The FDA's Advanced Manufacturing Initiative Is What We Do

There is great opportunity to leverage digital technologies that improve product quality and yield, process efficiency, on-time delivery and sustainability in pharma manufacturing.

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Solution Brief: Accelerate Market Growth with New Advances in Process Analytical Technology

Pharmaceutical companies, CDMOs and CMOs continue to grapple with the tension between meeting the demand for increasingly diverse pharmaceutical products and the escalating challenges in ensuring supply, especially during periods of disruption.

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Digitalization for Pharmaceuticals: Safeguarding Product Supply by Ensuring Asset and Process Health

In the pharmaceutical industry, equipment failures, changing operating conditions and other unexpected occurrences can cause batch failures, resulting in costly production losses and disruptions to supply. So how can companies maintain the security of supply while protecting profits?

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Delivering on the Promise of Prescriptive Maintenance

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.

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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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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.

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White Paper


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。

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