With technology revolutionizing every aspect of our lives, from how we live, work, and shop to how we conduct business, technology is taking over everywhere. Today businesses rely on emerging technologies to help them improve their competitive advantage and drive growth strategies.
Computer vision technology is one such tool that is immensely helping industries increase the efficiency of their systems by tracking and streamlining processes, maintaining data flows to provide valuable real-time insights, allowing them to tailor their services as per consumer preferences, reducing costs and enhancing revenues.
Despite the innumerable benefits that AI-based Computer Vision solutions offer, the most critical aspect a business should emphasize before adopting any new mechanism is to know whether it will deliver on its promises and generate a Return on Investment (ROI). With radical computer vision solutions, the answer may be even greater than you expect.
There are pieces of evidence available that the technology can eventually improve operations in every industry it touches. This fact explains the swift growth of the computer vision market. From a market size of $15.9 billion in 2021, the AI-based computer vision market is expected to reach $51.3 billion by 2026, growing at a CAGR of 26.30% for the forecast period.
However, for businesses, one-factor driving decisions about making investments in technology is reckoning expected returns on investment before deploying them. A return on investment refers to the financial ratio of an investment’s gain or loss relative to its cost.
In the simplest form, the benefits outweigh the cost when it comes to an investment in Computer Vision solutions; however, a calculation of ROI can be challenging to figure out but is attainable. Here in this blog post, we will highlight some of the most compelling factors that credibly impact the ROI of Computer Vision.
Let us first understand Computer Vision solutions.
Introduction to Computer Vision
Computer Vision is the field of Artificial Intelligence that focuses on replicating some complex parts of the human visual system and intelligent thinking. Enabling computers to derive information from visual inputs like images and videos in a similar way that humans do and make recommendations based on that information to automate tasks.
How does the technology work?
Computer Vision needs data to function. Just like a person learns to see and understand things, computer vision algorithms need the training to understand and interpret information from the data they capture. This is done using Deep Learning and an Artificial Neural Network.
Machine learning enables a computer system to learn about the context of visual data when enough data is fed through the model. And a Neural Network helps the deep learning model to ‘look’ by breaking down images into pixels and making predictions about what it sees.
The entire process requires a dataset of labeled or annotated images to feed the system to make it learn, and then the AI algorithm is enabled to perform different tasks that would otherwise have required human intervention like visual monitoring, analysis, expert-level interpretation and decision-making.
Computer Vision – Use-Cases
There are endless use cases of the technology across different industries like manufacturing, retail, logistics, healthcare, construction, transportation, and agriculture that include systems for;
· Machine Vision solutions like defects detection and quality assurance
· Out-of-stock detection for retail
· Predictive maintenance
· People detection and tracking for patients, customers or employee authentication
· PPE detection, security and compliance assurance
· Warehouse and Inventory management
· Security monitoring
· Support for digital twins in manufacturing
· Medical Diagnosis
· Traffic flow analysis and parking occupancy detection
· Smoke and fire detection
And the list doesn’t end here. Successful computer vision investments generate ROI by targeting the concrete problems first and then expanding on to establishing more cohesive and secure frameworks. There can be direct and indirect returns. Companies also need to consider the time it takes to break even and then supersede that amount in revenue or other added value in terms of factors that are not financially quantifiable.
The following are some factors that can help establish the ROI of Computer Vision solutions in the manufacturing industry;
Reduced Labor Costs
Reduced labor costs are the most common input to ascertain ROI calculations. Most production facilities rely on manual inspection processes to inspect their finished or work-in-progress products, often requiring a large workforce. However, when integrated properly, factory vision systems enable these tasks to become fully automated, happening at a rapid speed and maintaining a higher accuracy level of defect detection. The advantages of vision solutions go beyond the savings of wages and offer many other benefits like higher quality levels, speed and increased uptime.
Increased Profits through improved quality
With the help of a Machine Vision system, there can be a significant shift in product quality metrics. Product flaws will be identifiable at each stage, and the probability of a defective product reaching the final production stage will be nearly zero. It will also result in fewer inspection errors, more accuracy and greater reliability and consistency. A machine vision system ensures that only high-quality products reach customers, allowing the business to save the cost of poor quality and thrive. When calculating the ROI of a computer vision system, quality improvements can be a key driver.
Data is most valuable
Collecting data using a computer vision system gives a deep understanding of each manufacturing process and the entire facility. Further process improvements can be made using these valuable insights, which were not possible to acquire with manual data collection processes. Though measuring them before implementation is impossible, ROI calculation should incorporate these benefits.
Enhanced Safety, Reduced Financial Liabilities
Improved safety is an important factor and should not be overlooked while calculating the ROI of a Machine Vision system. The system significantly reduces the risk of injury by identifying hazardous areas, traffic flow inefficiencies, and trip and fall dangers. Removing workers from high-risk areas and eliminating strenuous tasks minimizes exposure to high healthcare costs and insurance claims. The direct cost of a single injury sometimes is enough to justify the cost of a safety upgrade.
The Bottom Line
Computer vision systems offer long-lasting benefits and high business ROIs to manufacturers. With many advancements, technology is further transforming its ROI potential for companies. However, not all factors may lead to financially quantifiable calculations, and using the right mix of reliable direct and indirect factors will help them reach the optimal outcome.
