April 25, 2017
Technology, Inc. (NASDAQ: AZPN), the asset optimization software company, today marked its commitment to continued industry
innovation and transformation at OPTIMIZE™ 2017.
At the company’s biennial customer event, top leaders and experts discussed AspenTech’s
groundbreaking innovations that are helping companies in complex, industrial
environments increase reliability and build sustainable competitive advantage
by delivering high returns over the entire design, operate and maintain asset lifecycle.
AspenTech’s Asset Performance Management track sessions at OPTIMIZE 2017 showcase how the company’s execution of its asset optimization strategy is delivering significant value and sustainable performance improvements. Leading global chemical firms EQUATE Petrochemical Company, Evonik Industries and INVISTA will share their objectives, achievements and plans for asset analytics, root cause analysis, pattern matching and machine-learning in a customer panel moderated by ARC Advisory Group.
Additional customer success presentations include The Dow Chemical Company’s use of Aspen Fidelis Reliability software to quantify significant value creation opportunities, and Evonik’s successful industrial test case using AspenTech root cause analytics capabilities to identify sources of process disruptions. An Aspen Mtell® software predictive analytics success story highlights the reliability improvements achieved by CSX Railroad Mechanical.
AspenTech’s 35-plus years of process modeling expertise, combined with big data machine-learning, help predict and address the root causes of process induced equipment failures causing over 80 percent of unplanned downtime, allowing the most critical industrial assets to run as closely as possible to their performance limits. The aspenONE® Asset Performance Management™ suite expands the aspenONE portfolio from engineering, manufacturing & supply chain into maintenance and operations to address key business challenges that include process disruptions, low asset availability and unplanned downtime, enabling companies to optimize throughout the entire asset lifecycle.
Antonio Pietri, Chief Executive Officer & President, AspenTech
“We are pleased to present the continued execution of AspenTech’s Asset Optimization strategy, announced at OPTIMIZE 2015 and made a reality at OPTIMIZE 2017. Together, AspenTech and global leaders in complex, capital-intensive industrial environments will extend optimization’s reach by pushing the boundaries of what is possible in design, running to the limits of performance in operations, and maximizing uptime with actionable insights into the maintenance management lifecycle.”
Peter Reynolds, Senior Analyst, ARC Advisory Group
“An essential ingredient for industrial transformation is the application of machine learning and predictive analytics to help improve plant uptime and asset availability.The next wave of improvements in asset performance will be led by innovations to operational and process engineering, and process optimization, and provided by domain experts with deep knowledge of the process, and the assets, and the systemic interaction between the two areas.”
AspenTech is a leading software supplier for optimizing asset performance. Our products thrive in complex, industrial environments where it is critical to optimize the asset design, operation and maintenance lifecycle. AspenTech uniquely combines decades of process modeling expertise with big data machine-learning. Our purpose-built software platform automates knowledge work and builds sustainable competitive advantage by delivering high returns over the entire asset lifecycle. As a result, companies in capital-intensive industries can maximize uptime and push the limits of performance, running their assets faster, safer, longer and greener. Visit AspenTech.com to find out more.
© 2017 Aspen Technology, Inc. AspenTech, aspenONE, the Aspen leaf logo, Aspen Fidelis Reliability, Aspen Mtell and OPTIMIZE are trademarks of Aspen Technology, Inc. All rights reserved. All other trademarks are property of their respective owners.