Automated Testing 101

May 17, 2024
min read
Tak Alguire
Co-founder & CEO of Serial
Table of Contents


Consumers have sky-high expectations for the quality and reliability of electronic products. Companies like Apple and Samsung have made this possible largely due to their extensive quality control practices that minimizes defective parts from ever reaching the consumer. This is largely due to in-process quality control and advanced automated test equipment. These high-speed test machines can have now become commonplace and ensure that products are of the highest visual, dimensional and functional quality. Lets dive into the intricacies of functional test equipment. 

Evolution of quality control in manufacturing

Quality control has been an integral part of manufacturing throughout history. 

Pre-Industrial Age

In 3000 BC the Egyptians used cubit rods as a form of ruler to maintain uniformity in their construction blocks. This is a rudimentary example of using a measuring technique to maintain quality.

In 1100 AD the venetian arsenal was producing a ship a day, they used one of the earliest examples of the assembly line, in conjunction with distinct guilds for carpentry, caulking and oar making. Each guild passed along specific training to their recruits with enforced quality control. This is an early example of standardization and process control to improve quality. 

The Assembly Line

In 1914 the modern assembly line introduced 84 discrete steps to assemble a single vehicle. A technology breakthrough at the time, but also introduced 84 highly repetitive tasks each with their own opportunity for human error. 

In the 1960s Poka-Yoke came out of Toyota as a way of mistake-proofing manufacturing steps, so only one order of operations was possible, thus minimizing the impact of human error. 

By the 1980s manufacturing precision became so capable that manual measurement became a new source of error, the contact measurement machines started becoming more common as a human assisted machine to accurately and precisely measure parts. 

Last 20 years

In the past 20 years automated optical inspection (AOI) has become a common technique to check for visual defects. Similarly, advancements in cameras and lasers have unlocked high-speed dimensional inspection, something that has historically been limited to low-speed contact measurement machines CMMs. 

Automated test equipment has become more common out of necessity. The complexity of products has increased exponentially over the years, and simply relying on human only training or testing is no longer possible. 

Benefits of Automated test equipment

Automated testing introduces a number of benefits for manufacturing operations. Lets walk through an example of these benefits using the 2D drawing below as the device under test (DUT).

Increased accuracy & precision

A human could manually measure these dimensions using calipers or a micrometer, however the measurement locations would vary from part to part. Additionally, some of these dimensions are near impossible to measure manually as they reference datums that need to be constructed.

Minimize human error

There are also many opportunities for the human to make a mistake, measuring from the different locations part to part, using a different measuring tool or even the mood the operator is in. While a CMM follows a pre-programmed procedure to complete the measurement. There is still a risk that the operator loads the CMM incorrectly or the wrong measurement probes are used, however these can be addressed using existing poka-yoke and six sigma techniques.

More testing capacity

If a human were to measure every dimension on the drawing then it would take them probably 20 minutes to complete. Scale this to the volume of the product and it quickly becomes expensive to measure every dimension. A combination of an industrial camera and 2D laser could complete all of these measurements in a matter of seconds. Thus increasing the testing capacity. Of course there are other ways to reduce the number of dimensions that need to be controlled such as only measuring dimensions that are not process capable. 

Early detection of defects 

Companies can take advantage of the digital data and apply statistical process control in realtime, thus enabling companies to detect deviations earlier in the process. Going back to the CMM example, it is common for some industries to sample a subset of parts in a shipment and measure them on a CMM to ensure quality from their suppliers. Evaluating this data in real time enables these companies to catch defects before the entire batch is consumed thus preventing millions of dollars of rework or scrap.

Types of automated testing equipment

There are many different types of automated testing equipment. Let's briefly review some of the common types: 


Dimensional measurement equipment has become a massive segment of automated testers: CMMS, cameras, laser profilometers, confocal sensors and interferometers are some of the common technologies. CMMs and optical measurement machines OMMs often come fully integrated and ready to be programmed. While the other technologies typically require an integrator in order to take full advantage of their capabilities. 


Electrical testers are very common in the PCB testing industry. Testing voltage, current and resistance of various components or pinout continuity. Modern PCB manufacturing lines can often assemble and test the entire PCB in a single machine without any human intervention. 


Environmental testing is common during the reliability testing process. Thermal shock chambers rapidly vary temperature. Humidity chambers can measure the impact of humidity on a product. Salt spray chambers test the corrosion resistance of materials, emulating ocean spray. 


Functional testers test the functional performance of the product to confirm the product is operating as intended. These types of testers are often custom as the function of the product is specific to the manufacturer.

Considerations when implementing automated test equipment

There are key considerations when considering the implementation of automated test equipment. 

Technical requirement

Is absolutely necessary quality control the specific metric the tester can measure? What is the technical risk associated with not using automated test equipment? Is it possible to manually control quality? Can the parameter be process controlled instead? Depending on these answers it may not even be necessary to implement automated testing. 

Initial Investment

The financial investment to purchase, house and operate the equipment is the primary detractor from automated equipment. In many cases these machines are investments that can be leveraged on future projects, CMMs and OMMs fall into this category. Other equipment can often be reworked for a smaller investment to adapt to new projects. In either case a significant budget is required to proceed with automated testing. 

Integration & Training 

Integrating new equipment into any manufacturing line is tough, automated testers are no different. The added challenge for manufacturing equipment is the qualification to trust the results. In most companies there is a golden measurement machine typically a CMM, while new equipment is correlated to the CMM. For other equipment it typically requires testing parts on the new equipment and mailing the same parts to external labs to verify the results. Once qualified there is the challenge of training the workforce on how to operate the equipment. Some equipment is as simple as loading the machine and hitting go, while others require extensive software setup. 

Final Thoughts

Automated test equipment has become common in the modern manufacturing environment. These testers introduce clear accuracy and efficiency benefits compared to their manual counterparts, at the expense of increased cost and complexity. Companies that operate automated test equipment must fully leverage the data output of the equipment to feedback into the design and manufacturing lifecycle. 

Tak Alguire
Co-founder & CEO of Serial

Tak is the Co-founder & CEO of Serial. He has over 5 years of experience in manufacturing operations, notably working on the iPhone, Apple Watch and Vision Pro. He has firsthand experience deploying large-scale manufacturing data tools to empower engineers to make data-driven decisions. Now he wants to help all engineers save time and effort.