A collection of practical examples of manufacturing DX that solves on-site challenges.
In the machinery industry, design reviews require improvements in design quality and efficiency. Particularly in increasingly complex product designs, design errors and oversights can lead to increased manufacturing costs and quality issues. This document introduces examples of how to achieve efficiency and quality improvement in design reviews using AI. It explains specific approaches to innovate the design review process, such as automatic checks of design data by AI and extracting insights from past design data. 【Usage Scenarios】 * Automatic checks of design data * Extracting insights from past design data * Reducing design review time 【Effects of Implementation】 * Improvement in design quality * Reduction in review man-hours * Shortening of product development periods
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**Features** * Inventory optimization utilizing demand forecasting AI * Suppression of over-detection in appearance inspection using cameras and AI * Prevention of defective products through work analysis * Skill inheritance system that verbalizes the "tacit knowledge" of skilled workers **Our Strengths** Ice Smiley Co., Ltd. operates one of Japan's largest AI portal media supporting corporate DX. We support our clients in solving their challenges by providing a wide range of information on AI implementation and introducing optimal AI solutions.
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IceMiley Inc. is a company that proposes appropriate solutions to solve various challenges faced by businesses through AI. Our job is to connect companies that want to develop and sell AI products with those that want to implement AI and achieve digital transformation, bringing smiles to both sides. Additionally, we operate one of the largest portal media in the country that introduces suitable AI products for companies, referencing numerous implementation and utilization case studies.
![[Support Case] Gaiax Inc.](https://image.www.ipros.com/public/product/image/2117561/IPROS2380423137210504968.png?w=280&h=280)
