roduct inspection is one of the most common applications for sensing

systems, and often one of the most challenging. In the high-volume production environments found in today’s manufacturing industries, manual inspection is no longer a realistic option. Inspectors are expensive to employ, they can only work limited hours and even the most conscientious inspector can never be 100 per cent attentive all of the time. Automatic inspection is, therefore, essential. But how should it be implemented? The answer depends on the complexity of the inspection task. In relatively straightforward, non-

critical applications, inexpensive sensors may do all that is needed. In fact, modern sensors - typically photoelectric and proximity types - can deliver excellent results in many situations. For more complex and critical applications, however, vision systems will usually be a better choice. Though more costly than simple sensors, they can do far more. For example, a sensor can check whether every bottle emerging from a production line has had a label applied, while a vision system can check that it is the correct label and, if necessary, monitor details such as whether the sell-by date is correct and properly printed. Vision systems were developed

primarily to help manufacturers produce the highest quality products quickly, consistently and cost-effectively. They can help to deliver on the much hailed ‘right the first time’ philosophy, as well as detect errors at the earliest possible stage, before they become too costly. Vision systems can be beneficially

included in a huge variety of applications in almost every industry sector, from high-tech automotive component manufacturing to high-throughput food and drink lines. They can be standalone off-the-shelf or, built-for-purpose systems, or they can be integrated into robotic or mechanical assembly systems. They can even be added to existing manufacturing systems to increase flexibility and performance. Although they are available in a bewildering array of types and specifications, the

28 MAY 2017 | DESIGN SOLUTIONS 

fundamentals of all vision systems are the same. They use one or more purpose-designed industrial cameras with specialised optics to acquire images, and then use powerful computer systems to process, analyse and measure characteristics defined by the user. When it comes to quantitative

measurements of a structured scene, vision systems excel because of their speed, accuracy, and repeatability. For example, on a production line, a vision system can inspect thousands of parts or products per minute. Also, because vision systems make no physical contact with the items being inspected, the risk of product damage is minimal. They also bring additional safety and operational benefits by reducing human involvement in a manufacturing process. For example, they can prevent human contamination of clean rooms and protect human workers from hazardous environments. Vision systems are widely used to

collect data from products and components and to guide automation systems, particularly those that use robots. For these applications, they are usually divided into four categories: 1D, 2D, 2.5D and 3D systems. 1D vision systems are essentially limited to the specific task of reading barcodes. These are the type most widely used in inspection applications. They can read and verify printed characters, check for

When the slightest problem with a product can result in financial penalties, it is more important than ever to ensure that they are correctly assembled, packed and labelled. Sensing systems are the key but, as Bob Hinchcliffe, technical director at Stelram explains, choosing the right option is vital

the presence or absence of items in their field of view, verify component orientation in assemblies and perform many other tasks. However, versatile as they are, 2D sensors do have their limitations. For example, they can tell whether or not a particular component has been placed in the right position within an assembly, but not if that component has been pushed down to secure it in place. For this sort of application, where the

2D picture from the vision system needs to be augmented with depth information (to establish if the component has been pushed down, or is it still resting on top of the assembly), a 2.5D vision system is often a cost-effective choice. This works in conjunction with a depth sensor - often a laser device - and combines information from both. With the right sensors, 2.5D systems can detect height differences as small 20µm. Where detailed spatial information is needed, a 3D vision system must be used. These systems incorporate multiple cameras mounted at different locations and use triangulation to work out and track the position of objects in 3D space. They are widely used in robot guidance applications, where they provide the robot with accurate real-time information about the locations of objects and their orientation. Sensing systems have an almost

limitless range of manufacturing applications, and making the right choice can determine the success or failure of a project. The best approach is to speak to experts who will offer guidance and advice on the best type of system for your specific needs. Stelram Engineering, for example, looks at all possible angles, and the solution you get will be tailored to do exactly what you need, efficiently and without breaking the bank.

Sensors play a vital role in today’s automation systems

Stelram Engineering

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