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It is critical for combined cycle power plants to control costs and increase efficiency. In order to accomplish these goals, these plants must make every effort to avoid costly shutdowns, including implementing the newest innovative technologies. This white paper details how combined cycle power plants can leverage the lessons learned from other industries to capture more value from capital equipment, thereby improving operations overall.

The energy industry has been hit hard by current global economic interruptions: rapid drops in demand, a changing mix of preferred products, plummeting crude prices, difficulty staffing essential production sites and fragile supply lines. Energy companies are re-examining their digital capabilities and increasing their focus on digitalization as an essential strategy.

この記事では AspenTech AIoT platform のIoTアナリティックスが、センサや稼働中デバイス の時系列データを使用し、設備資産のAsset Health スコアをどのように算出しているかを解説します。Asset Health スコアによって、サービスチームはリアルタイムで設備資産の健全性を把握で き、サービス業務やメンテナンスにかかる費用の削減につなげることができます。

In the current extreme VUCA (volatile, uncertain, complex and ambiguous) environment, chemical producers are learning the importance of operating with insight and agility. At the same time, companies are being tested for the depth of their resilience, and learning how to navigate huge shifts in demand, supply, workforce and economics, and emerge from this crisis in a stronger position.

Small operational issues in the sulphur recovery unit (SRU) can lead to higher emisisons — or worse, a frustrating and costly shutdown. Simulation of the SRU can enable more reliable operations and fewer shutdowns through the prevention of issues and quick and effective troubleshooting. In this paper, we present three common operational issues and show how simulation was used to prevent or quickly resolve the situation.

Ron Beck speaks to the power of a model based estimating system providing insight to its attributes like reusable templates and saleable features. How does ACCE differ from my proprietary Excel-based spreadsheets?

Whether it’s a pilot plant or a complex petrochemical plant, these facilities rarely run like a well-oiled machine. There are always unknown variable dependencies that are difficult to understand, and there’s substantial room for improvement. In many situations, optimization is not the focus for plants because there are issues with reliability and safety that take precedence. Does this sound familiar? The ability to simplify job tasks and boost efficiency will greatly enhance plant performance but also, make your job easier

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.

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: