Automation of upstream production
Not only is the automation of production important, but the upstream steps are also a necessity.
Automation has revolutionized #production in recent years. But what about the process steps before that? 🤔
By using machine learning and data analytics technologies, companies can optimize their production processes and reduce costs. But automation not only affects production itself, but also the processes before it.
An important step in product development is the digital simulation of products. By using #3D modeling and simulation technologies, companies can develop their products faster and more cost-effectively.
They can virtually test how the product will perform in different environments and conditions before it is actually produced. As a result, design flaws can be identified and corrected early on.
There is also potential in production planning through automation. By using machine learning and data analytics technologies, companies can better plan and control their production processes. They can make forecasts for production demand and adjust their production capacities accordingly.
It is always important to look at the entire digital process chain. This includes not only the interaction within the company, but also with partners and customers. Without the right preparation and sensible processing, automation can
automation will fail at the data transfer stage.
Digital consistency in #engineering is the keyword here!
Overall, automation in the upstream steps of production still offers great potential for companies. What are the benefits?
✅ Increased productivity
✅ Increased competitiveness
✅ More focus on core competencies and R&D
Disadvantages? I don't see any. Do you?