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  5. Thermo-fluid analysis
  6. Analyze experimental results and utilize them with machine learning 'PipelinePilot'

Analyze experimental results and utilize them with machine learning 'PipelinePilot'

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last updated:Apr 21, 2021

ウェーブフロント 本社
ウェーブフロント 本社
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Just connect over 3000 parts! Ideal for narrowing down candidates during new material development. With machine learning capabilities, it's effective for a wide variety of business improvements!

PipelinePilot is software that allows all tasks related to data analysis, such as data preprocessing, analysis, and visualization through graph creation, to be performed on a single product. - There are many "experimental result" data sets, but I don't know how to analyze them and want to utilize them. - I want to use machine learning to see trends from the "experimental results." - And more. It can be used for narrowing down candidates during new development or discovering correlations in complex data where relationships are not apparent. 【Features】 ◆ Easily create data processing flows without programming knowledge. ◆ Simplifies data preprocessing, which can be a bottleneck when handling large-scale data. ◆ Many successful implementations in chemical and drug discovery companies. *For more details, please contact us.

    simulatorThermo-fluid analysisContract Analysis
キャプチャ.JPG

Analyze experimental results and utilize them with machine learning 'PipelinePilot'

キャプチャ.JPG
キャプチャ.JPG イメージ.png イメージ1.png コンポーネント.png フロー1.png 利用シーン.png
  • Introduction to product details and case studies of "Pipeline Pilot".
  • Special site - Product/service details - https://pr.mono.ipros.com/wavefront/product/

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basic information

The analysis section supports a wide range of methods, from standard statistical analysis to machine learning and deep learning, and includes a standard feature for "fingerprinting that quantifies chemical formulas," which is necessary when conducting the increasingly popular field of materials informatics. *For more details, please contact us.*

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We have a proven track record of implementation in a wide variety of scenes, including material manufacturers, manufacturing industries engaged in material development, and related manufacturers in semiconductors and surface treatment.

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Data Analysis Comprehensive Platform (Data Science Tool) 'PipelinePilot'

Data Analysis Comprehensive Platform (Data Science Tool) 'PipelinePilot'

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Materials Development Integrated Simulation Software "Materials Studio"

Materials Development Integrated Simulation Software "Materials Studio"

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Essential for material manufacturers! Electronic lab notebook 'BIOVIA Notebook'

Essential for material manufacturers! Electronic lab notebook 'BIOVIA Notebook'

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[Case Study] Ideal for Lithium-Ion Battery Material Development 'Materials Studio' *Free case study available!

[Case Study] Ideal for Lithium-Ion Battery Material Development 'Materials Studio' *Free case study available!

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Easy introduction to the electronic lab notebook 'BIOVIA Notebook'

Easy introduction to the electronic lab notebook 'BIOVIA Notebook'

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[Notice] We will hold an online seminar titled "Examples of Using Machine Learning Tools in 45 Minutes" on October 14 (Wednesday).

  • Product news

The second installment of the online seminar that received a great response the other day! We will introduce case studies utilizing "tools" with the theme of the most frequently mentioned "keyword of interest" from the survey responses on the seminar day: [Machine Learning]. This seminar is recommended for those who want to know specific use cases such as "What can 'Machine Learning' actually do?" and "When should I use 'Machine Learning'?" This time, we will take a slightly different perspective and present case studies of "Machine Learning" applications using tools in a broad context, including "multi-objective optimization using Machine Learning" in 'Materials Informatics (MI)', "Data Science", and "Image Recognition Processing". ■ Event Overview 【Date and Time】October 14, 2020 (Wednesday) 13:15 - 14:00 (scheduled for 45 minutes) 【Participation Fee】Free (pre-registration required) 【Method】Held online (Web) 【Overview & Registration】Please register from the following page www.wavefront.co.jp/news/20201014-MI_seminar ★ We sincerely look forward to your participation! ♪★

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[Notice] We will hold an online seminar titled "Examples of Utilizing Machine Learning Tools in 45 Minutes" on October 14 (Wednesday).

