Watch how Aspen Mtell analyzed 220 million sensor values to identify the top 10 maintenance cost failures at one world-class refinery, and predicted a compressor breakdown 49 days in advance.

Aspen Mtell은 에이전트를 통해 설비 자산의 고장을 사전에 정확히 감지하여 비계획 가동중단으로 인해 발생되는 문제들을 없애는 솔루션입니다. 이 비디오는 에이전트가 무엇인지, 어떤 역할을 하는지, 어떻게 생성되는지, 이를 통해 궁극적으로 공장의 설비와 인력, 그리고 환경을 어떻게 보호하는지 알기 쉽게 보여드립니다.

Aspen Mtellは、エージェントを使用してアセットの障害をより早く正確に認識する処方的メンテナンスソリューションです。 このビデオでは、エージェントとは何か、何をするのか、どのように作成されるのか、どのように機能するのかをご覧いただけます。

Understand how Aspen Mtell’s Autonomous Agents share failure signatures across similar assets, enabling rapid time to value.

Learn how Aspen Mtell connects big data and prescriptive maintenance to deliver IIoT solutions.

What if all your data could easily provide strategic insights to your users across your entire enterprise? That's Aspen Enterprise insights, the first hybrid cloud visualization and workflow management solution that brings new levels of performance to operations and capital projects.

A customer case study of the use of Aspen HYSYS, PSV in Aspen HYSYS, dynamic modeling and flare to achieve lower CAPEX solutions and rapidly conduct safety studies for refining.

Over the past 40 years, maintenance best practices have greatly improved, but equipment continues to break down. So how can asset reliability be improved? With Aspen Mtell prescriptive maintenance software, you can predict breakdowns weeks in advance and take action to protect your machines, business investments, the environment, and most importantly, people.

Maintaining optimal inventory levels to achieve outstanding customer service sounds simple enough, but the timing of customer shipments can have a huge impact on plant storage tank inventory levels.

In just a few minutes, a scheduler can simulate the addition of a last minute customer order, determine its impact, and modify the production schedule to resolve any issues and fulfill last minute orders using Aspen Plant Scheduler.