May 17, 2026 Leave a message

Which technologies are most difficult to overcome in electronic scales?

Underlying Materials and Processing Technology of Weighing Sensors
Traditional metal foil strain gauges rely on organic adhesive layers to transmit force signals. The inherent defects of these adhesive layers-creep, aging, and moisture absorption-have long remained unresolved, leading to large zero-point drift and short dynamic fatigue life. The manual bonding process also struggles to guarantee consistency in large-scale production. The alternative, MSG glass micro-fused MEMS chips, require wafer-level mass production with atomic-level rigid bonding of "silicon-glass-metal," demanding extremely high standards for sintering temperature control and material purity. This is a recognized core technological barrier in the industry.

 

High-Precision Signal Processing Technology in Complex Environments
The raw weighing signal of an electronic scale is typically only a few millivolts. In complex industrial environments with electromagnetic interference, power frequency interference, and extreme temperature differences from -55℃ to 200℃, completely filtering out noise and controlling temperature drift and nonlinear errors within tens of thousands of volts requires simultaneous optimization of low-noise amplifier circuits, high-precision 24-bit ADC design, and dynamic temperature compensation algorithms. Even slight errors can lead to accuracy drift, making this the most difficult technical aspect to stabilize in mass production.

 

High-Reliability Anti-Interference Hardware and Mass Production Consistency

Technology Achieving complete isolation between analog and digital areas in PCB routing, eliminating ground loop interference through single-point grounding, while also considering the low power consumption and battery life of portable devices, requires standardized processes to ensure high consistency in the accuracy and anti-interference capabilities of each mass-produced device, avoiding quality fluctuations caused by component discreteness. This places extremely high demands on supply chain management and process refinement.

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