The 3D vision inspection system has been one of the fastest-growing tech innovations in the markets for industrial image processing that has unveiled an ever-augmenting range of possibilities for Industry 4.0 and the growth of automation. Many inspection and automation applications now require more precise data than traditional 2D inspection due to the rising quality requirements and expectations. While 3D machine vision has proven to be a reliable source of productivity improvements in a variety of industries, finding potential applications on the shop floor may not be clear at first. Employees may be aware of the problems they confront, but they are designed to deal with them, ignorant that machine vision can help. Finding problems that 3D vision can solve necessitates close observation of the manufacturing process and interrogation of the right set of questions.
Let’s take a look at some significant difficulties and how 3D vision technologies are used to turn them into assets.
3D vision is commonly used for the following applications:
· Check the volume and size of food items like energy bars.
· In highly reflecting situations, such as medical device components, reads embossed or raised characters.
· Verifies the presence and function of gadgets in packaged boxes.
· Identifies surface defects and chips surface defects relate to the loss or abrasion.
· Robotic guidance offers instant vision support. Using several perspectives, 3D vision allows an application to detect a point of interest and even determine an object’s 3D location, including tilt and angle, in relation to the absolute coordinate system.
Do you need to keep track of how much product you’re giving away and how to reduce the product waste?
Certain industry regulations and compliances frequently require that the shipment of products should not be less than the actual volume quotation. However, companies in the food and beverage industries, for example, routinely oversize package contents to adhere to compliance while remaining incognizant to product give-away. From an organizational perspective, a deeper understanding of the packaging process allows you to deliver the proper amount of product to consumers. In turn, it saves money by keeping a close eye on the organization’s fiduciary duty in the long run.
Application Example 1:
According to some estimates, only 80% of errors are caught by 100% human review, rendering an expensive and high propensity of inspection errors. A candy bar manufacturer was used to giving away products unknowingly without recognizing how much they are rendering. Real-time feedback is possible with a 3D vision system, which includes trending, control limits, and product specs displayed on a running SPC chart. A 3D vision solution is applied to form a data matrix allowing the candy bar manufacturer to precisely measure real-time product volumes to reduce product give-away through constant tracking and feedback synchronization. Over the course of a year, this application was able to save hundreds of thousands of liters of raw material, and as little as 0.5% material adjustments were realized.
Application Example 2:
Machine Vision and Deep Learning are changing the trajectories of visual inspection demonstrating high-level accuracy and efficiency. This has helped in many ways for manufacturers to negate the downsides of product recalls. In many FMCG companies with product specialization in manufacturing potato chips, human inspectors are used to spotting clumped together chips which often signify undercooked and chewy textures. Because of the high line speeds, many problems go undetected. Therefore, the clumped chips are blown off and discarded prior to bagging by incorporating 3D Vision inspections into the production line.
What is the consequence of product recalls?
A product recall sends shivers down the spine of any production manager. Product recalls are incredibly expensive and can significantly harm customer relationships.
Application Example 3:
Although human inspection may appear to detect mis-seated O-rings at a hydraulic valve maker, even a minor seating mistake can cause major issues for the final customer. The 3D solution properly installed can identify minute O-ring insertion mistakes, assure spec seating, and eliminate failed valves. In this process, using machine vision for a final quality check ensures that only products that are perfectly aligning to specifications make it to shipment, while poor products are rejected or reworked. This information can also be used to measure critical metrics about how well operations are running.
The Downsides of Manual Sorting
Manual sorting stations can become an inefficient and costly affair thereby creating bottlenecks in the production process. If there are any faults in the sort, the expense of a human sorting station catapults, resulting in even more problems down the road.
Application Example 4:
A company that makes canned baked beans with bacon must ensure that each can has the appropriate amount of bacon. With the installation of robotic arms directed by a 3D vision camera, the CMM inspection enables users to see pieces of bacon on the line, map their sizes and assemble the correct combination of small-medium-large sizes into each can.
Why do you rely on CMM inspections?
Objects for products can be evaluated for quality and measured using a Coordinate Measuring Machine (CMM). It is a device that uses a probe to detect discrete points on the surface of a physical object in order to draw accurate product assembly or sorting.
Application Example 5:
In order to execute inspections on every 1000th part, the precision machining center commits costly CMM and engineering time to keep the production line flying in the aerospace industry. However, despite the increased engineering lead time and production cost a large number of defective components were found leading to the discovery of machining defects and tools. 3D vision systems and 3D cameras create a well-structured 3D Vision inspection solution to get a more detailed description of the main characteristics of products. With the implementation of an in-line 3D vision technology, the surface inspection and critical feature measurements on each part coming down the line can be made possible eliminating the need for stoppages or resource reallocation.
The use cases of potential machine vision applications are evident across a wide range of sectors. Configured on smart and adjustable stand-alone sensors, machine vision technology permits rapid creation and easy integration to versatile high-speed cameras that offer high-quality 3D and contrast images. The scalability of machine vision systems rightly fits with 3D solutions that can help in reducing waste, improving quality, eliminating overhead costs, and increasing ROI.