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Why use Oxien’s N-Hence Manufacturing platform?
Answer:
The N-Hence Manufacturing platform uses production data (equipment, temperature, voltage, raw material, etc.) and confronts them with the quality metrics of finished or in-process products. The quality results indicate failures/defects/nonconformities in the products.
Using artificial intelligence/machine learning algorithms, the N-Hence Manufacturing platform is able to identify the relationship between production data (variables) and the failures identified in the products.
The diagnosis is presented through an indicator of the probability of occurrence of defects.
Answer:
The N-Hence Manufacturing platform uses production data (equipment, temperature, voltage, raw material, etc.) and confronts them with the quality metrics of finished or in-process products. The quality results indicate failures/defects/nonconformities in the products.
Using artificial intelligence/machine learning algorithms, the N-Hence Manufacturing platform is able to identify the relationship between production data (variables) and the failures identified in the products.
The diagnosis is presented through an indicator of the probability of occurrence of defects.
Answer:
The N-Hence Manufacturing platform uses production data (equipment, temperature, voltage, raw material, etc.) and confronts them with the quality metrics of finished or in-process products. The quality results indicate failures/defects/nonconformities in the products.
Using artificial intelligence/machine learning algorithms, the N-Hence Manufacturing platform is able to identify the relationship between production data (variables) and the failures identified in the products.
The diagnosis is presented through an indicator of the probability of occurrence of defects.
Answer:
The N-Hence Manufacturing platform uses production data (equipment, temperature, voltage, raw material, etc.) and confronts them with the quality metrics of finished or in-process products. The quality results indicate failures/defects/nonconformities in the products.
Using artificial intelligence/machine learning algorithms, the N-Hence Manufacturing platform is able to identify the relationship between production data (variables) and the failures identified in the products.
The diagnosis is presented through an indicator of the probability of occurrence of defects.
Answer:
The N-Hence Manufacturing platform uses production data (equipment, temperature, voltage, raw material, etc.) and confronts them with the quality metrics of finished or in-process products. The quality results indicate failures/defects/nonconformities in the products.
Using artificial intelligence/machine learning algorithms, the N-Hence Manufacturing platform is able to identify the relationship between production data (variables) and the failures identified in the products.
The diagnosis is presented through an indicator of the probability of occurrence of defects.
Answer:
The N-Hence Manufacturing platform uses production data (equipment, temperature, voltage, raw material, etc.) and confronts them with the quality metrics of finished or in-process products. The quality results indicate failures/defects/nonconformities in the products.
Using artificial intelligence/machine learning algorithms, the N-Hence Manufacturing platform is able to identify the relationship between production data (variables) and the failures identified in the products.
The diagnosis is presented through an indicator of the probability of occurrence of defects.
Answer:
The N-Hence Manufacturing platform uses production data (equipment, temperature, voltage, raw material, etc.) and confronts them with the quality metrics of finished or in-process products. The quality results indicate failures/defects/nonconformities in the products.
Using artificial intelligence/machine learning algorithms, the N-Hence Manufacturing platform is able to identify the relationship between production data (variables) and the failures identified in the products.
The diagnosis is presented through an indicator of the probability of occurrence of defects.
Answer:
The N-Hence Manufacturing platform uses production data (equipment, temperature, voltage, raw material, etc.) and confronts them with the quality metrics of finished or in-process products. The quality results indicate failures/defects/nonconformities in the products.
Using artificial intelligence/machine learning algorithms, the N-Hence Manufacturing platform is able to identify the relationship between production data (variables) and the failures identified in the products.
The diagnosis is presented through an indicator of the probability of occurrence of defects.
Create a leaner value chain
Maximize flow, reduce waste and promote financial results.
N-Hence Manufacturing
Using AI/ML to help our clients embed a data culture, improve internal processes, reduce decision lead time and streamline the innovation cycle.
Efficient Support
Our clients have immediate and efficient support!
Our goal is to optimize production processes to gain productivity with quality.
What are the process variables and their optimal values that will reduce production failures and minimize product defects?