従来の対処的メンテナンスだけでは、不測の事態に対応できません。手軽な機械学習による資産パフォーマンス管理(APM) により、今や製造工場のスタッフが、何十年にもわたって蓄積してきた設計や運用データから容易に価値を引き出し、資産（主に装置などのハードウェア）のパフォーマンスをより適切に管理して最適化することが可能になりました。本書では、常識を覆すような画期的なテクノロジーがどのように精密な故障パターン認識を使い、高精度に装置の故障を数ヶ月も前に予測し、処方的なメンテナンスをガイダンスするかを説明しています。また、５つのベストプラクティス（運用方法）をご紹介し、最先端の信頼性管理による、さらなる生産効率および利益率の改善手法について述べています。

Mining companies invest heavily in equipment for all stages of mining, mineral processing, refining and distribution. By monitoring asset condition and behavior and developing profiles of normal operations, anomalies and failures, predictive maintenance tools can notify staff of equipment problems prior to failure. This paper outlines how predictive maintenance provides mining organizations the intelligence needed to:

下载白皮书了解如何为化工厂建模，以提高绩效：

在白皮书里，我们探讨了如何改善炼油和石化公用事业系统运营，以提高能源效率、减少排放和提高灵活性。

A AspenTech® desenvolveu um método para integrar modelos fenomenológicos de simulação de processos e o conhecimento do processo com IA e algoritmos de analytics. O resultado é um sistema de modelagem híbrida que oferece um modelo abrangente e preciso mais rapidamente sem exigir uma experiência significativa.

AspenTech’s Performance Engineering Solutions can help improve engineering productivity and collaboration. Download this white paper to learn how you can leverage concurrent process engineering and lifecycle project economics to be more agile in bidding, project execution and handover of digital project data to your customer.

AspenTech® ha inventado un método para integrar modelos de simulación de procesos basados en primeros principios con el conocimiento en operación y algoritmos analíticos de IA. El software resultante de ello es un sistema de modelado híbrido que ofrece un modelo completo y preciso de forma más rápida sin necesidad de una experiencia significativa.

Achieve savings in both engineering hours and CAPEX with modular design through the use of stanadardized designs in re-useable templates.

Multiphase flow through pipes is characterized by the flow regime, liquid hold-up and pressure gradient. Accurate prediction of these flow attributes is necessary for designing and maintaining pipelines and flowlines in the oil and gas industry. Aspen HYSYS provides a number of flow correlations for modeling multiphase pipe flow. To aid the user and provide a basis for comparison, the performance of correlations for different pipeline geometries, fluids, and flow regimes was analyzed. This paper discusses these analyses.

With downstream margins globally close to a 10-year low, according to S&P Global Platts Analytics and ExxonMobil, companies need to find new areas for improvement. Current digital solutions offer ways plants can move beyond mechanical and equipment investments to drive greater profits. Download this white paper that outlines high impact operational improvements that deliver immediate results.