Object Graph Quality Control System
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Solution Overview
Problem
Current quality control processes in product development are time-consuming and resource-intensive, often resulting in the generation of thousands of documents that make it difficult to locate specific quality improvement information, leading to inefficiencies in resource utilization and information retrieval.
Innovation Solution
A computer-implemented method and system that organizes quality control information using an object graph, facilitating the reuse of existing data and reducing redundant information, thereby minimizing memory and network traffic, and enabling efficient specification and adherence to quality control procedures through a user interface that encourages the use of previously specified quality control information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional quality control processes are used to ensure comprehensive quality monitoring, then quality control coverage is improved, but the quantity of documents generated increases significantly making information retrieval difficult
Solution Approach 1:
The patent segments quality control information into structured data elements (process requirements, control parameters, sensor data, potential causes of failures) organized in an object graph database. This segmentation allows specific quality control information to be retrieved efficiently without searching through thousands of unstructured documents, thus maintaining comprehensive quality control coverage while improving information retrieval efficiency.
2Reliability
If traditional quality control activities are performed to ensure thorough process monitoring, then quality assurance is improved, but time consumption and human resource investment increase significantly
Solution Approach 1:
The system implements self-service quality control by automatically collecting sensor data from the manufacturing environment, comparing it against control parameters and process requirements stored in the object graph, and generating alerts for potential failures. This automation eliminates the need for manual document review and human analysis of quality control data, maintaining thorough process monitoring while significantly reducing time consumption and human resource investment.
3Reliability
If comprehensive quality control documentation is created to track all process aspects, then quality traceability is improved, but device complexity and resource requirements increase
Solution Approach 1:
The patent implements a universal object graph database structure that stores all quality control information (process requirements, control parameters, sensor data, potential causes of failures) in a single integrated system. This multi-functional database serves multiple purposes: tracking quality parameters, identifying potential failures, generating alerts, and providing traceability. This approach maintains comprehensive quality traceability while reducing system complexity compared to separate documentation systems for each quality control function.
Data Source
AI summary
A computer-implemented method includes receiving process information that specifies one or more process requirements and one or more potential causes of failures associated with processes for manufacturing a design, ii) control information that specifies one or more parameters and one or more values associated with the one or more parameters that facilitate determining whether the one or more process requirements specified in the process information that are associated with the processes are being met, and iii) sensor data associated with the one or more parameters from one or more sensors of a product development environment. Responsive to determining that sensor data associated with a particular parameter of the control information is outside of an associated range of values, a process requirement and a process associated with the parameter is determined based on the process information and the control information.