Building on the AI/ML Foundation with Image Analytics & Predictive Maintenance

From multiple Hadoop distributors battling it out for market share to create large data lakes for consolidating the space into a single solution provider and remain a contender in the data ecosystem—there is no question about the incredible speed in which the data and analytics space continues to evolve.

This evolution has forced many organizations to refine (and sometimes redefine) their data and analytics strategy to ensure that the tools, solutions, and processes align with the business’s needs.

New and innovative solutions and means of automating processes have created opportunities to use data in new ways and collect through various imagery types while analyzing massive volumes of data at a staggering pace.

Below we uncover how these modern solutions have positively impacted the manufacturing industry.

Image Analytics

Image analytics has seen tremendous advances as organizations leverage this process to extract meaningful information from images through digital imaging processing techniques.

It helps improve operational efficiency, enhance near real-time decision-making, increase employee productivity, reduce cost, and limit potential physical harm to employees.

For example, let’s look at an analog meter or an LCD that a system can read, decipher, and use in calculations.

There are many instances in a manufacturing environment where operators read displays on machines that don’t have an automated capability to send/receive information and make decisions on machine operations.

Enter AI/ML and imagery.

We now have a “lens” to read the analog or digital displays, make the necessary decisions to keep that machine in operation and keep the Overall Equipment Effectiveness (OEE) as high as possible.

Lasers and Thermal Imagery

While the human eye can detect many imperfections, lasers and thermal imagery can see even more.

We can use acceptable standards to look at the manufactured items to determine if they meet the appropriate standards.

Rejecting substandard items before being sold or distributed reduces costs associated with returns and negative customer satisfaction (a single unfavorable tweet can cost thousands of dollars to remediate).

Consider the use of imaging in the manufacturing of automobiles.

Many auto plant tasks are now automated, especially those considered dangerous, such as welding.

Now, a robot completes the frame’s welds, which are then inspected using standard and thermal imaging to ensure that the frame has been appropriately constructed and meets all safety specifications.

Image Analytics & Predictive Maintenance

Now that we understand how AI/ML with imaging makes manufacturing more cost-effective, we can introduce the idea of Predictive Maintenance (PdM). It leverages data analytics and AI-ML algorithms to proactively detect equipment failure before even they can occur.

Some of the types of predictive maintenance techniques include vibration analysis, oil analysis, and infrared thermography. These, along with other techniques, form the predictive maintenance toolbox, which can enable proactive maintenance strategies. Regarding predictive maintenance vs condition based maintenance, conditional maintenance is reactive and done only when necessary and different types of predictive maintenance is done proactively, which increases the equipment lifespan.

Predictive maintenance has a significant impact on the use of image analysis software. Image analysis software can analyze equipment images to identify any changes in running conditions and check for any failures, such as cracks in metals or the blade condition of turbines.

We know that machines need maintenance to continue to operate and that it costs less to maintain that machine than it does to fix it once it breaks.

Image analysis software can visually (or thermally) inspect various items to determine if some intervention is necessary before a failure occurs.

Our most recent IoT and Predictive solution development help a major industrial client quickly analyze part-specific information (service life, material characteristics, etc.).

Utilizing image analytics to enhance visual inspections of equipment, improve the inspector experience, and enhance the streaming data’s analytic value.

Various industries and areas can leverage different types of imaging.

There are many circumstances where inspection would be unsafe for humans, such as the interior of certain sections of a nuclear power plant or the stern of an oil tanker while it is still at sea.

In such circumstances, drones can play an integral part.

Consider agriculture—drones can inspect large acreages for damage after a storm or blight caused by insects.

As the number of resources working at a farm becomes scarcer due to the pandemic, this imaging can help save the crop.

The Marriage Between AI/ML and Imaging Systems

These advances are happening at a more rapid pace than ever before.

Given our current circumstances due to the pandemic, the need for this type of evolution has never been more imperative.

These innovations improve our quality of life by reducing faulty materials, increasing the useful life of certain items through an enhanced PdM, and replacing the reductions in the availability of human resources.

The marriage between AI/ML and imaging systems supports the economy and the population, and the benefits of such technology will last long beyond the pandemic.


1. What is an analytics image?

It is a pre-configured image or a virtual machine image that has software tools and services for data analytics.

2. What is the use of image analytics?

Image analytics is way of analyzing and extracting information from digital images using software tools.

3. How do you analyze an image?

Analyzing an image has the following steps. Preprocess the image to improve its quality. Use algorithms to segment the image based on structures or features. Extract features such as size, shape, etc. Classify the features and then Visualize the results in histogram, scatter plots, or heat maps.

4. What are the advantages of image analysis?

Image analysis is used for applications in healthcare, life sciences, manufacturing to derive valuable insights from data and make informed decisions.

5. What apps do you use for image analysis?

Some of the apps used for image analysis are ImageJ, CellProfiler, Fiji, OpenCV, MATLAB, Image-Pro, and ENVI.

6. What are the two types of image analysis?

The two types include Qualitative image analysis which is more aesthetically oriented and used in arts, Quantitative image analysis is focused on extracting numerical data from an image and used in scientific and engineering fields.