uso dell'intelligenza artificiale (AI) per migliorare il controllo di qualità: un caso di studio su Amazon

Artificial intelligence has infiltrated almost every aspect of industrial technology today (AI). AI is transforming the tools we use to manage manufacturing and processing facilities in subtle and not-so-subtle ways, from controllers to ERP to food safety and robotics. Quality control is one field where AI has a lot of potentials. Industries are profiting from the deployment of smart cameras and AI-enabled software to achieve greater quality inspection at speeds, latency, and costs that human inspectors cannot match. Given the social distance criteria of COVID-19, the introduction of these smart camera technologies is beneficial. For many years, machine vision has been employed in quality control applications. The introduction of quality control software-driven by deep learning, on the other hand, represents a departure from earlier machine vision technologies. The first stage comprises an expert deciding whether elements of photographs taken by a camera are relevant to the investigation (such as edges, curves, corners, color patches, and so on). The expert then creates a rule-based system that specifies, for example, how much "yellow" and "curvature" indicate a packing line item as a "ripe banana." The resulting system decides if the product is what it should be based on the expert's opinion. Despite the fact that this method has shown to be quite effective, there are a few occasions where it renders machine vision worthless. This is where artificial intelligence (AI) comes into play. Rather than depending on expert standards, AI-powered software may learn which traits are crucial on its own and develop rules that explain the attributes that distinguish exceptional items. This type of AI model is known as "deep learning." Businesses are adopting the latest technologies in their software development journey in order to construct a robust data engineering foundation and fuel innovation. Artificial intelligence will be the most significant breakthrough in quantitative easing during the next decade (AI). Facebook, Amazon, Google, and Microsoft are just a few of the IT behemoths who have invested billions in AI and Machine Learning programs and have integrated AI into their present and future products. Businesses must build an AI strategy in order to accelerate software development and achieve a successful digital transformation. We showcase a case study on Amazon Lookout for Vision, a new machine learning (ML) service that enables clients in industrial environments to detect visual abnormalities on production units and equipment promptly and cost-effectively.