Optimize Batch Plant Performance Course

Optimize Batch Plant Performance Course2019-10-24T11:23:21-04:00

This 1-day course will teach you how to get actionable insights from your industrial batch data for process optimization and troubleshooting. You will learn how to relate time-varying process data, raw material properties and initial conditions to final product quality and productivity.

Understanding the relationships between all your different blocks of data (raw material properties, initial conditions, etc.) will enable you to improve product quality, increase yield, and reduce your operating costs. Workshops using desktop MVA software (Aspen ProMV) will provide you with practical troubleshooting experience using industrial batch process data. Where possible, attendees’ data will be used. Contact us today to obtain more information or to schedule this course.

Our attendees return to work ready to apply multivariate data analysis to their own applications. In addition, ProSensus’ highly-trained instructors can serve to propel projects forward in a consulting capacity subsequent to course-completion.

A GOOD FIT FOR: Engineers, scientists and statisticians responsible for process troubleshooting, control and optimizing batch processes in the chemical, food, semi-conductor, biotech and pharmaceutical industries.

PREREQUISITES: A first course on multivariate analysis using latent variable methods, such as ProSensus’ comprehensive course: “Optimize Plant Performance Using Multivariate Data Analysis”, or experience with using these multivariate methods in industry.

Course Content:

  • Introduction to batch processes and data structures
  • Modeling and analysis of historical batch data
  • Prediction of end-point and final batch quality
  • Multivariate monitoring (MSPC) of batch processes
  • Optimization of batch processes
  • Model-based control of batch processes

    Are you interested in attending a future ProSensus course? Register below and we will notify you of our next available course offerings.


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