{"id":4013,"date":"2021-05-03T09:15:44","date_gmt":"2021-05-03T15:15:44","guid":{"rendered":"https:\/\/limblecmms.com\/?p=4013"},"modified":"2025-05-30T13:06:59","modified_gmt":"2025-05-30T19:06:59","slug":"visual-inspection","status":"publish","type":"post","link":"https:\/\/limblecmms.com\/blog\/visual-inspection\/","title":{"rendered":"What, Why, and How of Visual Inspections: Processes and Benefits"},"content":{"rendered":"

[vc_row kd_background_image_position=”vc_row-bg-position-top”][vc_column][vc_column_text]\"visualVisual inspection is a very common technique used by <\/span>maintenance professionals<\/span><\/a> in physical asset management. It is also the last step in the production line for most goods.<\/span><\/p>\n

While engineers are constantly finding new ways to automate widely used repetitive actions, visual inspections have remained an invaluable tool for finding issues, especially in the field of equipment maintenance.<\/span><\/p>\n

In this post, we explain the value of visual inspection for a variety of purposes and cover the most common modern use cases. And of course, because visual inspections can give varying results due to their subjective nature, we will share some essential steps you can take to standardize your inspection process.<\/span><\/span><\/p>\n

The definition of visual inspection<\/span><\/h2>\n

Visual inspection is a very basic inspection method used in manufacturing quality control and asset maintenance. It is the method of looking for flaws or imperfections using the naked eye and non-specialized inspection equipment.\u00a0<\/span><\/p>\n

Quite often, there is no empirical formula for finding defective products or inspecting a piece of equipment. Therefore, the experience of the person that is performing visual inspection plays a significant role in determining the efficacy of the process.<\/span><\/p>\n

Looking for anomalies with the naked eye is the most common method of visual inspection. But it is not necessarily limited to that. Using other senses for inspection also falls under the broad umbrella of visual inspection. The basic tenet is that an experienced person is using his sensory capabilities to identify problems with objects they inspect.<\/span><\/p>\n

For instance, experienced professionals can <\/span>assess the quality of materials like wood<\/span><\/a> and metals by judging the sound produced by them. They can just knock on the object and make a judgment based on the sound produced by it. <\/span>
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\nSimilarly, a <\/span>maintenance technician<\/span><\/a> might <\/span>smell<\/span><\/i> a gas leak, <\/span>hear<\/span><\/i> that something is loose inside the asset, or even <\/span>feel<\/span><\/i> that a piece of equipment vibrates more than it should or radiates excessive heat. All while performing a <\/span>visual inspection<\/span><\/i>.<\/span><\/span><\/p>\n

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Checklist for Creating a Preventive Maintenance Plan<\/h2>
Following a consistent Preventive Maintenance Plan can make life easier. Use this checklist to create your own!<\/h6><\/header>[\/vc_column_inner][\/vc_row_inner][vc_row_inner content_placement=”top” kd_background_image_position=”vc_row-bg-position-top”][vc_column_inner width=”1\/2″ css=”.vc_custom_1631866454223{padding-right: 50px !important;padding-left: 0px !important;}” offset=”vc_col-lg-6 vc_col-md-12 vc_col-xs-12″ css_tablet_landscape=”.vc_custom_1631866454223{padding-right: 0px !important;}” css_tablet_portrait=”.vc_custom_1631866454223{padding-right: 0px !important;}” css_mobile=”.vc_custom_1631866454224{padding-right: 15px !important;}”][vc_raw_html]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[\/vc_raw_html][\/vc_column_inner][vc_column_inner width=”1\/2″][vc_single_image source=”external_link” alignment=”center” css_animation=”fadeIn” custom_src=”https:\/\/3975608.fs1.hubspotusercontent-na1.net\/hubfs\/3975608\/Content%20Downloads\/PM%20Checklist%20mockup.png”][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row kd_background_image_position=”vc_row-bg-position-top”][vc_column][vc_column_text]<\/p>\n

Visual inspections in physical asset management<\/span><\/h2>\n

Visual inspection is an integral part of physical asset management. Maintenance professionals use it on a daily basis as part of their <\/span>routine maintenance activities<\/span><\/a>.<\/span><\/p>\n

Occasionally, an organization will train machine operators to perform visual inspections instead of maintenance techs. This practice is commonly referred to as <\/span>autonomous maintenance<\/span><\/a>.\u00a0<\/span><\/p>\n

Regular inspections help maintenance teams spot signs of wear and tear that can lead to equipment failure. Minor issues are corrected on the spot if the technician has access to the right tools and parts. Otherwise, they will leave a note about the detected issue. The maintenance manager or supervisor will later add a new task to the <\/span>preventive maintenance plan<\/span><\/a> so the problem doesn\u2019t go unaddressed.\u00a0\u00a0<\/span><\/p>\n

While they can be very useful, visual inspections come with a couple of downsides. Machines often need to be shut down so a technician can perform a visual inspection. As you can imagine, this reduces equipment uptime and can hurt the bottom line. The other problem is that visual inspections can sometimes spot the problem too late. If you detect noise, heat, or smoke, the failure might already be in progress.<\/span><\/p>\n

To combat these issues, more and more organizations are using condition monitoring sensors and equipment to monitor asset health and performance in real-time. This technology allows them to notice deterioration signs much earlier than it would otherwise be possible. This is neatly represented in the graphic below.<\/span><\/p>\n

