Computer Vision in Manufacturing – Benefits, Implementation and Use cases

Updated on Feb 6th, 2024

Computer Vision in Manufacturing

Did you know- the global computer vision market size was valued at USD 12.22 billion in 2021; and that manufacturing only has just begun to gather a small part of that market? 

Often seen as the herald of AI in vision technologies, computer vision and its use cases have been shown as an upward arrow on charts since 1960s. Ad even though the technology has been mostly used in science applications for solid state physics, signal processing, neurobiology, etc., the rapid growth and adoption of AI has led to large scale use of computer vision in the commercial sector as well. In this blog, we will focus majorly on its use cases and benefits in the manufacturing industry. 

  • The global computer vision market size is USD 12.22 billion. 
  • Computer vision technology has been evolving since 1960s. 
  • Manufacturing units with Computer Vision have witnessed 12% growth in labor productivity and 10% increase production output. 
  • Quality inspection cameras, guided robots, and equipment monitors are the most popular use cases for CV in manufacturing. 

What is Computer Vision? 

Computer vision is an interdisciplinary technology that facilitates getting analytical information from digital images or videos. From industrial perspective, the technology enables computers to automate tasks that require human visual capabilities. As such the technology is concerned with the extraction, analysis, and deriving meaningful insights from graphical information.  

Computer vision is a rather more complex version of image recognition application of AI. As in it takes mere detection of image to a whole another level, where it can create real-time analytical response from high-quality images or a sequence thereof from variety of source including multiple cameras, real-time surveillance footage, multi-dimensional from medical scanner, and more. Some of the major applications that the technology offers include- 

  • Automatic inspection 
  • Organizing information 
  • Modeling objects or environments 
  • Autonomous navigation 
  • Visual surveillance, and more. 

Usecases of Computer Vision

Benefits Computer Vision Brings in Manufacturing Industry 

Computer vision is already making remarkable contributions in multiple sectors including, but not limited to, medicine, autonomous automobiles, construction, agriculture, and retail. And while in theory the most effective applications from the technology can be derived for manufacturing businesses, it is arguably the least explored area for computer vision. In this section, we’re going to discuss how computer vision in manufacturing industry is already transforming and what more it can do to derive maximum benefits. 

Predictive-Maintenance-2Predictive Maintenance 

The foremost benefit of computer vision for a manufacturing business is the same as any advanced AI technology’s is – predictive maintenance. Equipment in manufacturing units goes through tear and wear every minute they are in work, and since they are usually worked over time, there value depreciates unpredictably. Moreover, there’s always a possibility of a maintenance issue in the equipment leading to a chain reaction causing other parts to malfunction as well. Predictive analytics software development  based on computer vision can save fortunes. These system can easily detect changes in machinery with accuracy that manual inspection cannot even match. They can monitor and flag deviations in the working of the plants in real-time and help operators make timely decisions to reduce downtime and reduce maintenance costs by predicting problems and getting them fixed before any outstanding damage occurs.   

Supply-Chain-and-Logistics-] Supply Chain Optimization 

While the most effective results from computer vision implementation in manufacturing business happens when it’s done for the actual manufacturing process, as we will learn in further points, remarkable improvements also happen in supply chains. In terms of both cost reduction and quality maintenance, computer vision can prove to a game changing technology. The tech can eliminate human supervision from touchpoints where visual capabilities till time rendered them irreplaceable. This will not only help them bring more efficiency in logistics, as unlike humans the application can work ceaselessly, but will also enhance quality. It is no secret that supply chain passes happen due to lack of diligence for a mere second. By eliminating human intervention, computer vision can eliminate those errors and bring more transparency to the entire process, from inventory management to monitoring overall warehouse operations, eventually improving customer satisfaction. 

