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ease
features
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support

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Description

AWAI offers two distinct methods of operation, both leveraging the same analytical framework. The first method, group analysis, eliminates the need for a traditional fixed questionnaire; instead, you can compose your questions in straightforward language and distribute an invite link, allowing respondents to participate without needing an account. Each individual engages with the AI independently, which prompts further discussion to elicit deeper insights. Once completed, the conversations are organized according to opinions, the underlying rationale, and the number of individuals who expressed each viewpoint, with unique opinions treated as outliers rather than being averaged out. This option accommodates up to 100 participants on a self-serve basis. The second method involves real-time meetings where each participant selects their preferred language for communication and reading, and contributions are categorized under specific topics as the discussion unfolds. Following the meeting, the content is organized thematically rather than presented as a mere transcript. Both approaches culminate in the creation of a document, where you can pose a straightforward question regarding the gathered information, resulting in a report that can be exported as a PDF and edited without any additional charges. Additionally, a public demo is available, requiring no registration to access. This accessibility allows potential users to explore AWAI's capabilities effortlessly.

Description

In response to the stringent quality requirements set by the automotive sector, semiconductor manufacturers are increasingly adopting Part Average Testing (PAT) to bolster the reliability of their products. This method focuses on identifying and eliminating "outlier" components that may pass conventional testing yet display unusual traits, thereby mitigating long-term quality and reliability concerns. By performing statistical analyses on a range of devices and modifying the pass/fail thresholds, PAT enables the early detection of these problematic parts, ensuring that only the highest quality components are included in production shipments. While Part Average Testing (PAT), as outlined in the Automotive Electronics Council AEC-Q001-Rev C specifications, primarily addresses DPM techniques for normal (Gaussian) distributions, many real-world scenarios involve distributions that do not conform to this norm. Consequently, it is essential to employ tailored PAT outlier detection strategies to prevent significant yield losses or erroneous identifications of outliers. To meet these challenges, PAT-Man emerges as a robust solution for implementing effective Part Average Testing (PAT). This innovative tool not only enhances the reliability of semiconductor components but also streamlines the testing process, ultimately benefiting manufacturers and consumers alike.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

$11.99/month
Free plan available, no card required. Subscriptions are Plus $11.99, Pro $29.99 and Ultra $99.00 per month.

Group analysis is a one-time purchase rather than a subscription: $799.00 base plus $11.99 per respondent, for up to 100 respondents on self-serve. Reports are included at no extra cost.

Prices are shown in the viewer's local currency; USD is the reference.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

OFFICE KAMIYA Inc.

Founded

2016

Country

Japan

Website

www.officekamiya.co.jp/

Vendor Details

Company Name

Galaxy

Country

United States

Website

www.galaxysemi.com/products/pat-man

Product Features

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

Product Features

Engineering

2D Drawing
3D Modeling
Chemical Engineering
Civil Engineering
Collaboration
Design Analysis
Design Export
Document Management
Electrical Engineering
Mechanical Engineering
Mechatronics
Presentation Tools
Structural Engineering

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