List of Aspen Mtell Customers
Aspen Technology
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United States
Bedford, 1730, MA,
United States
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Professional Services
3900
$1.1B
Since 2010, our global team of researchers has been studying Aspen Mtell customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Aspen Mtell for Asset Performance Management from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Aspen Mtell for Asset Performance Management include: CSX, a United States based Government organisation with 23000 employees and revenues of $14.70 billion, IRPC PLC, a Thailand based Oil, Gas and Chemicals organisation with 5250 employees and revenues of $7.69 billion, China National Bluestar, a China based OIl, Gas and Chemicals organisation with 10000 employees and revenues of $7.00 billion, Evolution Mining, Ltd., a Australia based Oil, Gas and Chemicals organisation with 2500 employees and revenues of $2.16 billion, Borealis Group, a Sweden based Oil, Gas and Chemicals organisation with 550 employees and revenues of $300.0 million and many others.
Contact us if you need a completed and verified list of companies using Aspen Mtell, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Aspen Mtell customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Borealis Group | Oil, Gas and Chemicals | 550 | $300M | Sweden | AspenTech | Aspen Mtell | Asset Performance Management | 2018 | n/a |
In 2018, Borealis Group selected Aspen Mtell as its asset performance management (APM) application for a predictive maintenance proof of concept targeting a business critical compressor. The decision positioned Aspen Mtell as the APM tool to support Borealis Group operations and maintenance analytics across manufacturing functions, with the selection driven by proof of concept performance and rapid deployment capability.
The implementation of Aspen Mtell concentrated on capability modules for historical and real time data ingestion, pattern recognition, early anomaly detection, failure signature discovery and prescriptive action recommendations. Aspen Mtell was configured to mine operational and maintenance datasets to predict future failures and to surface the precise signatures that precede asset degradation, enabling automated condition monitoring and analytic workflows aligned to predictive maintenance practices.
Operational integration focused on blending process, asset and enterprise data streams rather than specific vendor point to point connectors, enabling the solution to analyze both historical logs and live telemetry from plant equipment. The initial scope covered a business critical compressor on site with an explicit option to scale the Aspen Mtell deployment system wide, and the implementation targeted business functions in operations, maintenance, safety, quality and manufacturing.
Governance followed a proof of concept to scale pathway, using the successful POC results to inform rollout sequencing and to embed automated data analysis into maintenance decision making. Borealis highlighted rapid speed of deployment, accurate early detection of asset degradation and earlier warning to mitigate unplanned downtime and minimize customer disruptions as explicit outcomes of the Aspen Mtell deployment.
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China National Bluestar | OIl, Gas and Chemicals | 10000 | $7.0B | China | AspenTech | Aspen Mtell | Asset Performance Management | 2017 | n/a |
In 2017 China National Bluestar selected AspenTech to deliver asset performance management software, implementing Aspen Mtell as the core predictive maintenance application. The Asset Performance Management initiative paired Aspen Mtell with Aspen ProMV and targeted more than ten manufacturing sites, aiming to accelerate digital transformation across operations and reliability functions. The implementation emphasized predictive failure analytics and multivariable process monitoring, using model-driven anomaly detection and root-cause identification as primary functional capabilities.
Deployment architecture centralized analytics and alerting to a site-level operations layer, enabling condition-based monitoring and standardized alert handling across chemical production units. Operational coverage focused on maintenance planning and reliability engineering workflows, with governance structured around consistent escalation procedures and phased rollout of models and monitoring rules. The configuration leveraged Aspen Mtell for early failure detection while Aspen ProMV provided process signal correlation, aligning analytics outputs to operational workpack creation and corrective action processes.
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CSX | Government | 23000 | $14.7B | United States | AspenTech | Aspen Mtell | Asset Performance Management | 2017 | n/a |
In 2017 CSX implemented Aspen Mtell as part of an Asset Performance Management initiative showcased at OPTIMIZE 2017. The deployment targeted CSX Railroad Mechanical to apply predictive analytics against equipment-driven unplanned downtime and to improve asset reliability.
Aspen Mtell was configured to deliver pattern matching, root cause analysis and machine-learning based predictive workflows, aligning with aspenONE Asset Performance Management capabilities to move engineering insights into operational maintenance. Functional emphasis included predictive alerts, anomaly detection and condition-based monitoring to support reliability engineers and mechanical maintenance planners. The implementation narrative centers on asset analytics and failure prediction as core functional modules within the Aspen Mtell deployment.
Operational governance focused on embedding Aspen Mtell outputs into maintenance work management and root cause investigation processes within CSX mechanical reliability teams. The Aspen Mtell software predictive analytics success story presented at OPTIMIZE 2017 highlighted reliability improvements achieved by CSX Railroad Mechanical and illustrated AspenTech's broader Asset Performance Management strategy.
