Learn how YPFB Andina was able to increase their gas production using an integrated model solution that was able to provide a $280M increase in revenue in 1 year.

Phillips66 improves estimating productivity by 85% and reduces estimating variability to +/-15% with a five year before and after analysis of estimates vs. completed projects. Download the case study to learn more.

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.

In this case study learn how a global oil and gas company was able to detect and predict a variety of pending equipment failures. Download today to uncover how Aspen Mtell enabled the company to correctly identify all reported events – as well as unknown problems.

GlaxoSmithKline (GSK) wanted to review the structure of its batch production record and associated workflows as part of a continuous improvement process. Reducing batch review time usually results in faster batch cycle time, meaning higher throughput at the production facility and faster cash-to-cash cycle time. AspenTech was selected for this process due to integration with other solutions, such as Aspen InfoPlus.21® and GSK’s existing plant automation software (DCS). The pilot project was a resounding success, reducing order preparation time by 95% and record review time by over 50%.

When developing its highly successful digital transformation program, a leading European energy company turned to Aspen Mtell® for predictive maintenance. After deploying Aspen Mtell on more than 50 large assets in a refinery, the company began testing the technology at a wind farm and had five early successes in predicting gear box failures.

Engineering, Procurement and Construction firms (EPCs) are facing the challenge of fewer and smaller projects out for bid, and win rates are critical for their future success. This executive brief provides the winning combination of industry best practices and software that will allow you to create accurate bids, reduce risk and be more responsive to the changing needs of your customers.

意外停机影响广泛，所波及的不仅仅是工厂的生产率和盈利能力。强制关机还会对工厂和人员安全、温室气体排放和环境合规产生重大影响。但是，如果你真的可以计划停机时间呢？在本文中，我们将了解机器学习和预测分析的进步如何消除意外停机，使公司最大限度地减少最危险的情况，减少排放到环境中的气体量，提高生产率和盈利能力。

전세계적으로 시장 상황의 변동성과 불확실성, 복잡성과 모호함이 가중되고 있는 VUCA (Volatile, Uncertain, Complex and Ambiguous) 환경에서 기업들은 경쟁 우위를 확보하기 위해 Industry 4.0과 AI 등 새로운 기술들을 도입하고 있습니다. 이 백서에서 선도적인 기업들이 어떻게 디지털 엔터프라이즈를 뛰어 넘어, 진정한 의미의 미래형 스마트 엔터프라이즈로 거듭나고, 지속 가능한 운영 효율성을 달성할 수 있는지 확인해 보십시오.

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