The AI-based industrial visual inspection system is a revolutionary solution that combines the power of artificial intelligence and computer vision to enhance the accuracy and efficiency of visual inspections in industrial settings.
A well-established leader in the foods and beverages industry was in search of an AI-powered industrial automation edge computing solution that could be relied upon for managing their wide range of foods and beverages products; with a growing customer base and increasing product demand, this company decided that streamlining the distribution process and optimizing operational efficiency were of the upmost importance if they were to meet market expectations.
One of the biggest challenges facing today’s textile industry is the fact that it for the most part still relies on human vision and manual inspection for defect detection, meaning the industry not only operates on thin margins but also has a considerably high defect rate.
A few extensive warehouse facilities are already using some sort of automation, especially Autonomous Mobile Robots (AMRs), to help them stay ahead in their industry. But AMRs don’t come without challenges, especially when deploying them indoors in closed spaces. AMRs need to respond in real-time; they need to be able to make decisions on the go.
Autonomous lawn mowers are designed to reduce lawn maintenance labor costs and time. But an inefficient or improperly programmed or operated robotic lawn mower would defeat the whole purpose of “autonomy.” An unproductive and unsafe robot will turn a gardener into a programmer, taking away the focus on what matters: the grass.
Product inspection and defect-detection solutions within smart factories leverage visual inspection technology based on computer vision and deep learning. With the help of visual inspection systems collecting imaging data and feeding it into an inference engine, deep learning algorithms can help differentiate between different products, their parts, and specific characteristics and spot any anomalies. The visual inspection technology running on an appliance can imitate human eyes scanning products at an assembly line.
The growing demand for AI machine vision can be found in fast supply-chain processes, and one such application is the unloading of boxes from pallets, or depalletization.
A system integrator specializing in delivering smart solutions for supply chain management came to Lanner in search of a hardware solution that could be relied upon for automating most of the arduous tasks involved in depalleting, so that an end customer in the logistics industry can increase their productivity, throughput and also save costs.