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.

現在のVUCA環境において、新たなレベルの安全性、持続可能性、および収益性を実現する自律／半自律プロセスの開発のために、デジタライゼーションやAIに目を向ける企業が増えています。自己最適化プラントへのジャーニーはそこから始まります。自己最適化プラントがどのようにして以下のことを可能にするのか、是非このエグゼクティブブリーフでご覧ください。

Alors que nous nous adaptons à la "nouvelle norme" de volatilité extrême, d'incertitude, de complexité et d'ambiguïté, les entreprises du monde entier reconnaissent la nécessité d'exploiter leurs actifs et leurs chaînes de distribution avec une plus grande résilience, flexibilité et agilité afin de pouvoir répondre aux conditions changeantes du marché.

A specialty plastics plant needed a solution to reduce downtime on a problematic hypercompressor in their LDPE production process.

This petrochemical company launched an Aspen ProMV™ pilot project to investigate light component losses that go to the bottom of a fractionation column and pressurize the downstream column. Using Aspen ProMV for continuous processes, a model was developed, and bad actors that are highly correlated to the light product loss were identified. Aspen ProMV’s optimization tool was also utilized to provide better operating conditions to reduce losses.

Training moves with the times

AspenTech's Sanjeev Mullick discussed how integrated software solutions provide a collaborative platform to enable various disciplines to share data and information resulting in better quality of designs and consistency of project deliverables.

Delivering a competitive edge to chemical companies

Empowerment through IT enabled solutions

Enhancing production, maximizing profitability