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O sumo certo está na garrafa certa? As bolachas têm o tom de castanho pretendido? A data de validade foi adicionada à embalagem? Os sensores SensoPart fornecem respostas fiáveis a estas e muitas outras questões.
Por exemplo, no enchimento de garrafas de bebidas: os scanners a laser da série FT 25-RGO são especialmente treinados para a deteção de garrafas (transparentes), enquanto o sensor de cor FT 55-CM ou o sensor de visão VISOR® Object Color identificam inequivocamente se a tampa da garrafa está na posição certa e na cor certa. No final da cadeia de produção, o nosso leitor de códigos VISOR® faz a leitura da embalagem e verifica os códigos e as informações em texto simples. Muitos dos nossos sensores também são fornecidos numa caixa de aço inoxidável particularmente robusta e hermeticamente selada (IP 69 K), perfeita para a utilização em ambientes higiénicos: quando uma instalação industrial de processamento de carne é limpa com um jato de vapor potente no final de um turno, o sensor também pode desfrutar de uma boa lavagem.
Os exemplos de aplicação seguintes mostram-lhe as utilizações possíveis dos nossos produtos na prática.
In the food industry, packaging is often automated and handled by robots. These robots pick up food from the conveyor belt and place it into the correct packaging. To achieve this, a vision camera is needed to accurately determine the X and Y positions of the food on the belt and send this information to the robot. At the same time, the system should verify details such as size, diameter, deviations, and cooking level.
In an industrial bakery, rolls, pancakes, donuts, and bagels are produced on an automated production line. After coming out of the oven, these baked goods must be removed from the conveyor belt and placed in boxes by a robot. At the same time, the degree of browning of each item must be assessed to ensure quality.
To optimize the serving of drinks at major events, the process is automated using an innovative drink filling machine. Sensors ensure that transparent plastic cups are properly detected and automatically initiate the filling process as soon as a cup is inserted into the machine.
During final product control, it is to be checked that the products have a uniform appearance. The aim of the application is to guarantee the correct position of adhesive labels on packaging so that the products appear identical on the sales shelf.
During final product control it is checked that the products are correctly sealed. The aim of this application is to check that closures are fully sealed so that products cannot leak during transport.
In modern production facilities, where traceability and quality control are essential, reading OCR and DMC codes on components plays a key role. These codes are used not only for identification, but also to ensure complete traceability of products and components throughout complex manufacturing processes. A reliable vision system must not only recognize OCR and DMC codes, but also compare them against each other.
After harvest, oranges and other citrus fruits go through several processing steps before reaching the market or end consumers. One important step is the precise control of spray nozzles for chemical treatment. This protective coating is essential for extending the shelf life of the oranges and preventing premature spoilage. To ensure the preservation agent is applied in exactly the right amount, the oranges must be counted and their surface distribution measured on the conveyor. A vision sensor is required to reliably perform both tasks.
In modern manufacturing, the need for seamless component traceability (Track-and-Trace) continues to grow. Data Matrix Codes (DMCs) have emerged as one of the most reliable methods for identification and traceability. The goal is to scan the Data Matrix Code on each component, guaranteeing precise product processing and flawless serial number management.
In food production, different products (such as pre-packaged salads) are often processed simultaneously on a single line. A vision sensor ensures that the correct product type is processed and packaged, and inspection results are delivered in real time.
When manufacturing ball bearings, it is vital to know that the bearing has the full number of balls. The aim of the application is to inspect a ball bearing after assembly to ensure it is complete.
In high-performance bottling plants, tens of thousands of bottles can be transported on conveyor belts every hour. With the help of robots, the PET bottles are automatically placed on the conveyor line. Depending on whether the belt is free or not, the robot should place additional PET bottles on the conveyor line. An optical detection system should monitor whether the conveyor line is free or occupied in a certain area (area monitoring) and provide the robot with a trigger signal.
When filling glass bottles or labelling bottles, it is essential to be sure that the bottle is present under the tool in the machine.
After food is packed, QR codes are to be read on the packaging to check the legibility of the code and to read the content.
Millions of objects move along conveyor belts every day, advancing to the next processing step. Before downstream operations can begin, it must first be confirmed that an object is present on the workpiece carrier. A sensor is needed to reliably perform this presence check and keep production lines running smoothly.
A robot is tasked with picking components from a flexible feeding platform. The position of the objects may vary. A vision sensor can identify and relay the exact position of the part to the robot.
Throughout the production process, a large quantity of data is generated that has to be monitored and checked. The operator must be able to consult, manage and evaluate this data easily in order to identify and implement any necessary modifications to the process.
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