APM, AI, Prescriptive maintenance, prescriptive analytics

APM and Industrial AI Bring Untapped Value to Food and Beverage Manufacturing

April 13, 2021

Traditionally, equipment maintenance has been a financial sinkhole; predictive maintenance was discussed but rarely acted upon. Yet Asset Performance Management is a missed opportunity, one which AspenTech believes can be transformative for maintenance and create great value above and beyond maintenance cost savings. 

 

No Other Industry is Better Suited for APM than Food & Beverage 

APM technology, predictive and prescriptive analytics, and artificial intelligence (AI) play a large role for the food and beverage processing industry, one of the most important sectors within industrials. In fact, no other industry is better suited for an approach that provides more lead time for critical maintenance decisions. 

McKinsey noted in its March 2018 report, McKinsey on Food Processing & Handling Ripe for Disruption, that the food and beverage processing industry had demonstrated exceptional performance, citing several key measurements including EBITA margin expansion from 5.5 percent in 2002-07 to 10.2 percent in 2011-16; efficient use of capital, with 2.7x capital turns in 2011-16 compared with 2x capital turns for industrials; and a return to growth after the financial crisis, evidenced by 4.3 percent CAGR revenue growth 2011-16 versus 0.6 percent for wider industrials.1

With such encouraging numbers, APM solutions are well-positioned to drive positive results and sustained growth for food and beverage manufacturers.

 

Not All APM Solutions Are Created Equal 

APM solutions provide the time to plan for predicted downtime with a comprehensive view of the operation, enabling plant personnel to see exactly how downtime financially effects the entire organization. It’s interesting to note, however, that predictive and prescriptive maintenance have moved from the early focus on proof-of-concept pilots to broader rollouts. The market has learned over the last few years that, while everyone claims to be using machine learning and AI, not all APM solutions are created equal.

For instance, AspenTech offers a solution that now makes it possible to extract value from decades of design and operations data to perform prescriptive maintenance and optimize asset performance. It is the most scalable approach that can be deployed across an enterprise. Unlike other approaches, failure signatures developed on one asset can often be used as identical assets across different sites, further protecting the customer from degradation and failure. 

 

Attend the Webinar Improve Asset Reliability and Predict Potential Downtime with up to 45 Day’s Notice: Driving Growth with Prescriptive Maintenance in Food & Beverage Processing

Clearly, prescriptive maintenance is a must in food and beverage processing. Join our experts to learn how you can address challenges using your existing data combined with advanced AI and machine learning solutions. 

 

  • Identify issues up 45 days in advance with a 91% pre-failure accuracy detection rate
  • Evaluate both your process and assets to provide “root cause” early warning and prescriptive guidance
  • Scale rapidly across your site to realize ROI in weeks vs. months or years
  • Reduce unplanned downtime by 20% and maintenance costs up to 5%
  • Improve asset availability by 30%
 

Discover the faster, easier way to put an end to unplanned downtime and achiever your production goals. A Q&A session will follow, so come prepared with questions.

 

Speakers: Cheryl Armand, Senior Food & Beverage Digital Consultant, Aspen Technology, Inc.
  Matthew Hurst, Food & Beverage Digital Consultant, Aspen Technology, Inc.
Q&A:           John Campbell, Senior Director, Product Management, APM, Aspen Technology, Inc.
Moderator:    Dave Fusaro, Editor-in-Chief, Food Processing

 

  

1 McKinsey & Company

 

 

 

 

 

 

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