The ability to access real-time and trending performance data for large and small assets can be transformative for industrial production companies. Machine maintenance can evolve from reactive to proactive. Companies can better gauge how assets are performing not just relative to the assets’ history in one specific facility but relative to their performance in other facilities across the country or across the world, enabling better diagnostics, trouble-shooting and decision-making. Big Data-enabled condition monitoring can help companies lower total cost of ownership for assets and run their business more efficiently. Let’s check out the Top 3 Impacts in the below slideshare:
1. Easier benchmarking of machine performance within and across facilities
“Customers are … really interested in benchmarking their own data. They don’t want to just know how their pump, drive, turbine, transformer is performing in their plant; they want to know how it compares to other customers who are using the same solution in a similar setting and with the same type of asset.” –Shawn Lyndon, senior VP of product management – data analytics, ABB
2. Better transparency – especially for global businesses
“With companies becoming more and more involved in international/global business, using cloud services is the only answer to many of the challenging questions like providing production, process, and equipment transparency beyond the limits of a single factory.”
Martin Brucherseifer, consultant product engineer, Siemens.
3. Greater on-the-fly adaptability thanks to enhanced mobility
“It’s more than untethered people – it’s untethered equipment, it’s untethered analysis points … Plants will have to leverage more of these untethered mobile technologies, and as they do, what it will mean for them is greater efficiencies and greater adaptability in the factory design and delivering agility into the next-generation factory.” –Todd Landry, corporate VP of product and market strategy, JMA Wireless

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