Simple introduction of Awesome Intelligent Technology’s micro loss-in-weight scales
Release time: 2025-05-07
Awesome Intelligent Technology’s micro loss-in-weight scales are tailor-made for laboratories and small production lines with breakthrough technology, combining the three core advantages of “miniaturization, high precision and intelligence” to provide more efficient and flexible weighing solutions for manufacturing enterprises and scientific research institutes, and to help reduce costs, increase efficiency and optimize space.

This product adopts miniature flow sensor and high-precision dynamic compensation algorithm, which breaks through the volume limitation of traditional loss-in-weight scales, and can stably measure micro-quantities of materials, which is especially suitable for micro-quantity proportioning scenarios such as raw materials of pharmaceuticals, food additives, and chemical powders. The innovative modular structure reduces the volume by 50% compared with the traditional equipment, and the weight is less than 8kg, which high-precision loss-in-weight feeder can be easily embedded into the narrow experimental bench or automated production line, completely solving the problem of space occupation.
Traditional loss-in-weight scales are bulky and complicated to install, making them difficult to adapt to laboratory or small workshop environments. With its compact design and plug-and-play interface, this product can be quickly plugged into an existing production line or used independently, and is suitable for:
- Laboratory R&D: trace component analysis, sample preparation;
- Fine chemicals: continuous feeding of high value raw materials;
- Food and pharmaceuticals: small batch, multi-batch production;
- Save 60% space: free up valuable space in labs and workshops and reduce site costs;
- Reduce energy consumption by 30%: High-efficiency motor and low-power consumption design, more economical for long-term use;
- Zero maintenance burden: modular components support quick replacement and reduce downtime by 80%.