One Batch to Rule Them All: Golden Batch Monitoring with Exalens

What is Golden Batch?

In discrete or batch manufacturing processes, the term “golden batch” is often used to describe the ideal production batch against which all other batches are compared. That is, it serves as a benchmark or standard for comparing subsequent production batches, where production output and corresponding process execution represent the ideal conditions for batch production. By analysing and replicating the conditions under which a golden batch was produced, factory operators can aim to consistently achieve optimal production conditions in future runs.

What does it require?

In practice, golden batch manufacturing relies on advanced data collection, analytics, and process monitoring to compare real-time production runs against the golden standard. It also requires technology that can build a context-rich digital twin of your production so that all aspects of golden batch production can be captured and analysed. So that even if the most subtle deviations occur, adjustments can be made promptly to bring the process back in line with the desired outcomes. However, this requires more than relying on traditional condition monitoring technology or retrospective statistical process control analysis – it requires monitoring technology that can intelligently model your production process to find hidden patterns in your production process, your “hidden factory” if you will, that may lead to future production bottlenecks, execution latency and process variable drift.

How Exalens helps?

Exalens' self-learning digital twin anomaly detection and process monitoring aligns seamlessly with golden batch manufacturing. During baselining, Exalens digital twin models automatically generate a dynamic, time-based profile of the measurement values that were recorded and analysed for a particular batch that met product quality and performance targets.During live process monitoring, this ensures that any deviations from the ideal batch are swiftly identified so that they can be proactively corrected in real time, helping manufacturers maintain consistency and efficiency across their operations.

Exalens digital twin metrics for a golden batch baseline provide an intuitive visualisation breakdown of ideal process execution conditions between production states and process variables (see screenshot below).

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Once deployed to live batch monitoring, Exalens baselines provide highly precision detection of anomalous production conditions and pinpoints the "needle in the haystack" affecting golden batch quality requirements (see screenshot):

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With Exalens’ proactive golden batch baseline and monitoring, factory managers and operators can realise key benefits that enhance product quality and OEE objectives:

• Improved quality control: By continuously comparing current production to the golden batch baseline based on Exalens’ digital twin models, manufacturers can ensure consistent product quality and identify when there are deviations from the required production quality criteria.

• Reduce process variability: By applying process baselines that help operators spot and act on process bottlenecks and root causes in real time. Thus, helping to minimize undesirable process variability leading to more reliable and predictable production output.

• Enhanced efficiency: Manufacturers can optimize their processes by identifying ideal conditions for production, highlighting what worked best in the golden batch, thus reducing scraps, and downtime and enhancing yield.

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For industries like pharmaceutical, food and beverage, and chemical manufacturing, golden batch is a key production methodology, where consistency and quality are critical to product safety and performance. With Exalens, batch manufacturers can implement golden batch monitoring efficiently at pace, proactively optimise their batch against ideal process conditions and achieve consistently high-quality results in production output.