\"Visual
\nThese sensors allow organizations to run advanced maintenance strategies like <\/span>condition-based maintenance<\/span><\/a> and <\/span>predictive maintenance<\/span><\/a>. Such strategies reduce the need for visual inspections but are far from making them obsolete. Sensors are still fairly expensive and can only detect specific deterioration signs. It means that <\/span>manual <\/span><\/i>testing methods like visual inspections are not only necessary but a more cost-effective option, especially for inexpensive assets.<\/span><\/span><\/p>\n

Visual inspections in quality control<\/span><\/h2>\n

Visual inspection is the oldest non-destructive testing (NDT) method for quality control. In its original form, visual inspection is used to observe the surface of an object and look for cracks, scratches, misalignments, corrosion, and other physical defects.\u00a0<\/span><\/p>\n

Big brands, especially those that produce expensive products, have a lot to lose if they send out a whole line of defective products. Visual inspection is a great way to quickly filter out items with obvious defects.<\/span><\/p>\n

For instance, automakers like Rolls-Royce give extreme importance to the fit and finish of each component that goes into their cars. Their internal research shows how <\/span>roughly 70% of all faulty components<\/b><\/a> are rejected because of discrepancies found during visual inspection<\/b>.<\/span><\/p>\n

This is not to say that visual inspections are reserved only for luxury goods. A good counter-example comes from the food and beverage industry. Here, visual inspections are performed to ensure there aren\u2019t any foreign objects in the product, that packages are uniform and properly sealed, and that the products are not mislabeled. Because of the fairly straightforward nature of these inspections, many <\/span>food manufacturers are starting to adopt machine vision systems for quality control<\/span><\/a>.<\/span><\/p>\n

\"automatedAn example of an automated visual inspection system (<\/span><\/i>Image source<\/span><\/i><\/a>)<\/span><\/i><\/p>\n

Broadly speaking, visual testing for quality control can be done in three different ways:<\/span><\/p>\n

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  1. Random sampling: <\/b>Quality checks are performed on randomly selected products. Products can be checked right at the production line for obvious visual defects. More complex inspections (like testing the interior of a product) are usually carried out at special testing areas.<\/span><\/li>\n
  2. Full manual sampling: <\/b>All products are inspected manually. This can be a physically demanding job with a lot of repetitive actions. To maximize the health and productivity of workers performing the inspections, organizations should look to provide the necessary tools and ergonomic equipment.\u00a0<\/span><\/li>\n
  3. Automated visual inspection: <\/b>Products are inspected using cameras, image processing methods, and machine learning algorithms. More on this later in the article.<\/span><\/li>\n<\/ol>\n

    <\/span>
    \nThe automated systems for visual inspection seem to be gaining more traction as the private sector develops industry-specific solutions. It remains to be seen how fast will manufacturers adopt this technology.<\/span><\/p>\n

    Modern visual inspection techniques<\/span><\/h2>\n

    Incremental technological improvements in camera quality and machine learning are starting to change how we think about visual inspections. Maintenance techs now have the ability to perform visual inspections at hazardous and hard-to-reach places, while being miles away from the objects they are inspecting. Quality control specialists, on the other hand, have more and more access to automated visual inspection solutions.\u00a0<\/span><\/p>\n

    Remote visual inspections for asset maintenance<\/span><\/h3>\n

    These days, technicians can use <\/span>robots<\/span><\/a> and <\/span>drones<\/span><\/a> to view otherwise inaccessible areas. We are talking about inspecting objects at great heights, very confined spaces, hazardous places like storage tanks, and similar.\u00a0<\/span><\/p>\n

    Images or videos can be viewed from a remote location, even thousands of miles away from the location of the inspection site – hence the name remote visual inspection. The captured data can be accessed in two different ways:<\/span><\/p>\n

      \n
    1. Live stream:<\/b> Robots or drones can relay data of the location to the base station where the inspector can watch the live feed. In this case, the robot or drone can also be controlled from the remote terminal. It can only be used in cases where there is constant wireless communication between the equipment that is being operated and the base station.<\/span><\/li>\n
    2. Saved data<\/b>: In extremely remote or hazardous areas where there can be no wireless communication, videos and images are saved and analyzed later.\u00a0<\/span><\/li>\n<\/ol>\n

      An additional advantage of these types of inspections is that the images and videos can be easily shared between technicians and other relevant team members, without having to be physically present at the inspection site. This collaboration can be extremely useful when solving complex problems or when there is a need to contact specialized experts.<\/span><\/p>\n

      Automated visual inspections (AVI) for mass production<\/span><\/h3>\n

      Automated visual inspection (AVI) uses computer vision and artificial intelligence to perform visual inspections on products instead of quality inspectors. This technology aims to dramatically reduce the need for human intervention for inspection in large-scale automated factories.<\/span><\/p>\n

      \"cognitiveCognitive visual inspection solution from IBM (<\/span><\/i>Image source<\/span><\/i><\/a>)<\/span><\/i><\/p>\n

      Foxconn, one of the largest electronics manufacturers on the planet, <\/span>is using AVI in their manufacturing facilities<\/span><\/a>. We will use them as an example to briefly describe how this technology is supposed to work.<\/span><\/p>\n

      Suppose Foxconn is manufacturing motherboards for the latest iPhone. One ideal sample of the motherboard is made and inspected by a human visual inspector. Once it has been approved, this model is uploaded to the database and the algorithm can use it as a benchmark. Some examples of defective models are also uploaded to the server and used to teach algorithms how to recognize specific anomalies.<\/span><\/p>\n

      The rest of the motherboards will come out of the automated assembly line and pass under the camera systems for the AVI. Multiple images of the product are captured from various angles. The captured images are compared to the benchmark images stored using machine learning algorithms. Some of the factors compared could be:<\/span><\/p>\n