Fluor Achieves Significant Time Savings in SRU Simulation
Fluor uses Aspen HYSYS to evaluate different configurations of oxygen enrichment in the reactor model, with empirical correlations built in for more accurate modeling. AspenTech’s solution for SRU optimization allows users to increase production, reduce OPEX and meet emissions regulations by modeling the complexities of the SRU and the full gas plant.
Shell Adopts Global Supply Chain Process to Increase Profitability and Drive an “Enterprise First” Strategy
After the company identified uncommon operating procedures at each of its many refineries — which led to inefficiencies and lower margins — Shell launched “Enterprise First,” an initiative designed to standardize processes and technology across the organization. The key to driving this strategy — and meeting its objectives — is an integrated aspenONE® Supply Chain Management solution that helps Shell optimize refinery production, reduce costs and increase margin.
Oxiteno Plant Operations Reacts Quickly to Market Demand
Oxiteno has used the aspenONE® Engineering suite extensively over the past 25 years to modify and optimize current units, as well as design new units with complex configurations. Learn more.
US Railway Saves Millions by Preventing Line of Road Failures
A major transportation company responsible for delivering customer goods on time, safely and reliably, was plagued by catastrophic failures of locomotives that had gone undetected by its current reliability techniques. Using Aspen Mtell to examine data from engine lube oil samples, a leading U.S. railway was able to save millions of dollars.
Liquid Light Achieves Process Simplification and Reduces Costs
In order to meet their design need of maintaining a 25% cost advantage over conventional chemical processes, the engineers at Liquid Light needed a flexible software solution to find key property data (even for non-ideal and electrolyte systems), conduct “what-if” and case analyses, model reaction systems, select solvents, and scale-up quickly and reliably. Leveraging Aspen Plus and Aspen Properties, the members of Liquid Light have been able to make meaningful predictions about system behavior, moving them closer to full scale production.
From Reactive to Proactive: Machine Learning Drives Better Business Outcomes
In this case study, learn how Aspen Mtell's predictive maintenance technology was used to deliver 27 days of advance warning of a central valve failure at a specialty plastics plant.
Braskem Implements Aspen DMC3 to Deploy Controllers in Just Two Weeks and Immediately Accrues Benefits
Braskem is the largest petrochemical company in Latin America, the leading producer of polypropylene in the United States, and the eighth-largest resin producer worldwide. Braskem used Adaptive Process Control within Aspen DMC3 to deploy controllers in just two weeks to start accruing benefits immediately. The benefits included lowered energy usage by 20%, increased production rates and reduced process variability. Download this case study today to learn more about the benefits Braskem realized by using Aspen DMC3 and discover how to achieve these benefits at your organization.
Aspen Mtell® Machine Learning Finds Cause of Compressor Failures at LNG Facility
Read how this LNG facility used Aspen Mtell prescriptive maintenance to provide up to 61 days advance notice of catastrophic compressor failures, preventing an economic loss of more than $40M USD per occurrence. Quick to implement and readily scalable, the solution provided key insights into the root cause of the failures.
Multivariate Statistical Analysis Finds the Bad Actors in Out-of-Spec Batches
Learn how a large producer of synthetic rubber used Aspen ProMV to identify the cause of ongoing quality issues with its batch products. Download the case study to read how Aspen ProMV uncovered the variables that correlated most with batch quality, resolving production problems faster to limit losses.
Case Study: Prescriptive Maintenance Software Helps Saras Improve Business Performance and Drive Operational Excellence
As part of an effort to drive reliability in its refinery operations, Saras turned to Aspen Mtell prescriptive maintenance to improve equipment uptime and decrease maintenance costs. Learn how Saras executed a project within weeks that predicted equipment failures up to 45 days in advance using prescriptive analytics, and enabled the company to increase revenue and cut operating expenses.