AI that can search for past examples of process and jig design for the Production Technology Department.
Similar-shaped parts can be traced back to which process and which jig were used in the previous production. The processing decisions can be traced from the drawings.
Every time a mass production launch occurs, are you not re-examining "which processes and jigs were used to make similar parts last time, and where defects occurred"? The information needed for decision-making is scattered across process charts, jig drawings, and defect reports, and there are things that can only be understood by asking the responsible personnel. ARCHAIVE analyzes shapes to read drawings in three dimensions and searches for past parts with similar characteristics in shape and processing methods, such as holes, pockets, and bends. By linking part numbers to process charts, jig drawings, and defect reports as the same "item," you can summarize and review how similar parts were made and the reasoning behind those decisions at that time. 【Usage Scenarios】 - Referencing the processes of existing parts with similar shapes in the process design of new parts. - Searching for jig drawings used in the past with similar workpieces before jig design. - Confirming the manufacturability of drawings received from the design department based on the performance of past similar parts. - Checking processing defects and countermeasures that occurred with similar parts during mass production launches. - Tracing the history of process changes by combining drawings and documents. 【Benefits of Implementation】 - Reduces the time required for preliminary research in process design. - Allows for the reuse of existing jigs and processes, reducing setbacks during launches. - Makes it easier to prevent the recurrence of processing defects at the stage of process design. - Enables confirmation of the history of past decisions without needing to ask the responsible personnel.
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【Features】 - AI Similar Drawing Search: Find similar drawings based on shape, dimensions, keywords, and even hand-drawn sketches. - Shape Analysis: Reads drawings as 3D objects and searches based on features of shapes and processing methods, such as holes and pockets. - Automatic Linking: Links specifications, DR meeting minutes, and defect reports to drawings using part numbers as keys. - Cross-Search: Allows searching of drawings, technical documents, and forms based on content rather than file names. - AI-OCR and Attribute Extraction: Reads drawing numbers, part numbers, materials, and dimensional tolerances from drawings. - Ease of Implementation: No need for folder organization or uniform naming conventions. Current files can be registered as they are. 【Our Strengths】 - Retains the basis for decisions: Connects drawings (what was made) with DR meeting minutes and past troubles (why it was decided that way). - Implementation Track Record: 26 companies primarily in the industrial machinery and machine tool manufacturing sectors (as of October 2026). - Data Handling: Customer data is not used for training AI models. - Supportive Implementation: Moves to full implementation after confirming effectiveness with sample data. ARCHAIVE is a service provided by STAR UP Co., Ltd.
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