Submitted by Andrew Waycott, COO & Co-Founder at TwinThread
Picture this as a use case for remote manufacturing: One of your pump experts is capable of monitoring your entire fleet of pumps globally and across your entire operation, instead of just interpreting data on a per-asset or per-location basis. Imagine what that could mean with regard to scaling that expert’s knowledge, paired with the insights they uncover.
Simply put, you want to be able to free your subject-matter experts up to accomplish as much as they possibly can. Having them duplicate their efforts by physically traveling to this site and that site, and this factory and that factory, and this asset and that asset will not allow them to maximize their time and scale their findings. However, if they could see the performance of all assets, from one place, they would be much more capable of quickly and easily identifying opportunities to scale the findings of top-performing assets and pieces of equipment.
With the connectivity an intuitive Predictive Operations Platform provides, your problem-solvers will be fed the information they need without having to be in the physical location where the data is originating. This means your key operational decision-makers will be freed from strategizing in the blind. Instead, it will be quick and clear where opportunities for improved efficiency reside.
Without real-time access to enterprise-wide performance data, your experts are siloed. With the ability to remotely determine top performing assets, the only question that remains is, what will you be optimizing at scale next?
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