Optimize automotive manufacturing quality and operations
Against the backdrop of improving production efficiency and reducing manufacturing operating costs, the automotive manufacturing industry is increasingly adopting the digital transformation of manufacturing production based on the combination of IT and OT industrial IoT technologies. By adopting IoT technology, automotive manufacturers can obtain a large amount of real-time data and use it to optimize production, detect faults, and predict maintenance, thereby improving production efficiency, reducing costs, improving product quality, meeting customer needs, and maintaining competitive advantages.
Challenge
Optimization of operational efficiency
Without IoT technology support, automotive manufacturers may struggle to optimize their production processes, leading to inefficiencies, wasted resources, and increased costs.
Product quality improvement
Without real-time data collection and analysis, it can be difficult to identify and address quality issues in a timely manner, leading to product defects and recalls.
Customer demands
Consumer demand for cars is also constantly changing, and they are paying more attention to aspects such as safety, convenience, comfort, and environmental performance of cars, which also prompts automakers to continuously improve product design and production processes.
Increased maintenance costs
Without real-time data on production equipments, automotive manufacturers may need to perform more frequent and costly maintenance to ensure equipment reliability, leading to increased costs.
Solution
EMQX IIoT solutions can help meet the digital transformation needs of the automotive manufacturing industry by providing efficient and flexible access to data from heterogeneous industrial equipment.
Neuron, the edge industrial protocol gateway software, supports various industrial protocols such as Modbus, OPC-UA and most mainstream PLC protocols enabling efficient data access from various equipment. The real-time data collected is processed at the edge using eKuiper, a lightweight edge streaming processing engine, which provides high-quality data source for edge AI inference services. The lightweight deployment and SQL-based edge streaming data processing effectively reduce cloud-side transmission costs, enabling real-time data response at the edge.
EMQX provides large scale data access and provides various data interfaces, data persistence, and message queue integration capabilities, along with standard RESTful APIs for external application integration. This enables integration with other business systems such as ERP and CRM, allowing for more valuable analysis results. With EMQX ECP (Edge to Cloud Platform)，EMQX IIoT solution can easily manage multi-location, multi-Cluster distributed deployment, providing flexible and diverse edge cloud data channels.
Results
- Optimization of production processes: Real-time data collection and analysis can optimize production processes, improve production efficiency, and product quality.
- Cost reduction: By analyzing data and predicting maintenance, equipment failures and downtime can be avoided, thereby reducing maintenance and production costs.
- Improved customer satisfaction: Real-time monitoring of vehicle status and providing personalized services can improve customer satisfaction and loyalty.
- Rapid response to market demand: Real-time data analysis and production plan adjustments can enable faster response to market demand and meet customer's customized requirements.