AI Visual Inspection [RoxyAI] Explanation: Comparison with Rule-Based Systems

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last updated：Aug 01, 2025

三機 Creative Lab

Official site

Explaining the features of the appearance inspection software "Roxy AI"! This time, I will provide a detailed comparison with rule-based systems!

Would you like to start automating visual inspections that are currently judged by human hands, eyes, and experience? Eliminate the black box! Understandable and tangible! Usable on-site! Introducing the AI visual inspection product 【RoxyAI】, which pursues simplicity for "on-site usability": - Determines whether defects are included in the inspection area / Identifies types of defects / Detects unknown defects - Learns features from a small amount of training data / Fast and high-precision proprietary AI algorithm (patent pending) - Unique visualization technology (patent pending) that is easy to understand even for those unfamiliar with AI - Understand weaknesses by checking the sensitivity of the AI through touch. Easy for anyone, even without AI knowledge Our company leverages its experience in designing and manufacturing dedicated machines, inspection machines, factory logistics, and automation systems in the FA field to offer proposals and support for AI verification, actual machine evaluation, and automation of visual inspection processes. We also support the automation of production processes, including pre- and post-inspection processes, so please feel free to contact us first. Sanki Co., Ltd. (Atsuta-ku, Nagoya) is the official distributor of RoxyAI.

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basic information

【Comparison with Rule-Based Systems】 No.1 Rule-Based Type Determines based on inspection rules set by humans (such as length and area). Clear rule setting is necessary, and there tends to be a high occurrence of false positives. No.2 Roxy AI AI can learn features on its own and adapt to ambiguities and flexibility. (Since there are strengths and weaknesses depending on the inspection, it is necessary to choose the appropriate method.) No.3 What Rule-Based Systems Struggle With Things that are difficult to define clearly. No.4 With Roxy AI It can learn the characteristics of defects, allowing it to make determinations without false positives, even for things that are difficult to define.

Price information

The three machines are proposal-based and support our customers' "troubles." 【Purchase Method】 In addition to cash lump-sum purchases, we can propose payment plans that meet our customers' needs in collaboration with partner leasing companies. Recently, there are also leases that can ultimately be converted into company assets. Additionally, we can assist with various subsidies. If you have any concerns, please feel free to contact us.

Delivery Time

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Applications/Examples of results

【Other Features】 ■ The AI automatically extracts suspicious data from the learning dataset. ■ Focused checks on intervals where normal and defective data are mixed on the histogram. ■ Human judgment on the handling of suspicious data by reviewing enlarged images and overall images. ■ If issues are found, the corresponding images are deleted or normal/defective classifications are swapped. 【Examples of Achievements】 ■ Scratches (line scratches, dents) on metal products, processing defects (surface inspection after welding and burr removal). ■ Scratches (line scratches, dents, sink marks) on resin molded products, processing defects (burrs, chips). ■ Sensory inspection for shape defects such as weld beads and soldering. * This does not guarantee the detection of all defects.