Smart Manufacturing for Chemical Processing: Energy Efficient Operation of Air Separation Unit
Project Lead: Texas A&M Engineering Experiment Station (TEES)
Partners: Praxair, Process Systems Enterprise, AspenTech, OSISoft, Rensselaer Polytechnic Institute, University of Texas Austin
Member % Cost Share: 42%
CESMII % Cost Share: 58%
Duration: 24 Months
Problem Statement
An Air Separation Unit (ASU) is a complex and energy intensive process for chemical industries. Sub-optimal performance of these processes result in a loss of energy efficiency. For Praxair in the US, each 1% in operating efficiency is worth about $10 M/yr.
Project Goal
The goal of this project is to develop a number of SM Platform™ ready tools and deploy them on Praxair’s commercial Air Separation Unit for improving energy efficiency.
Technical Approach
Create data acquisition tools, asset templates and predictive tools for the air separation units and demonstrate their application in an integrated environment.
Key Tasks & Milestones
- Develop data model templates for the air separation unit for data acquisition and modeling & control environments
- Implement a coupled on-premise & cloud historian system to collect plant data for analysis in the cloud
- Develop steady state, dynamic, control oriented, planning and scheduling models for ASU
- Develop data models for individual assets for integration into a Remote Asset Management workflow
- Develop analysis tools for the efficient monitoring and operation of the Air Separation Unit
- Validate analysis tools through field testing on an air separation unit at Praxair
Potential Impact
Increase in operating efficiencies of Air Separation Units estimated at $10M/yr. for one large manufacturer, with potentially similar impact to other manufacturers with similar ASUs Contributes to CESMII’s energy reduction and energy productivity goals
Benefits
- Data templates, models, analytics tools available to other members with similar processes through the SM Platform™
- Contribution to the SM Platform™ core technologies (data acquisition, contextualization and apps)
Project Selection & Announcements
