How Data Reveals the Culprits Impacting Food Production Quality
For food and beverage companies, quality mishaps during production can mean more than a literal poor taste in a customer's mouth. In addition to the potential impact on consumer safety, quality lapses can slow down production and result in money down the drain.
Working In Silos
In the Pharma Times article “Working in Silos” AspenTech’s Justin Eames discusses the pitfalls of working in silos in the pharmaceutical industry and explains how AspenTech’s solutions can make an impact at speed using predictive analytics. Discover how to predict asset degradation and failure well in advance of an impending breakdown or disruption and gain the ability to make decisions that can not only minimize cost and disruption, but that can also protect public health by ensuring continuity and resulting quality of drug supply.
Blacks Swans and Gray Rhinos: Building Future Resilience
As all companies have been challenged by the current economic and health crisis, the successful recovery requires a new view toward future development and growth with metrics that consider broad and more long-term goals. Featured in Hydrocarbon Processing, AspenTech’s Paige Morse shares considerations for building future resiliency that center around digitalization.
How Digitalization and Industrial AI are Accelerating Sustainability
The 2015 Paris Agreement and other international climate change accords have helped raise global awareness of the need for countries to take urgent action to combat climate change. As companies continue to focus on sustainability, a common theme is taking shape around the role of digitalization as a key enabler. In fact, a recent ARC Advisory Group survey revealed that 75% of respondents rated digital transformation as highly important for achieving sustainability goals.
Digitally Enabled Reliability: Beyond Predictive Maintenance in Mining
Real-time condition-based monitoring of assets is an attractive solution for mining companies to minimize their unscheduled downtime and improve reliability of critical equipment. The success of an asset monitoring program depends on how well this data is analyzed, filtered and categorized to enable accurate predictions of impending failures. Focusing on the behavior of an asset only tells a small portion of the story. To fully predict failures, the trends of the entire process must be considered as a whole.
Efficient Plant: Use Industry 4.0 To Elevate Sustainability
In this article, AspenTech's Paige Marie Morse delves into how digital-transformation technologies can help industrial organizations cut energy costs while reducing environmental impact. Download now to discover how AI and machine-learning technology combined can enable companies to predict asset malfunctions well in advance and have positive financial and sustainable results.
When Lightning Strikes Twice
After an electrical storm stopped gas production at one of its plants, SABIC executives and reliability engineers turned to Aspen Fidelis Reliability to calculate the probability of it—or a similarly debilitating event—happening again. Read this article from Plant Services to learn more.
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