In process industries, a finished product is the result of a long chain of transformations: batches of raw materials, manufacturing stages, intermediate products, storage, and blending. Knowing how to link each product to its history has become essential for several reasons:
In short, traceability is no longer just a compliance obligation: when coupled with process and quality data, it becomes the foundation for effective quality management and fact-based continuous improvement.
Two complementary concepts allow you to reconstruct a product's history.
Traceability consists of tracking a batch at every stage of its manufacturing. It works in both directions:
Genealogy goes further: it models the complete tree of relationships between batches, including when flows split, mix, or are recycled, as is common in continuous or semi-continuous processes. Each finished product thus has a map of all the transformations it has undergone.
Traceability limited to batch numbers meets regulatory requirements, but not the question "why?". When combined with process data (operating parameters, recipes, events) and quality control results (laboratory analyses, inline checks), it becomes a full-fledged quality management tool, serving four purposes:
Thanks to the OIAnalytics contextualization engine, model the structure of your processes and the material flows that pass through them. The solution automatically chains raw material batches, intermediate products, and finished products, and attaches relevant data to each: operating parameters, recipes, production events, laboratory analyses, and quality checks, regardless of their source (SCADA, MES, LIMS, ERP, operator entries).
You thus have a complete and contextualized genealogy for each batch, directly usable by your quality, production, and process teams, without the need for specific development.
Non-conformity, customer complaint, health recall: starting from the finished product in question, trace back in a few clicks to the raw material batches and intermediate products used, and view the conditions under which each step was carried out. Conversely, immediately identify all finished products derived from a suspect batch to precisely target blocks or recalls. You respond faster to your customers and authorities, with facts.
Once your baseline manufacturing conditions are established, monitor your critical parameters and quality characteristics using Statistical Process Control (SPC) tools: control charts, capability indicators, and "golden batch" comparisons. Relevant alerts notify your teams as soon as a drift occurs, before it results in non-conforming products.
Contextualized traceability data provides a solid foundation for your Lean and Six Sigma initiatives. Using OIAnalytics' advanced analytics tools and machine learning algorithms, identify the factors that influence your product quality—such as raw material quality, recipes, and operating parameters—determine optimal operating conditions, and measure the gains achieved over time.
What changed between the period when production was compliant and when it deteriorated? What do non-conforming batches have in common? OIAnalytics' visualization and analysis tools allow you to compare batches, time periods, or lines, and share findings across teams. Your problem-solving processes (8D, QRQC, root cause analysis) are thus based on reliable data rather than manual extractions.
In conclusion, structuring your production traceability and genealogy transforms a compliance requirement into a performance driver. With OIAnalytics, your teams have a complete view from raw material to finished product, along with visualization, analysis, and SPC tools to investigate faster, control their processes, and sustainably improve product quality.
