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.

When this large energy company launched its digital transformation initiative, it turned to Aspen Mtell® to execute an online predictive maintenance pilot on a hydrogen compressor.

Shell Oil Company is a global energy and petrochemicals company that produces natural gas, gasoline, oil, and many bulk and specialty chemical products for customers worldwide. Read this case study to learn how Shell’s Manufacturing Margin Optimization team uses AspenTech solutions and AWS Cloud to optimize its energy and petrochemicals business, including planning and scheduling applications.

Start your journey to the self-optimizing plant and view this interactive e-book that highlights how your assets can be safer, more reliable, more flexible and more profitable.

Lea cómo esta compañía minera utilizó Aspen Mtell para predecir dos posibles fallas cuando se implementó en 12 activos durante un breve piloto en línea. Permitiendo así, un tiempo de inactividad planificado de equipos críticos, ahorrando dinero por cortes inesperados.

Learn how SK Engineering & Construction improved the speed and accuracy of their capital project cost estimates with Aspen Capital Cost Estimator (ACCE).

ケノス社がAspen Plus®バッチモデリングを活用し、プロセスにおいてどのように利益を確保し、試運転、試作をほとんど行わず、顧客ニーズの変更に対応できたかをご説明しています。日本語の事例カタログです。

Learn how Borealis, a leading provider of innovative solutions in the fields of polyolefins, base chemicals and fertilizers, implemented Aspen PIMS-AO to support the optimization team and bring about better decision-making for more profitable results. This case study explores how Borealis achieved dramatically faster run time, employed nonlinear modeling, deployed planning models to a centralized, virtual environment, and eased software deployment time and maintenance with more efficient use of hardware.

ケノス社がAspen Plus®バッチモデリングを活用し、プロセスにおいてどのように利益を確保し、試運転、試作をほとんど行わず、顧客ニーズの変更に対応できたかをご説明しています。日本語の事例カタログです。

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.