Working with AWS, Aspen Mtell delivers the earliest, most accurate warning of equipment failures.

Today, oil and gas provide more than 56 percent of the world’s primary energy mix (with coal, that share climbs to 83 percent).

No longer just a catch phrase, digital transformation in pharma manufacturing is more critical today than ever before — and the industry is getting on board. A recent study conducted by Axendia revealed that almost half of industry professionals surveyed are working for organizations that are actively undergoing digital transformation — a significant increase over the last two years. And the most cited reason to act? The need to make more data-driven, intelligent decisions. 

Huge increases in demand mean pulp and paper manufacturers require that their equipment run more efficiently and for longer spans of time, without the need for constant maintenance oversight.

It’s more crucial than ever to ensure high asset availability with fewer production losses. AI-powered predictive maintenance solutions help by providing early and accurate warnings of potential failures.

Veracel is an agro-industrial enterprise with an annual production of 1.1 million tons of Kraft cellulose. In 2020 they partnered with AspenTech to implement Aspen Mtell on their critical assets to improve their asset availability and utilization, reduce production losses, and decrease maintenance costs. Implementing Aspen Mtell has also allowed them to increase the collaboration between reliability, maintenance, and operations teams. Watch this video to find out how Veracel is increasing production while achieving its sustainability goals.

AspenTech has a 40-year history of innovation, building on our deep expertise in process industries worldwide to develop new solutions to meet increasingly complex industry challenges.

Aspen Fidelis is a reliability management solution that is uniquely designed to take process flows into account, and the impacts of failures and repairs on overall plant performance and revenues.

A confluence of factors like Industry 4.0, the knowledge gap and COVID-19 have created new expectations among the industrial workforce, including the need to grow and retain industrial data scientists.

With such a small number of female engineers, what can we do to encourage girls and young women to pursue careers in engineering? The answer lies in our response to diversity, equality & inclusion (DE&I).