What is ATE?

Meta: Learn about what ATE is and how efficiency can be increased while controlling costs using Automated Testing equipment for various industries

As most people in the industry know, there are distinct differences between manual testing and automated testing. Manual testing requires physical time and effort to ensure the software code does everything it’s supposed to do. In addition, manual testers have to make a record of their findings. This involves checking log files, external services and the database for errors. If you’re familiar with manual testing, you know this process can be extremely time-consuming and repetitive.

Automated testing or test automation is a method in software/hardware testing that makes use of special software tools to control the execution of tests and then compares actual test results with predicted or expected results. All of this is done automatically with little or no intervention from the test engineer. Automation is used to add additional testing that may be too difficult to perform manually.

The objective of automated testing is to simplify as much of the testing effort as possible with a minimum set of scripts. If unit testing consumes a large percentage of a quality assurance (QA) team's resources, for example, then this process might be a good candidate for automation. Automated testing tools are capable of executing tests, reporting outcomes and comparing results with earlier test runs. Tests carried out with these tools can be run repeatedly, at any time of day.

Why is ATE required?


When a particular decisive device’s performance and results are going to matter a lot to the final overall outcome, it becomes important that the decisive device in consideration performs accurately as it is designed for.

Just like a projection Airbag in an automobile, before launching any new vehicle, car-manufacturing companies perform umpteen numbers of tests on their automobile to check their efficiency. Accuracy and precision are the two important factors in the scientific world, where a difference of a decimal point can cause the whole cost of the project and time invested in it to go for a toss.

Automated Test System


Automated Test System consists of a master controller that detects and analyzes the data procured during the tests. The device also can compare the test results, where one is already fed into the system and the other is being captured from the Device Under Test (DUT).

These ATE’s consists of custom-designed controllers or relays to do all the processing of the data. The Device Under Test is physically connected to the ATE’s via wires or robotic machines and to a customized Interface Test Adapter (ITA) as per the scope of the project and requirements.

This mechanism, in general terms, is as simple as connecting battery wires to a DC motor to see whether it is working on it or not and then taking the RPM readings.Please note that all the connector devices may or may not be used all the time. It purely depends on the scope and requirements of the project. The principle aim is to check whether the desired outcome is achieved or not.

Advantages of Automated Test Systems

In the physical world around us, we do all sorts of testing, right from our bikes, our laptops and even our travelling bags to see whether they will be of use under duress when we need them the most. This helps us ascertain whether they provide us with the required level of functionality or not.

The simplest example would be as follows; a musician uses technology-enabled programs to check whether their devices are producing the exact sound or not, or to even see if there is any fault.

The results of Automated Testing determine whether the manufacturing unit meets the required specifications or not. Some of the numerous advantages that this system provides include the following:


Cover high percentage of modeled faults.

Increase Percentage Accuracy in Testing.

Minimize test time (to control cost).

No fault diagnosis.

Test at rated speed or the maximum speed guaranteed by manufacturer.

Generate reports for further analysis.

Meet standards as desired by the end customer.

Reduce human errors.

Increase turnaround.

Predict fault conditions based on adaptive learning of past tests.

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