Packing Style Data Updating for Prototype Part Registration
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Solution Overview
Problem
The challenge of registering prototype parts in a warehouse inventory management system is exacerbated by unstable numbers and shapes, frequent design changes, and the lack of a stable correspondence between part numbers and packing styles, making it difficult to associate prototype parts with their corresponding data.
Innovation Solution
A data updating method that includes acquiring part information using machine learning and artificial intelligence, collating it with ordered part information, and determining whether to add or update packing style data based on design changes, ensuring accurate storage in a database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If automatic registration of part information is implemented, then registration time is reduced, but accuracy of packing style association deteriorates for prototype parts
Solution Approach 1:
The system dynamically adjusts the registration process based on part type. For prototype parts, it enables manual packing style input despite automatic registration capabilities, allowing the packing style to be updated according to actual delivery requirements rather than relying on fixed part number associations
Solution Approach 2:
The system changes the registration parameters based on part characteristics. Prototype parts are identified through part number patterns or supplier information, and the packing style registration process is modified to accept flexible input methods (manual input, image recognition) rather than strict automated matching
2Productivity
If part number and packing style are associated through automatic recognition, then processing efficiency is improved, but reliability of data association deteriorates due to design changes
Solution Approach 1:
The system incorporates feedback mechanisms where the registered packing style information is verified against actual delivery data. When discrepancies are detected (such as packing style changes due to design modifications), the system allows for corrections and updates, ensuring the database reflects current reality rather than relying on potentially outdated automatic associations
Solution Approach 2:
The system performs preliminary identification of prototype parts through part number patterns or supplier information before the main registration process. This preliminary classification enables the system to apply specialized registration procedures that prioritize accuracy over speed for these particular part types
3Extent of automation
If mechanical acquisition of packing style information is used, then automation is increased, but difficulty of detecting and measuring deteriorates for prototype parts
Solution Approach 1:
The system introduces intermediary processing steps that bridge the gap between automated acquisition and the specific needs of prototype parts. Image recognition technology serves as an intermediary that can interpret visual packing style information, while manual input mechanisms serve as intermediaries to capture specific requirements that automated systems cannot detect
Solution Approach 2:
The registration system is designed with multi-functionality to handle different part types uniformly. It can process prototype parts, standard parts, and modified parts through the same overall framework, automatically identifying part types and applying appropriate registration methods (automatic, semi-automatic, or manual) as needed
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables the appropriate storage of packing styles for prototype parts in a database by leveraging AI and machine learning, even in the face of design changes and order fluctuations.
Implementation Method 1
inputting an image of the part to be delivered to a machine learning device that stores a plurality of images of the part to be delivered and identifying the part to be delivered
Data Source
AI summary
The data updating method includes a step of acquiring part information of a part to be delivered, a step of acquiring part information of the part ordered from the ordering information database, a step of collating the part information of the part to be delivered with the part information of the part ordered, a step of acquiring new or change information of the part ordered from the design information database, a step of determining whether or not the packing style data of the part to be delivered is added or updated from the part information of the part ordered and the new or change information of the part ordered, and a step of adding or updating the packing style data of the part to be delivered when it is determined that the packing style data is added or updated.