Enabling industrial companies to manage performance, quality and availability through predictive maintenance
Arrow Electronics, Inc. (NYSE:ARW) today announced it has teamed with IBM (NYSE: IBM) and National Instruments (Nasdaq: NATI) to offer a predictive maintenance suite that enables data-driven operations in factories, oil and gas plants, mines and other rugged environments.
Integrating NI’s advanced industrial monitoring devices with IBM’s analytics/AI and asset management software, the new Wireless Industrial Asset Insights IoT solution helps enable operations managers and business decision makers to detect and diagnose faults in advance and predict remaining service life.
Integration to the IBM Maximo Enterprise Asset Management and Asset Performance Management portfolio provides analytic-driven insights and enables maintenance teams to become more proactive. This means improving operations by better predicting failures and scheduling maintenance, opening work orders, creating workflows and centrally tracking maintenance activities.
The full solution can be rapidly installed in operational scenarios thanks to engineering to ensure compatibility and repeatable integration, as well as access to Arrow’s large ecosystem of pre-qualified services and IBM implementation partners.
“This unique and powerful combination of NI and IBM products creates a solution that will change the way operations are managed,” said Aiden Mitchell, vice president and general manager of IoT at Arrow. “Operations teams can make better business decisions regarding operations availability and risk, to help them improve the company bottom line from both opex and capex perspectives.”
“We are helping organizations bring powerful analytics and AI to the asset management process,” said Adriana Robinson, vice president, IBM Watson IoT. “This will enable customers to make immediate insight-driven decisions to improve operations and proactively manage asset reliability.”
The solution is available for purchase through Arrow, Arrow business partners and IBM.
