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Square Robot appoints Mark Stone to lead data strategy and advance inspection intelligence

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Picture of Anamika Talwaria

Anamika Talwaria

Editor for Tank Storage Magazine & Chair of Women in Tanks

Square Robot announced that Mark Stone, author of EEMUA 247, has joined the company as the vice president of Data and Analytics.  Stone’s appointment reflects Square Robot’s continued investment in being industry leaders in onstream robotic tank inspections, and sets the standard for statistical analysis using high density data sets. 

Stone brings Square Robot a background spanning statistical analysis of inspection data, fitness-for-service assessments, and the development of methodologies used across pressure vessels, pipelines, and storage tanks. As author of EEMUA 247, a key industry guidance document supporting the planning and evaluation of in-service robotic inspection of aboveground storage tank floors, he solidifies Square Robot’s capabilities to provide  actionable insight for operators.

‘Square Robot works with the largest storage tank owners in the world, and these clients are looking for guidance to correctly apply statistical analysis to the high resolution quantity and quality data that robotic inspection provides. Having this level of insight into tank asset integrity is new to many operators, and as part of the Square Robot team, we can be the guiding resource for statistical analysis of deep data sets,’ says Stone on joining Square Robot.

His contributions to standards and recommended practices have helped shape how operators apply statistical methods to non-intrusive inspection approaches in real-world environments. At Square Robot, Stone will focus on advancing how inspection data is analyzed and interpreted for Extreme Value Analyses (EVAs) that are completed in accordance with EEMUA 247.

Stone’s addition strengthens Square Robot’s position at the intersection of robotics, inspection, and data. As operators face increasing pressure to maintain aging infrastructure while minimizing downtime, the ability to interpret inspection data accurately and efficiently is just as important as the collection methods.

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