Why 23DA:
Navigating the intricate landscape of modern manufacturing, from a product's initial concept to its final delivery, demands a blend of precision and efficiency. A key element in this journey is quality control, which heavily relies on advanced inspection technologies. Yet, a common and costly mistake for many leaders is choosing the wrong technology. This misstep can result in money wasted, costly downtime, and even damage to a company's reputation. There is no universal solution; each manufacturing operation, product, and process has distinct requirements, making a one-size-fits-all approach a recipe for failure.
The manufacturing sector is filled with examples of badly-suited technology implementations. A common mistake is not conducting sufficient research before making a purchase. A solution that appears perfect on paper may be challenging to integrate or may not consistently achieve the expected goal.
A prime example is the improper use of machine vision technology. When this technology first became available, many manufacturers were misled by unfulfilled promises, a problem that persists to this day. What works effectively for a thermoforming facility may be a poor choice for a metal machining shop. While the first may value the ability to inspect large products with moderate sensor resolution, the latter may require extremely high resolution when inspecting a much smaller field of view (FOV).
A common mistake is purchasing an overly complex solution for the job at hand. Leaders might invest in a very high-resolution camera to track the position of a feature in a small area, when a much more affordable camera paired with simple magnifying lenses could achieve the same outcome. The goal is to select the right tool for the specific task, not necessarily the most expensive one.
Another frequent choice is investing in a technology with hardware limitations that delivers suboptimal inspection performance. For example, when inspecting a tire tread, a 2D camera alone can confirm the pattern is present but cannot measure its depth due to sensor limitations. This is where 3D technology, which uses triangulation, becomes essential. By projecting a laser line onto the object and using a camera to capture the line's distortion, the 3D vision system can generate a precise 3D profile, providing critical information about the tread’s depth that a 2D system could not detect.
Lastly, manufacturers can invest in the right hardware technology, but encounter software limitations. A rules-based vision system may have sufficient resolution to detect a feature robustly, but be incapable of handling variations in product SKUs or lighting, which AI could address without generating false positives and scrap.
The Bottom Line:
Manufacturers have diverse needs, and selecting the right technology requires a deep understanding of the application. Factors such as target size, field of view, specific inspection goals, and future changes in the manufacturing setup (among others) must be thoroughly analyzed. A solution that works today may not be scalable for tomorrow's production needs.
This is where a company like 23DA can help. Instead of pushing for a single product, 23DA aims to promote innovation by recommending the objectively best-fit technology for each manufacturer's unique requirements. By prioritizing a deep understanding of the application over a quick sale, 23DA can help leaders make smarter, more sustainable investments.