Predictive Quality

Predicting Quality with Artificial Intelligence (AI)

From long-standing production experience we know that scrap or rework can occur even if all process parameters or sensor values are within the valid tolerance limits. Complex correlations and interactions originating from the actual production technology usually cause these failures. This is where the mApp Predictive Quality steps in. The solution predicts the quality of a product during or after the manufacturing process by means of data analysis and AI methods.

The mApp uses historical process values and the corresponding quality assessments and analyzes these values to assess the probability of the produced article being classified as scrap or yield. To this end, the mApp Predictive Quality creates a model based on historical data, which maps the interrelationships between process values and quality. The results help reduce inspection costs as the company can decide to inspect only those parts that are more likely to be of poor quality. In particular if a product cannot be inspected immediately or is destroyed during inspection, then the application's prediction supports the people responsible in taking sound decisions on whether the semi-finished product is further processed or not — even without extra inspection. This helps saving time and money in quality assurance.

Your benefits

Your quality assurance is optimized by reducing the number of inspections and predicting quality assessments (pass/fail) with the help of artificial intelligence. This approach pays off for both, mass production and destructive inspections.

Predicting Quality with Artificial Intelligence (AI) promotes sustainability

Predictive Quality uses artificial intelligence (AI) to make early quality assessments for products with a high vertical range of manufacture, for example. The processing of presumably defective parts can then be stopped at an early stage. This saves material, energy, and processing time.

Technical information

Die mApp Predictive Quality is included in the Quality Management category of HYDRA X and in the AI Suite.

The mApp uses data of the Virtual Production Reality (ViPR) of MPDV's Manufacturing Integration Platform (MIP)

 

Predictive Quality in the MIP ecosystem

Quality assurance is a central topic in manufacturing. Along with the AI-based prediction of quality, MPDV offers further mApps reducing scrap in production:

• In-Production Inspection: In-production inspection
• AI-based Scrap Analysis: Analyzing scrap with AI
• Quality Analysis & Statistics: : Quality Analysis & Statistics
• Work Order Controlling: Production KPIs and post calculation

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