Introduction
In the PCBA manufacturing process, the panel-cutting stage is often viewed as a final step in production. However, numerous field failure cases indicate that many latent quality issues actually occur during this stage. This is particularly true in areas with high component density, such as those containing BGAs, MLCCs, and large-size QFNs. If the stress generated during panel cutting exceeds the material's tolerance, it can lead to microcracks, solder joint fatigue, or even internal interlayer damage. These issues usually do not surface immediately during factory testing but gradually manifest after long-term operation at the customer's site or following vibration during transportation. Consequently, an increasing number of PCBA manufacturers are adopting strain gauge testing to quantitatively analyze the mechanical stresses incurred during the panel separation process.
Why Has Panel Separation Stress Become a Hidden Risk in PCBA Manufacturing?
In mass production of PCBA manufacturing, panelization design can improve SMT placement efficiency, but the panels ultimately still need to be separated using methods such as V-cuts, milling, or punching. The problem is that during the separation process, the PCB undergoes instantaneous bending and deformation, and this mechanical stress is transmitted along the board to the solder joints and the undersides of components. For standard through-hole components, this impact is relatively limited. However, for large-size BGAs, ceramic capacitors, or thin-profile PCBs, the risk is significantly amplified. Many PCBA manufacturing projects experience situations where "products ship normally but fail at the customer's end"; essentially, microcracks have already formed during the panel separation stage and simply propagate further under subsequent thermal cycling or vibration.
Strain Gauge Testing Quantifies "Invisible Stress"
Traditional PCBA manufacturing sites typically rely on visual inspections and functional testing to assess panel separation quality. However, mechanical stress itself is invisible, making it difficult to accurately assess risks based on experience alone. The core value of strain gauge testing lies in converting the deformation of the PCB surface during the panel-cutting process into real-time data. By attaching strain gauges to critical areas, the tensile and compressive changes at the moment of panel cutting can be recorded, generating a complete stress curve. This approach allows PCBA manufacturing engineering teams to determine the safety of the panel-cutting process based on quantified data rather than relying on subjective experience.
Areas Near Critical Components Are Key Focus Areas for Strain Testing
In PCBA manufacturing strain testing, it is not necessary to place strain gauges across the entire PCB. Testing typically focuses on areas surrounding high-risk components. Examples include the four corners of BGAs, areas near large MLCCs, connector pad areas, and components located near the board edges. These locations are most susceptible to bending stress during the depaneling process. Engineers apply strain gauges in critical directions based on the PCB structure and component layout, simultaneously recording dynamic changes during the panel-cutting process. Through data analysis, high-stress areas can be quickly identified, enabling the optimization of cutting paths and support methods.
Optimizing the panel-cutting process involves more than just replacing equipment, it requires adjusting the process logic
When many companies encounter panel-cutting cracks during PCBA manufacturing, their first instinct is to replace their equipment with higher-end models. However, in reality, equipment is only one of several contributing factors. What truly determines stress levels includes the design of panel connection points, board-edge support structures, the direction of panel separation, and toolpaths. For example, in some PCBA projects, adjusting the separation sequence can significantly reduce stress peaks, while adding localized support fixtures can effectively minimize board deflection. The significance of strain gauge testing lies in providing data feedback during these process adjustments, eliminating the need for optimization through trial and error.
Stress Control Standards Are Becoming a New Threshold for High-End PCBA Manufacturing
During the rapid iteration phase of consumer electronics, many panel-separation issues can still be addressed through after-sales service. However, in high-reliability fields such as automotive electronics, medical devices, and industrial control, panel-separation stress has been incorporated into formal audit standards. Some international clients require PCBA manufacturers to provide strain test reports and explicitly specify maximum allowable strain values. If test data exceeds these limits, the product may be deemed to pose a long-term reliability risk-even if it is currently functioning normally. This means that the panel-separation process has evolved from a "supporting process" to a critical component of reliability control.
From "Avoiding Cracks" to "Establishing a Comprehensive Stress Management System"
Currently, an increasing number of PCBA manufacturers are realizing that stress control during panel cutting cannot be limited to a single test but requires the establishment of a systematic management mechanism. Factors such as panel layout design reviews, planning of no-place zones for critical components, management of panel-cutting equipment parameters, and the accumulation of strain data directly impact long-term stability. Through the accumulation of long-term data, engineering teams can quickly identify high-risk structures and proactively avoid issues during the product introduction phase. This capability is, in essence, already an integral part of the PCBA manufacturing process system.
During the PCBA manufacturing process, many seemingly "sporadic" solder joint cracks are actually caused by long-neglected mechanical stress issues. Strain gauge testing makes it possible to visualize and quantify hidden risks during the panel separation process, shifting process optimization from empirical judgment to data-driven decision-making.
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