Industrial D&E Platform With Reusable Flow Blocks and Code Execution
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Solution Overview
Problem
In industrial data transformation, existing solutions face challenges such as inefficiencies due to reinvention of similar data transformation tasks, lack of transparency and feedback, high skill and licensing requirements, and complexity in customizing solutions for specific data transformation problems, leading to tedious manual handling and inefficient transitions from development to testing or execution.
Innovation Solution
A development and execution (D&E) platform providing a graphical user interface with a process flow editor and code editor, allowing users to arrange programming blocks, compile, and execute them individually or in combination, with features like caching output for seamless workflow, AI-driven recommendations, and community feedback mechanisms to improve solution customization and sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If engineers develop custom data transformation solutions using conventional software and programming languages, then the solutions can be tailored to specific data transformation problems, but the development complexity and time increase significantly
Solution Approach 1:
The system segments data transformation solutions into reusable, modular components stored in a solution repository. Each solution component can be independently developed, tested, and deployed. Users can assemble customized solutions by combining these pre-built modules through a graphical interface, eliminating the need to develop entire transformation pipelines from scratch while maintaining adaptability to specific requirements.
Solution Approach 2:
The system introduces an intermediary layer (the solution repository and graphical composition interface) between the user and the complex software development process. This intermediary enables users to create customized data transformation solutions by selecting and configuring pre-built components without needing to write source code or understand underlying software architecture, thus reducing development complexity while preserving customization capability.
2Adaptability or versatility
If engineers develop data transformation solutions using expensive licensed software and programming languages, then the solutions can be powerful and flexible, but the licensing costs increase
Solution Approach 1:
The system enables users to self-serve by providing a graphical interface and solution repository that allows them to create, customize, and deploy data transformation solutions without needing expensive licensed development tools or programming expertise. The platform includes built-in capabilities for solution composition, execution, and management, eliminating the need for external expensive software licenses while maintaining solution flexibility.
3Reliability
If similar data transformation solutions are developed independently by different engineers, then each engineer can solve their specific problem, but inefficiency occurs due to reinventing the wheel
Solution Approach 1:
The system creates universal, reusable solution components that can serve multiple data transformation scenarios. A single solution module developed by one engineer can be stored in the solution repository and reused by other engineers for similar or related problems. This multi-functional approach maintains problem-solving effectiveness while dramatically improving development efficiency by eliminating redundant work across the organization.
Solution Approach 2:
The system implements feedback mechanisms that track solution usage, performance, and success rates. When a solution is deployed and executes successfully, this information is fed back to the repository, making the solution available for others to discover and reuse. The feedback loop also enables continuous improvement of existing solutions based on real-world performance data, further enhancing their effectiveness and reusability.
4Ease of operation
If conventional development processes are used with manual source code compilation and execution, then developers have full control over the software, but the transition from development to testing is tedious and time-consuming
Solution Approach 1:
The system performs preliminary actions by pre-compiling and validating solution components before they are needed for execution. When users assemble solutions from the repository, the components are already in executable form. The system also pre-validates the correctness of solution compositions through automated checks, eliminating the need for manual compilation and extensive testing during the development-to-testing transition, thus reducing time loss while maintaining development control.
Data Source
AI summary
A method for providing access to a development and execution (D&E) platform for development of industrial software, including providing while the D&E platform is being accessed a GUI with a development tool having process flow and code editors and an execution tool and arranging two or more programming blocks of a process flow responsive to input from an author when the process flow editor is accessed. The two or more programming blocks, when arranged, are configured to be executed. The method further includes editing source code of the two or more programming blocks responsive to input from the author when the code editor is accessed, compiling at least one of the two or more programming blocks responsive to input from the author when the execution tool is accessed, and executing the compiled at least one programming block responsive to input from the author when the execution tool is accessed.