Industrial Analytics for Infant Cereals Production

Ensure quality, food safety, and resource efficiency in every step of infant cereals processing with TrendMiner.

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Ensure quality, food safety, and resource efficiency in every step of your process with TrendMiner.

Optimizing energy consumption in pasteurization

Pasteurizing safely on less steam

Why it’s relevant

Pasteurization requires precise temperature and steam control to ensure food safety while minimizing energy use. Fluctuations in operating conditions can increase steam consumption, reduce efficiency, and affect production performance. Finding the right balance between thermal requirements and energy efficiency helps reduce operating costs without compromising product quality.

Why TrendMiner

Analyze historical and real-time temperature, steam, and production data to identify the most energy-efficient operating conditions. Compare performance across production runs, quantify energy losses, and determine optimal operating ranges that maintain pasteurization requirements while reducing energy consumption.

Ensuring pasteurization safety and compliance

Spotting critical-limit deviations and the batches they touch

Why it’s relevant

Pasteurization must meet defined time and temperature requirements to eliminate harmful microorganisms. Deviations from these critical limits can compromise product safety and require affected batches to be investigated or rejected. Maintaining consistent conditions is essential for food safety, regulatory compliance, and product traceability.

Why TrendMiner

Monitor temperature, flow rate, and other critical process parameters to identify deviations from validated operating conditions. Contextualize events against production batches and operating standards, investigate the causes of deviations, and support faster identification of potentially affected production.

Note: TrendMiner supports process monitoring and investigation; it does not replace validated food-safety controls or automated product-rejection systems.

Optimizing product quality and yield

Finding the operating window behind your best product

Why it’s relevant

Product quality in dairy processing depends on multiple interacting variables, including temperature, steam, processing speed, moisture, and specific weight. Variations during pasteurization and drying can affect final product characteristics, consistency, and yield. Understanding these relationships is essential to maintaining quality while maximizing production efficiency.

Why TrendMiner

Correlate process conditions with quality measurements to identify the operating parameters associated with optimal product characteristics. Compare successful and unsuccessful production runs, identify the root causes of quality deviations, and establish optimal operating ranges that improve consistency and yield across the production line.

Minimizing product losses during dryer start-up and shutdown

Getting the dryer on spec faster after every start-up

Why it’s relevant

Start-ups, shutdowns, and transitions between operating conditions can generate significant product waste in dairy drying processes. Until temperature, moisture, and other process conditions stabilize, the product may fall outside required specifications. Reducing stabilization time helps minimize losses and improve overall production efficiency.

Why TrendMiner

Analyze historical start-ups and shutdowns to identify the conditions that lead to faster stabilization. Correlate process variables with product quality and waste generation, and investigate how storage tank levels, process interruptions, and operational changes affect production performance. Use these insights to reduce start-up losses and improve operational consistency.

Ensuring accurate ingredient dosing and batch consistency

Dosing to recipe, batch after batch

Why it’s relevant

Accurate ingredient dosing is essential for maintaining product composition, recipe compliance, and consistent quality. Deviations in ingredient quantities or dosing sequences can lead to off-specification batches, unnecessary rework, and material waste. Understanding deviations across batches helps ensure reliable and repeatable production.

Why TrendMiner

Compare process data across batches and recipes to identify deviations in ingredient dosing and mixing conditions. Visualize process sequences, track relevant operating parameters, and investigate the causes of inconsistencies to support more reliable production and improved batch-to-batch quality.

Detecting pipe fouling and optimizing cleaning cycles

Catching fouling early and cleaning when it counts

Why it’s relevant

Product residues accumulating in dairy processing pipes can promote microbial growth, restrict flow, and reduce heat-transfer efficiency. Fouling can lead to unplanned cleaning, longer production interruptions, increased water and chemical consumption, and potential product-quality issues. Detecting changes early helps maintain hygienic conditions and maximize production availability.

Why TrendMiner

Correlate flow rate, pressure, temperature, pump speed, and product retention time to identify patterns associated with fouling or deteriorating equipment performance. Compare production and Cleaning-in-Place (CIP) cycles, detect abnormal operating patterns, and identify opportunities to optimize cleaning frequency and duration while maintaining required hygiene standards.