White Paper

Low-Touch Machine Learning is Fulfilling the Promise of Asset Performance Management

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.

White Paper

Low-Touch Machine Learning is Fulfilling the Promise of Asset Performance Management

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. This white paper describes five best practices for driving state-of-the-art reliability management to predict breakdowns months in advance—increasing production and profitability.

White Paper

低接触式机器学习助力实现资产绩效管理

单独的传统预防型维护无法解决非预期停机问题。凭借低接触式机器学习所驱动的资产绩效管理,现在可能会从数十种程序、资产和维护数据中抽取相关数值,从而优化资产绩效。在本白皮书中,将学习这种插断性技术如何部署精确性故障模式识别,其具有较高的准确性,可以提前预测设备停机月数,并就约定的维护提供相关建议。本白皮书亦列述了驱动先进可靠性管理的五个最佳实践,以期增产提盈。

White Paper

資料:手軽な機械学習が資産パフォーマンス管理(APM)の可能性を開く(日本語)

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。

White Paper

Low-Touch Machine Learning is Fulfilling the Promise of Asset Performance Management

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.

White Paper

Making Capital Project Management Decisions: Minimize Risk, Maximize Profitability

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.

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デジタルツインとスマートエンタープライズ

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。

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Manufacturing Cost Competitiveness in Commodity Chemicals: Five Essential Principles for Emerging Market Producers

All chemical facilities have opportunities to reduce manufacturing costs, including newer, state-of-the art plants, older plants and those in between. Leading global producers have demonstrated reduced energy consumption, increased yield and higher reliability by simply improving operational practices through the application of advanced technology.

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Maximize Mining Equipment Effectiveness, Minimize Margin Loss

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:

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Maximice la efectividad de sus equipos mineros y minimice las pérdidas de beneficios

Las compañías mineras invierten fuertemente en activos para todas las etapas del proceso minero: extracción, procesamiento, refinería y distribución del mineral. Al monitorear la condición y el comportamiento de los activos y desarrollar perfiles de operaciones normales, anomalías y fallas, las herramientas de mantenimiento predictivo pueden notificar al personal sobre los problemas del equipo antes de que ocurra falla. Este documento describe cómo el mantenimiento predictivo proporciona a las organizaciones mineras la inteligencia necesaria para:

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