Client Background and Needs
To drive the transformation of traditional production lines toward smart manufacturing, Riwei Technology planned the development of a “Machine Data Collection System.” This system could integrate with smart set-top boxes (SMB) and Industrial IoT (IIoT) platforms to enhance production transparency and digital management—upgrading conventional production lines into smart, data-driven operations. The challenge of this project was how to balance functional design, system stability, and environmental reliability to ensure the solution could be practically deployed and generate real value.
Magnus Solution
Magnus participated in the development and optimization of the system in the role of ODM manufacturing and electronic manufacturing services (EMS):
● Data acquisition module: accurately collected process parameters, machine data, and operating status, providing the foundation for process optimization, quality control, and predictive maintenance.
● PCB design: developed a central Data Acquisition module to ensure secure and stable transmission of data to the cloud platform.
● OEM manufacturing services: conducted testing and system integration to guarantee reliable deployment and real-world application in factory environments.
Project Outcome
With Magnus’s support, Riwei Technology successfully launched its Machine Data Collection System, enabling enterprises and factories to:
● Monitor equipment status in real time, increasing production line visibility.
● Make more accurate decisions based on real-time data.
● Improve production efficiency while reducing operating costs.
● Establish predictive maintenance capabilities, extending equipment lifecycle.
Through this project, Magnus provided product development services in electronic system design and manufacturing, helping Riwei Technology deliver a customized solution for smart production. This system can now be promoted across factories and enterprises, supporting them in optimizing workflows, enhancing production transparency, and driving data-driven decision-making.