This paper addresses the pain points in the traditional service model of the blown film equipment manufacturing industry, such as slow pre-sales response, scattered equipment monitoring, cumbersome after-sales processes, and inconvenient accessory procurement. It designs and implements a customer service management system that spans the entire customer lifecycle. The system adopts a microservices architecture combined with edge computing, integrating four core modules: intelligent customer service powered by a large language model, AI image recognition for accessory purchases, intelligent equipment monitoring, and digital after-sales service, to establish a data processing system that facilitates edge-cloud collaboration. Each device is equipped with an independent edge computer to handle monitoring, computing, and alert functions, capable of operating offline and reporting critical status, alarm events, and aggregated data to the cloud database. The system supports access through both the web and WeChat mini-programs, with the expectation to support concurrent monitoring of over a hundred devices and concurrent access by hundreds of users. The AI customer service response time is controlled in seconds, and the accuracy rate of accessory image recognition exceeds 90%. This provides a reference implementation path for the service digital transformation of similar equipment manufacturing enterprises.