Aspen Fidelis enables plant managers to identify the optimum approach for improving throughput at the lowest cost. In this video, see how this powerful tool can run hundreds of event-driven Monte Carlo simulations to increase the capacity of a plant and maximize ROI.

A landmark sustainability training series to help drive PetroChina Petrochemical Research Institute’s carbon capture initiatives.

Customers share perspectives on the VUCA supply chain challenges they've been facing and how AspenTech SCM has helped them respond to this unprecedented challenging environment.

Explore use cases for managing cloud data, making that data actionable, and applying AI and ML to that data.

世界中で、主要な組織が高度なデジタル技術を採用および実装しています。デジタルトランスフォーメーションの旅は、資産集約型産業、特にエネルギーおよび化学薬品ビジネスの性質を変えるでしょう。こうした状況下では、デジタルツイン（物理的な資産の仮想化されたコピーとその運用上の動作）が重要な役割を果たします。今日アスペンテックが描くデジタルツインの重要なコンセプトは、仮想データに対して洞察とアドバイスを提供するAIの力です。本ホワイトペーパーでは、これからのデジタルツイン戦略で重要になる鍵をご覧いただけます。

Making big capital project management decisions shouldn’t be left to subjective perceptions or over-simplified analysis. Decision-makers need quantifiable, trustworthy answers to make the most profitable decisions possible. Aspen Fidelis Reliability is a robust RAM analysis tool that can handle the real-world challenges of today's process industries. In this paper, learn how Fidelis enables you to maximize the economics of business decisions and accurately predict future asset performance of the whole system.

Are you wondering how your site stacks up against those of your peers? Do you know what your Advanced Process Control (APC) Score is? Gain key insights into your APC program and find out how best to measure it against others by reading this white paper. Determining where you stand compared to your competitors is a key step toward closing your APC GAPs and improving your site’s profitability. Download this white paper and learn how you can also participate in a benchmarking survey and be a part of an exciting study!

Whether particles are being formed, reduced in size, enlarged, participating in reactions, or just being separated from a fluid stream, ignoring or poorly modeling the solids processing steps may lead to lost opportunities, including cost reductions and quality improvements. The main challenges that arise when optimizing or troubleshooting a solids process include inefficient designs due to separate modeling of fluids and solids sections, overdesign of equipment, high-energy demands, reduced yields and quality variability. Modeling the solids section of a process is important for many common processes including specialty chemicals, agrochemicals, metals and mining, pharmaceuticals, biofuels and more. This paper describes the approach for incorporating granular solids and the corresponding solids processing steps when modeling processes.

Traditional preventive maintenance alone cannot solve the problems of unexpected breakdowns. With asset performance management powered by low-touch machine learning, it’s now possible to extract value from decades of process, asset and maintenance data to optimize asset performance. In this white paper, learn how this disruptive technology deploys precise failure pattern recognition with very high accuracy to predict equipment breakdowns months in advance and advise on prescriptive maintenance. The paper also outlines five best practices for driving state-of-the-art reliability management to increase production and profitability.

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。