Machine Tool Data Model Adaptation Without Runtime Translation
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Solution Overview
Problem
The existing methods for operating machine tools face inefficiencies due to the mismatch between specific and generic data models, leading to architectural disadvantages and performance losses, especially when expanding functionality through cloud-based additional functions without knowing the machine's internal architecture.
Innovation Solution
A method where a machine tool is connected to an external server with a generic data model that is translated and modified based on user requests to create a specific data model, allowing the external server to handle the data transformation outside the machine tool's runtime, thus relieving computational effort and improving performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a generic data model is used in the external server for cloud-based applications, then adaptability and versatility are improved, but manufacturing precision deteriorates due to mismatch with the specific machine tool data model
Solution Approach 1:
The patent applies preliminary action by pre-compiling the specific data model into a precompiled data model that is stored in an database. When a user requests machine tool data, the system retrieves the precompiled data model instead of performing real-time translation. This advance preparation eliminates runtime conversion overhead and ensures data precision while maintaining adaptability through the generic data model interface.
2Manufacturing precision
If data model translation is performed within the machine tool at runtime, then manufacturing precision is maintained, but productivity deteriorates due to computational overhead
Solution Approach 1:
The patent extracts the computationally intensive data model translation process from the machine tool's runtime environment. The specific data model is pre-compiled into a precompiled data model and stored in an database accessible by external servers. This extraction removes the translation overhead from the machine tool's operational workflow, significantly improving runtime performance while preserving data accuracy through the pre-compiled model structure.
3Adaptability or versatility
If the machine tool's internal architecture is modified to support cloud-based apps, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary mechanism in the form of a precompiled data model that acts as a bridge between the generic data model used by cloud-based applications and the specific data model required by the machine tool. This intermediary layer allows the machine tool to maintain its existing internal architecture while still supporting cloud-based apps, thereby improving adaptability without increasing device complexity.
Data Source
Figure 1
AI summary
The invention relates to a method for operating a machine tool and a corresponding machine tool system (20). According to the invention, a generic first data model and engineering data (17) are first of all provided in an external server device (18). The engineering data (17) contain information specifically relating to a machine tool (10). After a user query regarding an operation of the machine tool (10), the first data model is translated and/or modified to become a second data model. This occurs in accordance with the engineering data (17) and technical data of the user query by the external server device (18). The second data model is transferred from the external server device (18) to the machine tool (10), and a control unit (16) of the machine tool (10) can operate the machine tool (10) according to the second data model. The machine tool (10) can thus be adapted outside the running time of the machine tool (10).