Improving Drug Manufacturing Reliability and Performance

Challenge

A global pharmaceutical company produces, distributes, and markets 40 distinct drugs to over 120 million patients annually. The company’s top priority is to ensure patients receive uninterrupted supplies of therapy, which requires minimizing manufacturing production delays.

In the company’s largest biologics manufacturing plant, 100+ distinct systems must operate continuously and seamlessly throughout a two-month cycle to produce a single batch of drugs. An unanticipated system failure may compromise the drug quality and lead to scrapped batches or production delays. Lost revenue from unanticipated system failures can amount to $40,000 – $70,000 per hour at this single plant, or up to over $50 million per year depending on the severity of the delays.

Approach

Prior to engaging C3 AI, the company lacked an effective approach to anticipate and prevent system failures. The C3 AI® team implemented and configured the C3 AI Reliability application to predict system failures in the company’s largest biologics manufacturing plant with $3 billion annual revenues. With C3 AI Reliability, the company can monitor system health and performance across the plant, anticipate failures up to 10 days in advance, take preventative action, and increase throughput by decreasing production delays and scrapped batches.

Solution Architecture

Enterprise AI for Manufacturing

The C3 AI Platform provides the necessary comprehensive capabilities to build enterprise-scale AI applications 18-26x faster than alternative approaches. The C3 AI Platform enables manufacturers to rapidly integrate petabyte-scale data from any/all enterprise systems, operational sources, sensor networks, and external providers to power machine learning models that generate predictive insights to solve previously unsolvable problems.

Many global manufacturers are already using the C3 AI Platform to drive digital transformation efforts, generating results such as: reducing inventory by as much as 35%, lowering waste caused by quality defects by over 20%, and generating hundreds of millions of dollars in economic value annually.

Proven results in weeks, not years

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