  • Other・notification

The second installment of the online seminar that received a great response the other day! We will introduce case studies utilizing "tools" on the theme of the most frequently mentioned "machine learning" from the survey responses on the seminar day regarding "keywords of interest." This seminar is recommended for those who want to know specific use cases such as, "What can 'machine learning' actually do?" and "When should I use 'machine learning'?" This time, we will take a slightly different perspective and present case studies of "machine learning" applications using tools in a broad context, including "multi-objective optimization using machine learning" in "Materials Informatics (MI)," "data science," and "image recognition processing." ■ Event Overview 【Date and Time】October 14, 2020 (Wednesday) 13:15 - 14:00 (scheduled for 45 minutes) 【Participation Fee】Free (pre-registration required) 【Method】Held online (Web) 【Overview & Registration】Please register from the following page www.wavefront.co.jp/news/20201014-MI_seminar ★ We sincerely look forward to your participation! ♪ ★

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[Notice] We will hold an online seminar titled "Examples of Utilizing Machine Learning Tools in 45 Minutes" on October 14 (Wednesday).

  • Company news

The second installment of the online seminar that received a great response the other day! We will introduce case studies using "tools" with the most frequently mentioned keyword from the survey responses on the seminar day: "Machine Learning." This seminar is recommended for those who want to know specific use cases such as "What can 'Machine Learning' actually do?" and "When should I use 'Machine Learning'?" This time, we will take a slightly different perspective and present case studies of "Machine Learning" applications using tools in "Materials Informatics (MI)," including "multi-objective optimization using Machine Learning," "data science," and "image recognition processing." ■ Event Overview 【Date and Time】October 14, 2020 (Wednesday) 13:15 - 14:00 (scheduled for 45 minutes) 【Participation Fee】Free (pre-registration required) 【Method】Held online (Web) 【Overview & Registration】Please register from the following page: www.wavefront.co.jp/news/20201014-MI_seminar ★ We sincerely look forward to your participation! ♪ ★

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[Notice] We will hold an online seminar titled "Examples of Utilizing Machine Learning Tools in 45 Minutes" on October 14 (Wednesday).

  • Seminar・Event

The second installment of the online seminar that received a great response the other day! We will introduce case studies utilizing "tools" with the theme of the most frequently mentioned "keyword of interest" from the survey responses on the day of the seminar: [Machine Learning]. This seminar is recommended for those who want to know specific use cases such as "What can 'Machine Learning' actually do?" and "When should I use 'Machine Learning'?" This time, we will take a slightly different perspective and introduce case studies of "Machine Learning" using tools from a broad perspective, including "multi-objective optimization using Machine Learning" in 'Materials Informatics (MI)', "Data Science", and "Image Recognition Processing". ■ Event Overview 【Date and Time】October 14, 2020 (Wednesday) 13:15 - 14:00 (scheduled for 45 minutes) 【Participation Fee】Free (pre-registration required) 【Method】Held online (Web) 【Overview & Registration】Please register from the following page www.wavefront.co.jp/news/20201014-MI_seminar ★ We sincerely look forward to your participation! ♪★

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ウェーブフロント

ウェーブフロント 本社

software

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Our company develops and sells a "Maintenance Management System" for managing and operating various plants, factories, and other facilities and assets. Currently, this system is undergoing significant evolution into one that incorporates IoT technologies, such as sensor information and input from tablet devices, as well as AI technologies like machine learning, featuring functions for failure prediction and automatic scheduling. Additionally, as part of the recent trend towards digital transformation (DX), there is a growing movement to digitize and automate manufacturing processes and research and development sites in factories to enhance operational efficiency. In line with this trend, our company provides a solution aimed at improving efficiency in research and development environments, known as the Laboratory Information Management System (LIMS), which includes features such as workflow management, data tracking, data management, data analysis, and integration of electronic lab notebooks.

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