Anomaly Detection Solution Impulse

~~The "Key" to Promoting DX in the Manufacturing Industry: Organization, People, and Systems~~ ❑ Lecture Content 15:00–15:05 Introduction 15:05–15:35 Required Digital Business Operations Capabilities in the Manufacturing Industry (Spending Research Manager Yasushi Shikida, IDC Japan) 15:35–16:05 What is Necessary to Realistically Promote DX in the Manufacturing Industry (Takayuki Kikuchi, Chief of Technology Development Division, Toyo Seikan Group Holdings) 16:05–16:15 What is the Impulse to Advance AI and IoT Projects to the Next Stage (Toshiaki Enami, Chief Operating Officer, Brain's Technology Inc.) ❑ Organizer Brain's Technology Inc. ❑ About the Online Seminar - After registration, we will provide you with a URL to participate in the online seminar. - You can participate from your company or personal desk while keeping your face and name hidden. ❑ Important Notes - Participation from IT vendors, system development companies, competitors in the same industry, and individuals is not allowed.

~~The "Key" to Promoting DX in the Manufacturing Industry: Organization, People, and Systems~~ ❑Lecture Content 15:00–15:05 Introduction 15:05–15:35 Required Digital Business Operations Capabilities in the Manufacturing Industry (Spending Research Manager Yasushi Shikida, IDC Japan) 15:35–16:05 What is Needed to Realistically Promote DX in the Manufacturing Industry (Takayuki Kikuchi, Chief of Technology Development Division, Toyo Seikan Group Holdings) 16:05–16:15 What is the Impulse to Advance AI and IoT Projects to the Next Stage (Toshiaki Enami, Chief Operating Officer, Brains Technology Inc.) ❑Organizer Brains Technology Inc. ❑About the Online Seminar - After registration, we will provide you with a URL to participate in the online seminar. - You can participate from your company or personal desk while keeping your face and name hidden. ❑Notes - Participation from IT vendors, system development companies, competitors in the same industry, and individuals is not allowed.

~~The "Key" to Promoting DX in the Manufacturing Industry: Organization, People, and Systems~~ ❑Lecture Content 15:00–15:05 Introduction 15:05–15:35 Required Digital Business Management Capabilities in the Manufacturing Industry (Spending Research Manager Yasushi Shikida, IDC Japan) 15:35–16:05 What is Necessary to Realistically Promote DX in the Manufacturing Industry (Takayuki Kikuchi, Chief of Technology Development Division, Toyo Seikan Group Holdings) 16:05–16:15 What is the Impulse to Advance AI and IoT Projects to the Next Stage (Toshiaki Enami, Chief Operating Officer, Brains Technology Inc.) ❑Organizer Brains Technology Inc. ❑About the Online Seminar - After registration, we will provide you with a URL to participate in the online seminar. - You can participate from your company or personal desk while keeping your face and name hidden. ❑Notes - Participation from IT vendors, system development companies, competitors in the same industry, and individuals is not allowed.

In the manufacturing field, where constant improvement in productivity and quality assurance is required, efforts utilizing AI are accelerating to quickly detect equipment malfunctions or failures and to prevent issues such as the occurrence of defective products. Various sensors and devices can be installed on production equipment and machinery, allowing for the acquisition of time-series data from measurement values and control parameters. The abnormal detection solution Impulse's "Abnormal Detection App" uses such time-series data to detect unknown anomalies by leveraging AI technology, rather than relying on traditional threshold-based systems. The "Cause Analysis App" can analyze the factors leading to the occurrence of anomalies. In this webinar, after introducing case studies of time-series data analysis utilizing AI technology, we will pick two specific cases from those studies and explain the creation and analysis methods of the anomaly detection model using actual screens and data, along with demonstrations. - Detection of early signs of plant equipment failure - Analysis of defect factors in the injection molding process of automotive parts manufacturing