{"id":8721,"date":"2026-05-22T13:59:05","date_gmt":"2026-05-22T04:59:05","guid":{"rendered":"https:\/\/aizoth.com\/?p=8721"},"modified":"2026-05-22T13:59:05","modified_gmt":"2026-05-22T04:59:05","slug":"intermach_2026","status":"publish","type":"post","link":"https:\/\/aizoth.com\/en\/2026\/05\/intermach_2026\/","title":{"rendered":"AI Analytics Platform \u201cMulti-Sigma\u00ae\u201d Exhibited at INTERMACH 2026 in Bangkok, Thailand"},"content":{"rendered":"\n

The no-code, cloud-based AI analytics platform <\/a>Multi-Sigma\u00ae<\/a>, developed and provided by AIZOTH Inc. (AIZOTH), was introduced at the joint exhibition booth of Booknet Co., Ltd.<\/a> and USACO Corporation<\/a> during INTERMACH 2026<\/a>, a major manufacturing exhibition held at BITEC<\/a> in Bangkok, Thailand, from May 12 to 15, 2026.<\/p>\n\n\n\n

The booth was \u00a0jointly operated by Booknet Co., Ltd.<\/a>, a Thai company and member company of iGroup<\/a>, and USACO Corporation<\/a>, a Japanese company. During the event, representatives from Booknet Co., Ltd.<\/a>, USACO Corporation<\/a>, and AIZOTH<\/a> introduced the features and application examples of <\/a><\/a><\/a>Multi-Sigma\u00ae<\/a> to visitors.<\/p>\n\n\n\n

INTERMACH is one of ASEAN\u2019s leading manufacturing exhibitions, held annually in Bangkok, Thailand. The event brings together a wide range of manufacturing-related technologies and solutions, including machine tools, industrial machinery, automation, robotics, sheet metal processing, welding, and parts procurement, attracting many companies, research institutions, and engineers.<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

During the exhibition, nearly 100 visitors visited the booth and showed strong interest in Multi-Sigma\u00ae<\/a>. At the booth,our staff members spoke with visitors about their challenges and areas of interest while explaining Multi-Sigma\u00ae<\/a>\u2019s key features: High-Accuracy Prediction, Contribution Analysis, Multi-Objective Optimization, and AI Chain Analysis.<\/p>\n\n\n\n

One topic that attracted particularly strong interest was how to build highly accurate AI models from small amounts of data. In manufacturing and R&D settings, it is often difficult to secure a sufficient volume of data. To address this challenge, Multi-Sigma\u00ae<\/a> uses an auto-tuning function based on proprietary algorithms to improve prediction accuracy while helping to prevent overfitting. Many visitors asked specific questions about this capability.<\/p>\n\n\n\n

The AI Chain Analysis function, which enables analysis by linking multiple AI models, also drew significant attention. The ability to link AI models to analyze data involving multiple processes or complex relationships is expected to be useful in a wide range of applications, including manufacturing process improvement and condition exploration in research and development.<\/p>\n\n\n

\n
\"\"<\/figure>\n<\/div>\n\n\n

<\/a><\/a><\/a>Multi-Sigma\u00ae<\/a> is characterized not only by its ability to achieve high-accuracy prediction using machine learning models based on neural networks, but also by its ability to perform contribution analysis and optimization without requiring programming. At the exhibition booth, many visitors also responded positively to its user-friendly operability, which enables advanced AI analysis even without specialized programming knowledge.<\/p>\n\n\n\n

In particular, visitors involved in research and development highly appreciated the Contribution Analysis function, which quantifies the contribution of each explanatory variable to the objective variable and helps users understand the relationships among variables. The ability not only to obtain prediction results, but also to understand why those results were produced, is a valuable feature when examining research and development themes or manufacturing conditions.<\/p>\n\n\n\n

In addition, the booth introduced application examples in the agricultural field, as well as use cases in design and development within the manufacturing industry. These examples also attracted strong interest from many visitors, some of whom requested individual meetings or a free trial.<\/p>\n\n\n\n

Through our participation in INTERMACH 2026<\/a>, we recognized the growing interest in the use of AI in manufacturing and research and development across Thailand and the broader ASEAN region. AIZOTH<\/a> will continue to support data utilization and problem-solving in a wide range of fields, including research and development, manufacturing, and agriculture, through Multi-Sigma\u00ae<\/a>.<\/p>\n\n\n\n

We have prepared various leaflets introducing analysis examples using Multi-Sigma\u00ae<\/a>, the AI analytics platform developed by AIZOTH<\/a>. These leaflets can be downloaded from the page below.<\/p>\n\n\n\n

https:\/\/aizoth.com\/en\/service\/multi-sigma\/download\/<\/a><\/p>\n\n\n\n

For any questions regarding not only our products but also joint research or consulting services, please contact us using the inquiry form below.<\/p>\n\n\n\n

<\/p>\n\n\n\n

\n
Contact Us<\/strong><\/a><\/div>\n<\/div>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"The no-code, cloud-based AI analytics platform Multi-Sigma\u00ae, developed and provided by AIZOTH Inc. (AIZOTH), w … AI Analytics Platform \u201cMulti-Sigma\u00ae\u201d Exhibited at INTERMACH 2026 in Bangkok, Thailand<\/span><\/a>","protected":false},"author":8,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_locale":"en_US","_original_post":"","footnotes":""},"categories":[17],"tags":[],"class_list":["post-8721","post","type-post","status-publish","format-standard","hentry","category-news","en-US"],"acf":[],"_links":{"self":[{"href":"https:\/\/aizoth.com\/?rest_route=\/wp\/v2\/posts\/8721","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aizoth.com\/?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aizoth.com\/?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aizoth.com\/?rest_route=\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/aizoth.com\/?rest_route=%2Fwp%2Fv2%2Fcomments&post=8721"}],"version-history":[{"count":7,"href":"https:\/\/aizoth.com\/?rest_route=\/wp\/v2\/posts\/8721\/revisions"}],"predecessor-version":[{"id":8732,"href":"https:\/\/aizoth.com\/?rest_route=\/wp\/v2\/posts\/8721\/revisions\/8732"}],"wp:attachment":[{"href":"https:\/\/aizoth.com\/?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8721"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aizoth.com\/?rest_route=%2Fwp%2Fv2%2Fcategories&post=8721"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aizoth.com\/?rest_route=%2Fwp%2Fv2%2Ftags&post=8721"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}