Hitachi, dataPARC team on smart manufacturing, industrial data transformation

Industrial data management and analytics software provider dataPARC and systems integrator and IT services provider Hitachi Systems have debuted a collaboration whereby Hitachi will integrate dataPARC’s industrial data platform—featuring its advanced historian and PARCview analytics toolkit—into its suite of digital manufacturing solutions.

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As part of its industrial digital transformation (DX) initiatives, Hitachi Systems supports customers in collecting, connecting, and utilizing data from across production environments.

By incorporating dataPARC’s industrial analytics toolkit, Hitachi will offer manufacturers an open, scalable platform that unifies diverse data sources—from process control systems and historians to quality, maintenance, and business data—into one environment, according to a release from the companies.

Much of Tokyo-based Hitachi Systems’ business deals with IT and OT integration, and its services cover the gamut, from system design to operation and maintenance. Hitachi’s expertise resides in information technology, control systems, and industrial data solutions.

Washougal, Washington-based dataPARC provides industrial analytics software for process manufacturers worldwide, and its PARCview platform connects and contextualizes data from disparate systems. DataPARC serves customers in industries such as pulp and paper, chemicals, oil and gas, power and utilities, and mining and minerals across more than 1,000 sites globally.

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“By combining our digital transformation expertise with dataPARC’s proven industrial data and analytics technology, we can help manufacturers build a stronger data foundation for innovation,” said Masatsugu Hase, director, VP and executive officer at Hitachi.

Added Jason Myers, business director at dataPARC: “Hitachi Systems is one of Japan’s most trusted technology partners for industrial digitalization. Together, we’re providing customers with a flexible, modern platform to maximize the value of their process data and accelerate performance improvement.”