Increased Productivity Greater Productivity 

The manufacturing processes that require human visual understanding, can benefit largely with the help of computer vision. In fact, despite being in its neoteric stage, the deployment of computer vision-powered robots has already started bringing noteworthy results. Some businesses have reported 12% growth in labor productivity, while other 10% increase production output. And to think this is just the tip of the iceberg; computer vision has huge potential in improving productivity for manufacturing businesses leading other benefits, we’ll shortly uncover. 

Accessibility Issues Elimination of Errors  

One of the biggest challenges for manufacturing processes is the inevitability of errors and the collateral damage caused by the same. With the help of computer vision, these errors can be minimized to a great extent. Most of the errors that happen in manufacturing, happens due to lack of due diligence. There are several minute things that a laborer can easily overlook, but when that work is taken care of by a highly functional computer vision application, chances of errors drastically decrease. The application can easily identify production issues in real-time, and segregate faulty products. This eventually optimizes the manufacturing processes by minimizing wastage, improves quality and enhance customer trust. 

Cost Savings Cost Optimization 

Both the above-mentioned benefits don’t stand alone. Put together they result in huge cost savings and reduction in overhead expenses.  AI-vision based solution development and deployment can reduce maintenance cost, loss due to machine downtime, eliminate operational overheads, and improve output per unit time to eventually help businesses earn more net revenues. 

worker-safetyWorkforce Safety 

While most of the points mentioned above concern with making manufacturing businesses more efficient and productive, there are other, ore humanistic areas as well, where computer vision is helping. The application can easily detect machinery malfunction before they can snowball into serious problems which can potentially harm factory personnel. Not only that, the technology can be used to monitor the workers health as well. It can be trained to sense and alarm operators for when a labor is showing signs of fatigue or discomfort, helping them offer proper medical care as soon or even before it’s required.

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How to Implement Computer Vision Applications in Manufacturing? 

To implement such a transformative technology in a manufacturing business, requires a completely sophisticated approach, in order to ensure easy transformation with no resistance and positive ROI.

1. Evaluation of problems

The purpose of adopting computer vision, or any form of AI in manufacturing industry, is to offer solutions to problems and eliminate inefficiencies. As such it is important to make identification of those problems and inefficiencies the first step of the process. This is why, when it comes to adoption of computer vision, you should not start by thinking of the technology but rather come to his technology when one of the problems your organization is facing has a solution in it. Now once you’ve reached to the point where it is clear that computer vision is the right choice, it is ideal to involve all the stakeholder to gain insights from them and ensure that when the process is underway, there is no resistance.

2. Create an implementation team

In this stage, you will actually work on assembling a team of dedicated developers for the technology’s implementation. Now the members of this team will vary on the basis of your requirement, objective, and use case. However, rest assured, you are going to need some tech savvy people in this team with very specific skillset. For example, if your use case requires you to add more capabilities to your equipment you will need personnel skilled in hardware manipulation, whereas if it’s just surveillance process enhancement for predictive maintenance, more people from data science background will be required. 

Other than skillset, the reason you should assemble a complete team for this transformation process is to guarantee the success of the program with optimal effectiveness. Often when you implement such strong technologies in siloes the overall scope of the project gets diminished because of lack of clarity and common objective. Making a team will also help in establishing accountability as well as time-sensitivity of the project, since you will always keep optimum resources in the team to see it through.

3. Run a pilot program

Once you have created the team and set them in motion, it’s time for you to prepare and execute a pilot program. It is unwise to consider that such a huge transformation can happen in large scale. In fact, you will have to implement and constantly test the results many times before the process will finally be over. But with pilot program your objective should be to prove technical feasibility of computer vision in your manufacturing units with insightful demonstration at the end of it. 

With this pilot run you will also get to learn the bottlenecks and smoothen them out.  You can figure out how old technologies can integrate with your computer vision application to create a moe cohesive ecosystem. Once that’s done, you’ll be ready to scale u the process and start transforming your processes to involve the new tech.

4. Train your staff

Adopting computer vision is not the easiest thing to do for personnel who’s been working through traditional methods through ages. New technologies like computer vision are often complicated and require extensive training. Providing engaging training sessions are key to a successful transformation.  

