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.
White Paper: Beyond Oil Digitalization-The Roadmap to Upstream Profitability
This paper discusses digital transformation in the oil patch. It explores how upstream industry leaders are capitalizing on the explosion of data and how, in particular, merging rigorous process models with both analytics and data visualization can help achieve a competitive advantage. It also reveals how innovations from AspenTech are helping to lead the way toward asset reliability and profitability.
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:
Pushing the Reliability Envelope: Digital Optimization for the “Always On” Refinery
AspenTech conducted a survey of 240 downstream customers to uncover thoughts and opinions on digital optimization and industry trends for 2018 and beyond. This white paper details the results of the survey and provides the reader with insights on the focus of increased reliability, a top priority for many refinery organizations.
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.
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.
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.
Process Plant Design: The High Cost of Slow Decisions
Risk analysis is generally performed in the later stages of design to prove that the plant will deliver what it’s supposed to. However, some clever practitioners are now employing it much earlier to speed up decision-making and lock in superior design choices when they really matter at the beginning of the project. In this paper, learn how Aspen Fidelis Reliability uses a systems approach that allows you to quantify the true value or cost of any design or improvement project, maintenance change, operations improvement or supply chain constraint.