White Paper: Seeing Into the Future With Prescriptive Analytics
Discover how to predict equipment breakdowns and perform prescriptive maintenance using a new approach to asset performance management. In this white paper, learn how nine early adopters of prescriptive analytics have reduced unplanned downtime and improved asset reliability. Download the paper to read real stories about the bottom-line results that have been achieved—in as little as 2 ½ weeks.
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.
Use Advanced Simulation to Improve Processes Involving Solids
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.
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.
Accelerate New Product Development in Chemicals
Understanding how different variations to raw materials, recipes and operating conditions influence product outcomes can present a fast track to new product development for chemical companies. Download this whitepaper to learn how Aspen ProMV can reduce R&D time in the following ways:
Use Existing Data and Resources to Speed Up New Food and Beverage Product Launches
What role can digitalization play in new product development and increasing your competitive advantage in the food and beverage industry?
In this White Paper discover how Aspen ProMV can identify a simple process change to help your company create your newest product. ProMV helps make sense of the data available by the people most familiar with the process without requiring new resources. Additionally, ProMV increases the speed of new product development and shortens the time to market.
Prescriptive Maintenance: Transforming Asset Performance Management
Prescriptive maintenance technology is transforming how companies manage asset downtime. With more advance warning of equipment failures comes more opportunity to mitigate the negative impact of those events.