How Open Data Could Facilitate Automation for the Electronics Industry
Even though the electronics industry is familiar with automation, many companies need more resources to mechanize their processes. In response, open data is leveling the playing field — and ultimately revolutionizing the sector.
What Is the Significance of Open Data?
The Biden Administration authorized the Defense Production Act in March 2023 to increase the domestic production of printed circuit boards (PCBs) and various other microelectronics. While it’s mainly incredible news for those working in the electronics industry, the upcoming manufacturing acceleration highlights the need for an evolution of automation.
The act marks the beginning of a turning point for the sector and creates a unique opportunity for them to capitalize on the latest digital innovation. More specifically, they have the chance to utilize open data fully.
It’s foundational for many automation technologies. For example, PCB manufacturing typically relies on artificial intelligence (AI) sensors for quality inspection. While it’s a relatively reliable method once it’s operational, it can be challenging for companies to produce a successful algorithm.
The need for extensive AI training is one of the most significant obstacles to the process because most sources aren’t comprehensive or organized. Obtaining and combining the available information can be incredibly resource-intensive, so it often isn’t feasible. The industry needs a solution — and open data may be what they’re looking for.
Why Does the Industry Need Open Data?
The term refers to the amount of information people produce daily. Algorithms rely on large volumes of text, images, or videos to recognize patterns and be useful in electronics manufacturing. Most automation models operate on big data.
The electronics industry can only innovate with the automation capabilities of AI if it has a complete collection of relevant text. While businesses could form their own, it often takes extensive resources. Think of it like how a thermostat can automatically change the temperature according to its programming — it needs historical data or purposeful input to be of any use.
Even though many have access to operational statistics, they have no way of using them. For instance, machines on the shop floor constantly generate operational information that could give higher-ups a data-driven overview of factory functions. They technically have a wealth of relevant details but don’t utilize them. In fact, manufacturers in the electronics industry rarely collect or analyze information even though they produce more daily.
Doing so would be incredibly beneficial, as they could use it to improve productivity or streamline the assembly line. However, manufacturers can only gather it with the right equipment, which may be out of their budget.
Can Open Data Address Automation Barriers?
For the most part, organizations in the industry still have yet to utilize automation to its fullest extent. For instance, PCB engineering is largely manual, even though a fast production pace is critical for electronic manufacturing. AI can help them, but many still need better access to training data sets.
Typically, companies looking to automate with AI face various entry barriers — the most significant being that an algorithm requires a massive amount of information to learn effectively. Often, they can’t source enough to train it properly.
Relevant, accurate and up-to-date data is critical for success because it affects the final product. Businesses training their AI with incomplete or low-quality text or images will end up with a subpar model, ultimately affecting its performance and value.
Even though there’s a massive amount online, much of it is relatively inaccessible or low quality. In addition, it’s virtually useless in its raw form — algorithms and humans can only decipher it if it’s in the correct format. Most companies in the electronics sector need access to a large, organized and free source to be able to automate operations effectively.
How Is Open Data Revolutionizing Automation?
The benefit of an open source is primarily accessibility — organizations no longer have to invest in expensive resources to find information. They can simply find statistics, photos or relevant operational figures online.
Additionally, open data allows for more differentiation, which could help accelerate electronics production. For example, it would give them greater access to defect samples of PCBs, ultimately improving the accuracy of their automation technology.
There are plenty of free resources companies can utilize. For example, a Canadian research organization has an extensive collection of data repositories anyone can access for free. Even though it doesn’t offer many texts specific to electronics engineering, similar online platforms have more relevant figures.
In addition, institutions with public funding often provide free open data. For example, the United States National Aeronautics and Space Administration uses its simulator to generate data and produce research sets. The information is technically synthetic, but it’s relevant and accurate nonetheless.
How Can Companies Approach Open Data Use?
Companies even leverage automation tools to produce their own open data. For example, they could use a generative text model to manufacture a synthetic collection. Since it can supplement research gaps, they can use it to streamline their automation processes.
The benefit of this technology is it can understand language and independently create content. Plus, it needs massive amounts of information for teaching purposes, meaning it has likely already processed terabytes of raw data. Many of these algorithms have open-source training details, which lets organizations in the electronics sector confirm their validity and accuracy.
The Innovation of Open Data
The combination of real and synthetic open data could revolutionize automation in the electronics industry. It makes innovations accessible to any business in the industry, which is an incredible achievement, especially regarding the recent push to accelerate microelectronics domestic production.