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Evolution Mining, Ltd. | Oil, Gas and Chemicals | 2500 | $2.2B | Australia | AspenTech | Aspen Mtell | Asset Performance Management | 2017 | n/a |
In 2017, Evolution Mining implemented Aspen Mtell as an Asset Performance Management application at its Mungari Gold Operations in Western Australia. The implementation followed a rigorous offline testing approach, where Aspen Mtell was evaluated on multiple pieces of equipment across two of Evolution Mining's key assets before the decision to deploy the system in online Live mode at Mungari, aligning with the company’s Data Enabled Business Improvement DEBI program and receiving site-level operational sponsorship.
Aspen Mtell was configured to mine historical and real-time operational and maintenance data to discover precise failure signatures that precede asset degradation and breakdowns, predict future failures, and prescribe detailed corrective actions. Implemented functional capabilities included anomaly and signature detection, predictive failure forecasting, and prescriptive maintenance guidance to generate actionable recommendations for maintenance teams, consistent with Asset Performance Management workflows.
The deployment integrated with operational and maintenance data feeds, using historical maintenance records and real-time operational telemetry to train models and trigger prescriptive alerts. Operational coverage emphasized maintenance and plant operations at Mungari and the two assets used during testing, with the solution intended to inform work planning, execution, and asset availability decisions across site operations.
Governance and rollout were managed under the DEBI program through a staged validation approach from offline proof of concept to Live mode, with site-level acceptance criteria and process adjustments to embed prescriptive maintenance into existing workflows. Outcomes explicitly cited by Evolution Mining included mitigation of unplanned downtime, provision of information to support productivity improvements, and increased asset availability through the predictive and prescriptive capabilities of Aspen Mtell.
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IRPC PLC | Oil, Gas and Chemicals | 5250 | $7.7B | Thailand | AspenTech | Aspen Mtell | Asset Performance Management | 2018 | n/a |
In 2018, IRPC PLC selected Aspen Mtell software for deployment at its refinery and petrochemical plants in Rayong Province, Thailand. The deployment centers on Asset Performance Management to provide predictive and prescriptive maintenance capabilities across IRPC’s fully integrated petrochemical complex.
Aspen Mtell software was configured to deliver autonomous agent driven anomaly detection and early warning of equipment degradation and impending asset failures, while prescribing actions to avoid problems or reduce adverse consequences. Functional capabilities implemented include pattern detection in operational data, prescriptive recommendations for corrective actions, and logic to reduce false alarms so that maintenance teams receive prioritized alerts. The implementation emphasizes automated monitoring and decision support to align maintenance execution with detected failure modes.
Operational scope covers IRPC’s refinery and petrochemical plants and extends across supporting facilities within the industrial zone, including the company’s deep sea port, tank farm and power plant. The rollout targeted maintenance, reliability engineering and operations functions to increase equipment availability and embed predictive workflows into daily operations. IRPC selected Aspen Mtell to scale these Asset Performance Management practices across the industrial zone.
The Aspen Mtell deployment is positioned as part of IRPC’s 4.0 program, built around Growth, Digital and People, to adopt Industry 4.0 predictive and prescriptive maintenance best practices. IRPC stated objectives include increasing plant reliability and reducing maintenance cost, and the implementation aims to ensure critical equipment is available on demand through prescriptive maintenance and AI driven detection. The program aligns with AspenTech’s advances in AI and machine learning to weave a digital thread through operation and maintenance processes.
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Buyer Intent: Companies Evaluating Aspen Mtell
ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating Aspen Mtell. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating Aspen Mtell for Asset Performance Management include:
- BHP, a Australia based Oil, Gas and Chemicals organization with 91304 Employees
- Teck Resources Limited, a Canada based Oil, Gas and Chemicals company with 7200 Employees
- Anglo American, a United Kingdom based Oil, Gas and Chemicals organization with 55000 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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FAQ - APPS RUN THE WORLD Aspen Mtell Coverage
Aspen Mtell is a Asset Performance Management solution from AspenTech.
Companies worldwide use Aspen Mtell, from small firms to large enterprises across 21+ industries.
Organizations such as CSX, IRPC PLC, China National Bluestar, Evolution Mining, Ltd. and Borealis Group are recorded users of
Aspen Mtell for Asset Performance Management.
Companies using Aspen Mtell are most concentrated in Government, Oil, Gas and Chemicals and OIl, Gas and Chemicals, with adoption spanning over 21 industries.
Companies using Aspen Mtell are most concentrated in United States, Thailand and China, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Aspen Mtell across Americas, EMEA, and APAC.
Companies using Aspen Mtell range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 20%, large organizations with 1,001-10,000 employees - 60%, and global enterprises with 10,000+ employees - 20%.
Customers of Aspen Mtell include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified Aspen Mtell customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Asset Performance Management.