Now while arranging these sessions keep in mind that everyone has different learning styles and needs. And it is your responsibility to tailor the learning process as per individual requirement for smooth adoption. Other than learning to adapt, the staff should also learn the scope of computer vision and how they are going to benefit directly from it, to eliminate any probabilities of resistance.

5. Deploy and fine-tune

Once you have set the pilot program for the application with a skilled team and even have your rest of the staff prepared for it too; you are ready to deploy computer vision on large scale with as many use cases as required. Of course, the process is going to be gradual and should be completed in smaller modules. In this final stage, it is important to ensure integration of the technology with the traditional tool set happens smoothly. Last thing you want is a unit acting up post deployment. So keep iterating the process of implement and test throughout the transformation process of our supply chain and manufacturing process, to ensure the technology solves your problem smoothly and not create new ones. 

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Computer Vision Use Cases in Manufacturing

Now we know how computer vision can be gradually implemented to transform workflows in a manufacturing firm, it’s time to learn varied use cases through which it can be done. 

Accurate-Real-time-Inventory-OverviewInventory Management Tools 

Manufacturing companies are equipping their inventory management tools with computer vision. This is helping them in more effective tracking of inventory location and current status. There are now way less errors they have accounted in warehouse operations and inventory mismatch, since the implementation of computer vision from end-to-end processes help them eliminate any vulnerability associated with negligence. In fact, added with predictive AI applications, such tools are capable of optimizing supply chains by alerting respective managers to get alerts when any product goes out of stock or enters the pre-stipulated reserve status.  

Quality-ControlQuality Inspection Cameras 

Other than inventory and supply chain optimization, computer vision has huge implications of maintain high quality standards of final products and their packaging. Companies that have installed their security, surveillance and process monitoring cameras with quality inspection computer vision applications have reported drastic rise in the positive quality and packaging standard audits. Manual inspection has always remained unguaranteed at best, but with the computer vision based quality inspection cameras, manufacturing units can have greater confidence in the quality of their product, which eventually leads to operational efficiency. 

Barcode LabelsBarcode and RFID Readers 

Many leading manufacturing companies are investing in computer vision-based systems for reading barcodes and facilitate the concerned processes with improved efficiency. And so far, they have been proved to be more effective than the traditional tools in diverting packages with faulty barcodes. The entire process of product audit with barcodes has been simplified and made more effective by the simple addition of computer vision technology. Now companies no longer have to work with samples. Every product they deliver can now circulate in the market with the assurance of authentic information-attached to the packaging. 

Improved-asset-condition-monitoringEquipment Monitors 

Manufacturing plants involve specialized equipment for the production of goods. With regular use, these machines may show signs of wear or even malfunction, leading to product defects and losses. The use of computer vision technologies is much more effective than human observations in detecting such changes in manufacturing equipment. Such technologies have been used to recognize defects in real time, even in tiny machine parts. This makes it possible to discover and repair the parts in time which could have otherwise caused the manufacturing process to slow down. 

Rigidity of Robotic Process AutomationGuided Robots 

One of the most exciting use cases of computer vision is in the manufacturing automation robots. With the technology, these robots are more capable than they were ever before. They are better guided to present on the assembly lines all by themselves without needing a centralized software with an administrator behind. They can now also now pick and place the items with greater precision avoiding unforeseeable accidents by inspecting the imagery in real-time. 

Wrapping Up! 

When it comes to adopting new technology, there always something daunting about the entire process. This phenomenon becomes even more palpable when the technology is as intensive as computer vision and the process as intricate as manufacturing. That being said, with a proper skillset and approach no process is too difficult. Matellio has been helping manufacturing businesses for decades in digitally transforming their businesses with state-of-the-art technologies. Now with our skillset and experience in computer vision applications development, we are more ready to help you adopt it AI for your manufacturing business. All you need to start your transformation journey is book a free consultation call with our experts, and they will start helping you out right away. 

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