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Entergy Nuclear to save $1 million per day with PLM software 17/09/2009
 
manufacturing business simulation PLM software US nuclear power operator Entergy Corp reckons it will be saving up to US $ 1 million per day, once it goes live with Dassault Systèmes PLM solution.

The company, which manages 10 commercial sites with a total of 12 reactors, says it will use the system for 3D digital modelling, planning and simulation, in particular, of maintenance tasks.

John Mahoney, innovations leader for Entergy's Nuclear Operations, explains that, at the company's Waterford 3 plant, near New Orleans, it successfully simulated multiple maintenance projects using the software.

He cites projects including analysing the potential impact of a fire on equipment in key areas of the plant, replacing in-core instrumentation sensor systems that monitors reactor fuel conditions, and removing and replacing a reactor coolant pump motor that weighs 57 tons.

"Harvesting the use of 3D, along with laser scanning technology, is as transformational to the engineering and project management disciplines as moving from the slide rule to calculators was in the late 1960s and early '70s," states Mahoney .

"Combining scanning and modelling with up-to-date, advanced planning allows processes that could dramatically reduce the old industry-wide steam generator replacement average of 78.5 days. In some cases that time could be reduced by nearly 20%," he adds.

Entergy implemented a combination of Dassault Systèmes technologies, including Catia for modelling the plant and Delmia to simulate project work.

Additionally, to ensure the team had accurate dimensions of the plant, Entergy used scanning and digital photogrammetry from Dassault Systèmes' partner Areva NP.

Mahoney says that Entergy plans to use Dassault's enovia PLM (product lifecycle management) software in the future for managing assets and engineering projects.

He also talks of linking project schedule activities to the 3D model, which would "provide the opportunity to continue to effectively shrink outage schedules through critical path scenario optimisation".
 
Author
Brian Tinham
 
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