Use Case
Beverage Industry
Industry/ Bottling
Functionalities
#digital-twin #process-optimization #batch-tracking#quality-optimization
Root Cause Analysis and Batch Tracking for Bottling Industry
A leading producer of beers and other non-alcoholic beverages aimed to easily identify the root cause of quality issues in specific batches and track their potential impact on other batches. Additionally, they sought to use this batch tracking to optimize recipes, manage the natural variability in raw material properties, and achieve consistent product quality.
Challenge
In the bottling industry, ensuring consistent quality across all batches is a top priority. The main challenge lies in identifying the root cause of quality issues in specific batches and identifying which other batches could potentially be impacted by the same issue. This process is rooted in the natural variability in raw materials. Companies need precise adjustments to maintain stable product quality and operational efficiency.
Wizata was selected as a partner to optimize their production process through a data-driven recommendation system:
➜ Batch Root Cause Analysis
Developed an advanced analytics model to trace the origin of quality issues in specific batches by linking raw materials and production batches. This system also provides insights into how such issues might affect subsequent batches or different products in which the same raw material was used, enabling quicker corrective actions.
➜ Real-Time Quality Optimization
Implemented a dynamic process optimization tool to adjust production parameters in real time, ensuring consistent quality despite raw material variability. This approach reduces waste and minimizes downtime, while maintaining the desired product characteristics.
Approach
Wizata and the local experts worked closely to ensure that the project generated measurable ROI and business impact.
The following activities were performed:
➜ Set up of Wizata platform, hosted within customers’ Azure tenant
➜ Ingest and contextualize process, recipe, raw material and the end product data.
➜ Design and build a Batch Tracking System
➜ Use an specific ML models of the platform and produce real-time recommendations
➜ Build customized dashboards for relevant stakeholders
Outcome
The implementation brought measurable improvements across critical aspects of the producer's operations:
➜ Enhanced Batch Traceability. The advanced analytics model enabled precise identification of the root causes of quality issues within specific batches and their impact on others. This level of traceability improved decision-making, and minimized waste.
➜ Scalable and Centralized Model Management. The models are centrally managed within the Wizata platform, enabling updates across all products without high maintenance costs.
Get in touch with one of our experts
Philippe Maes
pma@wizata.com
+32 476 209 149