Manufacturing Flow Data Correlation Across Product Lifecycle Phases
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Solution Overview
Problem
Current data extraction methods in aerospace manufacturing flows are manual, time-consuming, and prone to errors, especially when dealing with complex object data from advanced fabrication equipment, which can lead to siloed data and reduced value of generated data.
Innovation Solution
A method and computing system that automatically collect and correlate various data types, including object data, observational data, and text data, from multiple devices across different product lifecycle phases, determining product lifecycle data and storing it for analysis of the manufacturing flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual data entry is used to collect data from multiple machines, then data can be consolidated for lifecycle tracking, but the process becomes time-consuming and impractical for machines generating large quantities of detailed data
Solution Approach 1:
The patent replaces manual mechanical data entry with automated electronic data collection systems. Sensors and machine interfaces automatically capture process data, while software systems electronically transmit and consolidate information across multiple machines, eliminating the need for manual data gathering and entry operations.
Solution Approach 2:
The patent introduces intermediary software systems and data platforms that act as mediators between multiple machines and the central lifecycle tracking system. These intermediaries automatically collect, standardize, and transmit data from various machine sources, enabling seamless data consolidation without manual intervention.
2Extent of automation
If historians are used to extract data from machines, then data extraction is automated, but historians are generally configured for text data and cannot facilitate integration of complex data types into lifecycle data
Solution Approach 1:
The patent creates a universal data integration platform capable of handling multiple data types including text, images, videos, and sensor data from various machines. This system serves multiple functions: collecting data from different sources, processing various data formats, and integrating them into a unified lifecycle tracking framework, replacing the limited text-only capability of traditional historians.
Solution Approach 2:
The patent transforms the data handling capability by changing the parameters of data acceptance and processing. The system accepts and processes complex data types with varying formats and structures, converting them into standardized representations that can be integrated into lifecycle data, thereby expanding the system's adaptability beyond text data.
3Loss of information
If data is collected from multiple fabrication machines, then comprehensive lifecycle data can be obtained, but the data becomes siloed with each machine unaware of processes performed by other machines
Solution Approach 1:
The patent merges data from multiple previously siloed machine systems into a unified lifecycle tracking platform. The system combines process data, sensor readings, and operational information from various fabrication machines into a single integrated dataset, enabling comprehensive lifecycle tracking while maintaining data reliability through centralized management and validation.
Data Source
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AI summary
One example provides a method of monitoring a product moving through a manufacturing flow being performed across a plurality of product lifecycle phases. The method comprises obtaining (402), by computer network from a first device (106) in a first product lifecycle phase, first object data (200) related to a first process performed by a first device (106) on the product, and obtaining (404), by the computer network from a second device (108) in a second product lifecycle phase, second object data (200) related to a second process performed by a second device (108) on the product. The method further comprises determining (412) product lifecycle data (118) for the product based on the first object data (200) and the second object data (200). The method further comprises storing (418) the product lifecycle data (118) for analyzing the manufacturing flow across the plurality of product lifecycle phases performed on the product.