Manufacturing companies can benefit from AI to prevent reputational damage and market share loss
Losing sales due to the quality of your products? AI in manufacturing is here to help
Manufacturing companies suffer losses in sales as a result of bad market rejection because their products are of poor quality.
It just takes one post about a bad quality of a company’s product to go viral and immediately affect sales.
Everyone remembers the major recall Sansung had with 2.5 million units of galaxy that started to blow up during flights.
Customers avoided buying Samsung products.
It caused Samsung a 17 billion dollar loss in sales.
Most recalls are caused by insufficient control of a company’s global manufacturing operations and processes.
What makes manufacturing so difficult to control?
Each factory has many different types of machines, delivering different data structures that do not “speak” the same language and are, therefore, extremely difficult to control.
Due to this situation, it is impossible to gain a deep understanding of the process and detect malfunctions resulting from quality and efficiency issues.
How AI in manufacturing can help you gain control of your production line and avoid recalls?
As a result of digital transformation, consumers receive safe, high-quality products while maintaining efficient and effective operations.
Utilizing AI technology, data can be instantly analyzed and automatically integrated with different types of data from any factory around the world, optimizing quality and efficiency of production processes.
Failures can be predicted by correlating tested parameters. You will receive automated alerts if the system detects abnormal behavior, which could prevent a recall incident.
QualityLine is AI manufacturing Analytics software solution with a patented pattern recognition technology that automatically integrates, interprets and analyses ANY type of manufacturing data and from any factory worldwide.
QualityLine continuously collects manufacturing data, from multiple global locations, in real time and analyses them to create a global end-to-end control that optimizes quality and efficiency in manufacturing.