As manufacturing moves toward intelligence, flexibility, and transparency, data interactions among production equipment, quality inspection systems, warehousing and logistics systems, and MES/WMS platforms are growing exponentially.
However, in real-world implementations, manufacturing companies commonly face the following challenges:
- Diverse and complex data sources: Device protocols, PLC data, MES/WMS systems, and edge-side collection systems all differ in format, making unified scheduling difficult.
- Difficulties in cross-system and cross-factory collaboration: Long data transmission chains and high real-time requirements exist between factories, production lines, and systems.
- Complex industrial scheduling logic: With many task dependencies and long chains, traditional scheduling tools often fail to meet industrial scenarios.
- Insufficient visualization and traceability: Industrial data collection pipelines lack transparency, making troubleshooting difficult.
- Unreliable data collection quality: Once exceptions occur, they are often hard to locate and hard to recover.
In today’s comprehensive industrial digitalization, more and more enterprises are asking: Is it possible to have an industrial-grade data scheduling system with high reliability, high observability, and cross-system collaboration support?
The emergence of Apache DolphinScheduler brings new possibilities for data collection and scheduling in manufacturing.
Apache DolphinScheduler in Manufacturing Data Collection Practices
To help more manufacturing enterprises better understand how Apache DolphinScheduler is implemented in industrial scenarios, we invited Qiu Zhongbiao, an intelligent manufacturing expert from a large manufacturing group in Shenzhen, to deliver an in-depth sharing session on industrial data collection and scheduling.
Through this livestream, you will learn:
- How Apache DolphinScheduler supports industrial scheduling logic
- How to improve pipeline reliability in cross-system and cross-factory data flows
- Real application solutions for material traceability and data collection in factories
- How DolphinScheduler deeply integrates with MES/WMS and industrial internet systems
- How open-source ecosystems and manufacturing technologies co-evolve under Industry 4.0 digital transformation
This session provides practical guidance for developers, architects, and digitalization teams working to build intelligent factories.
Speaker Introduction
Qiu Zhongbiao, Apache DolphinScheduler contributor, Senior Intelligent Manufacturing Software Engineer at a large manufacturing group in Shenzhen. He has long been responsible for MES, WMS, and industrial internet system development, specializing in industrial data collection, industrial scheduling, and system integration, with extensive real-world industrial cases and hands-on experience.
Event Topics & Agenda
This livestream will focus on “Hands-On DolphinScheduler for Manufacturing: Data Collection & Workflow Orchestration,” including:
- Common challenges in manufacturing data collection and scheduling
- Advantages and suitability of Apache DolphinScheduler in industrial settings
- Real manufacturing industry data collection practice cases
- Cross-factory and cross-system data flow and scheduling solutions
- Live QA and prize draw
The livestream covers theory, practice, and real cases, making it suitable for technical personnel, manufacturing IT teams, and digital transformation leaders.
Don’t Miss Out!
If you’re facing complex industrial data pipelines, cross-system collaboration difficulties, lack of scheduling visibility, or unstable data collection, this livestream will provide you with clear and practical solutions.
Join the livestream and learn the best practices of Apache DolphinScheduler × Intelligent Manufacturing with industry experts!
Schedule: 2025/12/19 19:00-20:00(Beijing Time)
Live Stream: https://meeting.tencent.com/dm/WdyFL7R0Jixa
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