parel, pharmaceuticals, oil and gas, personal care products, building materials and textiles. We’ve done implementations ranging from a single machine to a manufacturing process that spans multiple plants and a very broad range of produc- tion equipment and processes. We’re also working across links in the supply chain. One of our customers is using Sight Machine in plants owned and operated by its contract manufacturers. ME: Describe how one customer
is processing billions of data points per week, optimizing its global manufactur- ing. What are the productivity gains made with this type of technology? Sobel: This company uses contract manufacturers in multiple countries to make the same product. The com- pany invested heavily in new production equipment, which it configured and then installed at the contractor facilities. Each one of these machines contains hundreds of sensors constantly outputting data. Even though machines at different
plants are identical, they sometimes per- form differently. The data tells the client why and enables the client to develop and improve standardized best prac- tices and raise overall efficiency. In one example, downtime at one of the client’s facilities was consistently higher than at the other facilities. Using the digital twin of their operation created with the Sight Machine platform, the client was able to determine there was nothing wrong with the machine, the configuration or the way it was being operated. Instead, the problem was ambient atmospheric conditions. This is the kind of systematic data-driven analysis that allows compa- nies to move to proactive, automatic, and continuous analysis of operations. ME: How much progress have manufacturing operations made in implementing advanced data analytics, leveraging technologies like Big Data and the Industrial Internet of Things?
Sobel: A lot of companies have learned that collecting
data isn’t the same as using it. Companies have invested enormous sums in things like data lakes, which by them- selves don’t do anything. What they’re really looking for is
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December 2016 |
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