AVEVA (Schneider Electric) > Case Studies > Ascend Performance Materials Case Study

Ascend Performance Materials Case Study

AVEVA (Schneider Electric) Logo
Technology Category
  • Analytics & Modeling - Big Data Analytics
Applicable Industries
  • Plastics
Applicable Functions
  • Process Manufacturing
Use Cases
  • Process Control & Optimization
The Challenge

Ascend operations must access multiple software systems to manage day-to-day operations in an effective and secure manner. These systems generate large sets of data which contain critical information pertaining to management systems, planning and cost information in business systems and energy consumption. As a result, Ascend management was challenged with creating relevant reports reflecting performance measures in overall context of their operational process. The company’s previous process entailed collecting and analyzing data manually which was not effective, since the information collected was generated after the fact, and was too complex for collaborative use across the organization.

About The Customer
Ascend Performance Materials is the global leader in the production of Nylon 6-6.
The Customer
Ascend Performance Materials
The Solution

Wonderware Intelligence software addresses the challenges faced by Ascend to leverage the hidden insights in industrial data. The software automates the transformation of time series and transactional data across multiple sources and turns large amounts of Industrial “Big Data” into actionable metrics and Key Performance Indicator (KPI) information. Metrics and context data is kept in an open information model, providing a single version of the current data. This is stored in data warehouses and enterprise business intelligence tools enabling Ascend management to make strategic sense out of the production data. With Wonderware Workflow, companies can institutionalize work processes that manage normal, unscheduled or disruptive events within their operations environment. This industrial workflow application benefits operations, maintenance, engineering, quality, environmental & safety departments within an organization.

Data Collected
Energy Consumption Rate, Maintenance Requirements, Operation Performance, Time Series and Transactional
Operational Impact
  • [Efficiency Improvement - Operation]

    Their operators now immediately view key data generated during the manufacturing processes at each plant, which enables them to operate more efficiently.

Quantitative Benefit
  • The company achieved a savings of $500,000 in utilities and materials costs.

  • More than $1 million in savings was achieved in maintenance costs.

  • Avoided potential plant shutdowns which equals to a savings of $2 million.

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