Conclusion. Machine vision systems have a wide range of applications in industrial automation. They enable industrial robots to perform complex tasks reliably and accurately, and allow companies to achieve previously impossible levels of efficiency and productivity. Machine vision has developed significantly over the last ten years and is now essential to many industries.
industrial robots are set to bring a new industrial revolution more important than anything seen before. Industrial robots perform repetitive tasks efficiently, they do not eat, they do not make mistakes, they do not get tired, they do what they are told.
Segmentation comprises demand for individual robot and end-users in all the regions and important countries in the region. Application segment includes current and estimated demand of industrial robots for applications such as picking, packing and palletizing. While gripper segment includes present and forecast demand for packaging robot with grippers such as claw, clamp, vacuum and others (Pneumatic and Hydraulic). End-use industry segment includes demand for packaging robots in industries such as food & beverages, pharmaceuticals, consumer products, tracking and logistics and industrial packaging.
Forex claims a few robots can trade profitably with 100% accuracy, like Ivybot. Some others with 94% accuracy like Forex Megadroid and 96% like FAP Turbo, though, the accuracy rates are debatable to an extent because the robots rely on past market pattern to analyse the market. With unexpected market changes, which may be comparatively new to the robot, accuracy in predicting possible positive trades may vary. They are tested and have proved to give profitable results at both demo and live accounts.
Such bots have been used extensively in data entry and database management services. However, more complex ‘smart’ bots have also been developed that can do actually data processing to simulate ‘intelligence’. These programs can take decisions and perform a variety of tasks and follow a set of rules and algorithms. What is significant that they programs can actually ‘learn’ as they process more and more data; in effect that they get better the more they work. Over time, they can recognise what inputs produce the outcomes nearest to the perfect ideal and then tailor their inputs accordingly.