Problem
Amidst escalating demand, a renowned global manufacturer of contrast media faced critical capacity limitations, jeopardizing their ability to meet market demand. The production process was hindered by a significant 17% rate of unplanned downtime in their preparation and filling lines, limiting the continuity of customer supply. This downtime not only affected the direct application of contrast media for imaging and therapies, but also impacted the preparation of other crucial drug products. The absence of real-time alerts and guidance for operational transitions further exacerbated these challenges, requiring a solution that could streamline processes and mitigate inefficiencies.
Solution
In response to these challenges, we implemented a comprehensive AI-driven approach with Aizon, providing a step-change in the manufacturer's operational framework. We deployed several predictive AI models in real-time and tailored them to key aspects of the production process including product characteristics, packaging formats, and material origins. The operational personnel were given proactive guidance of optimal phase transfer time windows, as well as required resourcing ahead of time. These models were also designed to predict and pinpoint potential issues such as stops and slowdowns, effectively reducing waste and enhancing overall efficiency.
Result
The transformative power of Aizon's technology recuperated lost operational time and increased the manufacturer's capacity by an impressive 12.3%, translating into millions of vials per year. Furthermore, our solution drastically cut manpower wait times by approximately 15%, streamlining the fill-finish environment where continuous oversight is impractical. The AI models served as a proactive alert system, advising when to initiate the next phase or adjust operations, thereby facilitating a smoother production flow.
This strategic integration of AI models into the manufacturer's processes increased their capacity and reduced the waste, making the manufacturer's production lines not just reactive but proactively responsive to emerging challenges. How do you see AI transforming manufacturing processes within your company to effortlessly overcome operational challenges?
