AspenTech Industrial AI™는 공정 산업의 판도를 바꾸는 기술로서 AI 알고리즘의 속도와 성능에 실제 도메인 전문 지식의 효율성과 매개변수를 결합하였습니다. 특수 목적에 맞게 설계된 아스펜테크의 AI 솔루션은 데이터 인사이트, 엔지니어링 기반기술, 공정자산에 대한 지식 및 산업에 특화된 전문 지식을 결합하여 고객 기업이 끊임없이 변화하는 비즈니스 요구 사항에 더 빠르게 적응하고 대응할 수 있도록 지원합니다.

Upgrading automation, digital and data infrastructure has become essential for chemical companies seeking long-term growth and competitiveness.

AspenTech Industrial AI™ is a game-changing technology for the process industries, combining the speed and power of AI algorithms with the efficiency and parameters of real-world domain expertise. Our purpose-built AI solutions bring together data insights, engineering fundamentals, asset knowledge and industry expertise, enabling companies to adapt and respond quicker to ever-changing business needs.

Bio-based feedstocks play an important role in creating a circular economy. Making biofuel or chemicals from biofeedstocks typically has a lower carbon footprint than the fossil fuel-based processes. Therefore, transforming biofeedstocks is considered as one of the energy transition pillars. Despite sustainability advantages, many chemical and polymer makers have been reluctant to actively pursue large-scale use of biofeedstocks mainly due to economics and process complexities.

Capital project owners need to optimize their CAPEX spending throughout the lifecycle of their projects, from design to operations.

Leading asset-intensive companies are using prescriptive maintenance—powered by AI and machine learning—to unlock the value and productivity lying uncaptured in assets. Using a scalable, easy to implement prescriptive maintenance solution, companies can improve the accuracy of failure detection, increase the advance notification period of asset downtime events and reduce maintenance spend.

As sustainability targets drive the energy industry towards a net zero future and energy security concerns intensify, companies are challenged to meet these competing demands within financial and workforce restraints. Owners and EPCs must cater to short-term energy demands while simultaneously positioning themselves for the long-term energy transition projects gaining traction.

Chemical manufacturers are facing a dual challenge with global demand increasing. On one hand, chemical production has to increase to address the growing demands of a growing global population. On the other hand, the industry is facing a climate and an environmental crisis.

Discover how to predict equipment breakdowns and perform prescriptive maintenance using a new approach to asset performance management. In this white paper, learn how nine early adopters of prescriptive analytics have reduced unplanned downtime and improved asset reliability. Download the paper to read real stories about the bottom-line results that have been achieved—in as little as 2 ½ weeks.

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。