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.

How data, machine learning can power energy sector

How chemicals companies can drive operational resilience with the digital twin

Learn how one of world’s largest multinational energy companies used Aspen GDOT to maximize production of specific diesel and jet fuel products at one of its refineries. By using real-time optimization across multiple APC units, the refinery was able to decrease sulfur giveaway by 70%. Download this case study to learn how you can optimize production and reduce product giveaway.

Advanced planning, optimum results

Qenos 사가 Aspen Plus®의 회분식 모델링을 어떻게 자사의 공정에 적용하여 변화하는 고객의 요구에 맞춰 플랜트 검증 단계를 최소화하고, 고객 맞춤형 제품을 신속하게 시장에 공급할 수 있었는지 실제 사례를 소개합니다.

Forbes-The Self-Optimizing Plant is Within Reach

Learn how SES, one of the leading estimating organizations worldwide, saves 70% manhours using ACCE. SES is responsible for, estimating projects such as SADARA, Suncor Tar Sands, and Mozambique LNG using ACCE.

This article examines three applications where rigorous heat exchanger models can boost value derived from process simulation and provide more accurate results.

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.