Most of today’s factory production lines have experienced a transition from manual-intensive mode to semi-automation to full automation. However, there are also many manufacturers who have gradually completed digital transformation (Digital transformation) and even begun to promote intelligent production models (Intelligent / Smart manufacturing).
Regardless of digital or intelligent production, what elements do factories need to have to be qualified to meet the production requirements of today’s customers and factories? Based on our customer experience, Datacube shares the following elements for comparison:
- Deploy a large number of sensors (Sensors)
- Perform big data (IoT) analytics
- Use Machine Learning
- Use cloud ERP to manage inventory, production lines, and customer relationships
- Extract operation’s data, and apply it into whole production management
- 3D printed molds
- Establish a predictive methodology to respond to machine maintenance and tool losses in advance
- Build AR/VR to let customers understand the finished simulation product
Since the above elements are included, how should the factory bosses act further ?
- Production machines and tools cannot be stale, they must be expandable and can adapt to complex and changing environment in the production line.
- Establish a production culture and try to allow management and employees to exchange ideas
- In addition to the gradual integration of humans and machines, managers and workers must also have a deep understanding of customer requirements to help improve system optimization solutions together
- Develop digitalization strategies and schedules, train employees to adapt to advanced production processes and relevant knowledge
Generally, it takes at least 3-5 years to upgrade an intelligent system. Some factory leaders are worried about long-term investment, results, or colleagues’ doubts, so they hesitate to move forward. Therefore, we suggest that factories do not need to rush to implement it comprehensively, but can implement it gradually (part by part). Among them, Datacube firmly believes in using the help of big data and machine learning to effectively help customers drive production efficiency, so as to reduce costs, increase profits, and finally lead the competition.
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