Digital Engineering Data Threads for Manufacturing Waste Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems experience inefficiencies in the flow of data related to physical products, leading to wasted resources and reduced efficiency in manufacturing and product quality due to lost, duplicative, or inefficiently formatted data.
Innovation Solution
Applying data element mapping analysis to identify and prioritize data threads, adjusting a subset of these threads to improve efficiency by removing excessive or redundant data elements while preserving data flow order, and implementing an improved system architecture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data element mapping analysis is applied to identify and prioritize data threads, then manufacturing efficiency and product quality are improved, but system complexity and implementation time increase
Solution Approach 1:
The patent segments the data flow system into discrete data threads that can be individually analyzed, mapped, and optimized. By breaking down the complex data flow into manageable segments (data threads), the system enables targeted improvements without requiring complete system overhaul, thus improving productivity while controlling complexity.
Solution Approach 2:
The patent implements partial action by prioritizing and adjusting only the most critical data threads rather than attempting to optimize all data flows simultaneously. This approach allows for incremental improvements in manufacturing efficiency while avoiding the complexity and resource requirements of comprehensive system restructuring.
2Loss of energy
If redundant data elements are removed to reduce waste, then resource utilization improves, but data flow integrity may be compromised
Solution Approach 1:
The patent introduces data element mapping analysis as an intermediary mechanism that identifies and distinguishes between redundant and essential data elements. This intermediary analysis layer enables the systematic removal of waste while preserving data flow integrity by ensuring that only truly redundant elements are eliminated based on their impact assessment.
Solution Approach 2:
The patent implements feedback mechanisms that monitor data flow after adjustments are made. This feedback system ensures that removing data elements does not compromise data flow integrity by detecting and preventing removals that would negatively impact manufacturing processes or product quality.
3Productivity
If manual data transfer processes are automated, then productivity increases, but implementation costs and system complexity increase
Solution Approach 1:
The patent applies partial automation by focusing automated data transfer implementation on high-priority data threads that provide the greatest productivity benefit. This selective approach avoids the prohibitive costs of complete automation while still achieving significant improvements in data transfer efficiency for critical processes.
Data Source
AI summary
A method for improving production of a physical product may include applying a data element mapping analysis to a current state of a system. The method may further include evaluating results of the application of the data element mapping analysis to identify and prioritize data threads of the system for increased efficiency. Additionally, the method may include adjusting, as a function of the prioritization of the data threads, a subset of the data threads of the system to improve one or more metrics of the system associated with waste that impedes efficiency. Further, the method may include utilizing the adjusted data threads to increase an efficiency associated with production of a physical product produced by the system.