans were all they had ever seen. And so people predicted that every next swan they would see would be white. The discovery of black swans shattered this prediction. The black swan is a metaphor for the uselessness of predictions that are based on earlier experiences, in the presence of unknown unknowns -Taleb,Nassim
Cerebra Pre-Diagnostics helps in identifying problem statements worth solving and use cases worth operationalizing in a short time
Watch out for the next feature in Cerebra Feature Series.
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