A leading producer and marketer of nickel, as well as a recycler of nickel-containing materials such as batteries. Challenge The customer is currently using a manual process to inspect and sort nickel pieces on a conveyor belt. Personnel is responsible for identifying and removing any pieces that do not meet the required shape or dimensions, as well as any contaminated pieces and unknown objects. This process is potentially error-prone and may lead to inconsistencies in sorting, especially when dealing with large volumes of nickel pieces or unknown objects.
Challenge The customer was using a competitor’s vision system with 6 FlexPicker robots on 3 conveyors to pick sausages, but the system was not meeting their satisfaction. There were problems with accuracy, speed, and rotation of picks, and sausages were sometimes being destroyed. The system also struggled when there were many sausages on the conveyor belt. Ocellus Solution Ocellus replaced the cameras with Nano 2020 cameras and trained an AI model to detect and identify different types of sausages.
A waste management company located in Norway. The company’s main focus is to provide efficient and sustainable waste management services to municipalities in the region of Sør-Hedmark. Challange Sorting waste is a crucial aspect of waste management, especially in waste loading areas where bags containing various types of waste need to be sorted out from other types of waste. Workers usually perform this task manually, relying on their ability to identify and separate the colored bags containing waste.
Challenge In waste management, it is crucial to sort out specific green bags containing bio waste from other types of waste in a waste loading area. This task is usually performed manually by workers who need to identify and separate the green bags containing bio waste from other bags. Failure to do so can lead to environmental issues, health hazards, and increased costs of waste management. Ocellus Solution To overcome this challenge, Ocellus installed a 3D color camera above the waste loading area to capture images of the waste bags.