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Support tools Product List and Ranking from 109 Manufacturers, Suppliers and Companies | IPROS GMS

Last Updated： Aggregation Period:Aug 05, 2026～Sep 01, 2026
This ranking is based on the number of page views on our site.

Support tools Manufacturer, Suppliers and Company Rankings

Last Updated： Aggregation Period:Aug 05, 2026～Sep 01, 2026
This ranking is based on the number of page views on our site.

  1. 山本電機 Shizuoka//Machine elements and parts
  2. ガイオ・テクノロジー Tokyo//IT/Telecommunications
  3. Translead Tokyo//Service Industry
  4. 4 IDAJ Kanagawa//software
  5. 5 LIGHTz つくば本社 Ibaraki//software
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Support tools Product ranking

Last Updated： Aggregation Period:Aug 05, 2026～Sep 01, 2026
This ranking is based on the number of page views on our site.

  1. Photosynthesis Maximization Support Tool 山本電機
  2. Embedded Software Unit Testing "Coverage Master winAMS" ガイオ・テクノロジー
  3. Translead CRM Translead
  4. Report creation support tool 'WingReport v3.1' ソフトウィング
  5. 5 Input support tool "BEAR-D2" レオクラン 本社

Support tools Product List

211～240 item / All 251 items

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Reduction of estimated cost examination through similar shape search in shipbuilding.

Reduction of estimated cost examination through similar shape search in shipbuilding.

Accelerating shipbuilding estimates and rough cost analysis through similar shape searches.

For shipbuilding: To address the challenge of spending time searching for similar parts every time an estimate or rough cost is considered, which slows down the proposal speed, we will solve this with the similar shape search function of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing you to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that relied on the experience of skilled workers. 【Usage Scenarios】 ■ Fast search for past similar design cases ■ Automatic checks of requirements according to design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel 【Implementation Effects】 ■ Reduction of variation in design quality and promotion of standardization ■ Shortening of development time by reducing design and verification man-hours ■ Continuous sharing and promotion of the use of skilled workers' know-how

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Collaboration among shipbuilding suppliers and the use of 3D CAD data.

Collaboration among shipbuilding suppliers and the use of 3D CAD data.

Facilitating the collaboration of design data with shipbuilding suppliers through the use of 3D CAD data.

For shipbuilding: We address the issue of inefficient exchange of design data with suppliers, which leads to rework due to misunderstandings, through the 3D CAD data utilization feature of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past examples to 3D CAD data, allowing users to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse the verification tasks that relied on the experience of skilled workers. [Utilization Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Cost reduction effects of rework in aircraft component design.

Cost reduction effects of rework in aircraft component design.

Visualize the costs associated with design rework of aircraft components and make it easier to explain the reduction effects to management.

For aircraft parts: The issue of not being able to visualize the man-hours and costs associated with design rework, making it difficult to explain to management, will be resolved with blooplinter's design rework reduction feature. 'blooplinter' is a knowledge utilization tool that links design know-how and past examples to 3D CAD data, allowing for quick access to necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that were previously reliant on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development time through reduction of design and verification man-hours ■ Continuous sharing and promotion of the use of skilled workers' know-how

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Improving quality through automated requirement checks in railway vehicle parts design.

Improving quality through automated requirement checks in railway vehicle parts design.

Automate the design requirement checks for railway vehicle parts to be faster and more reliable.

For railway vehicle parts: We will solve the issue of design requirement check omissions being discovered in later processes or after mass production, leading to correction costs, with the automatic requirement check feature of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past examples to 3D CAD data, allowing for quick access to necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse the verification tasks that relied on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Confirmation of differences during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variation in design quality and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the use of skilled workers' know-how

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Utilization of Similar Shape Search for Railway Vehicle Parts Production Technology Department

Utilization of Similar Shape Search for Railway Vehicle Parts Production Technology Department

The design of jigs and equipment for railway vehicle parts also utilizes past assets through similar shape search.

For railway vehicle parts: The production technology department faces the challenge of not being able to find past designs of similar jigs and equipment, leading to new considerations each time. This issue is resolved with the similar shape search function of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing for quick access to necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that were previously reliant on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checking of requirements in accordance with design standards ■ Confirmation of differences during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Training young railway vehicle parts designers and utilizing knowledge.

Training young railway vehicle parts designers and utilizing knowledge.

Accelerating the development of young designers for railway vehicle parts by utilizing knowledge from 3D CAD data.

For railway vehicle parts: We address the challenge of young designers' training relying on on-the-job training (OJT) at the site, which slows down the training speed, with the young training and design knowledge utilization features of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past examples to 3D CAD data, allowing users to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that previously relied on the experience of skilled workers. [Utilization Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements according to design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Passing on design know-how to new personnel [Implementation Effects] ■ Reduction of design quality variation and promotion of standardization ■ Shortening of development periods by reducing design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Reducing Rework in Construction Machinery Parts Design: Techniques for Utilizing 3D CAD

Reducing Rework in Construction Machinery Parts Design: Techniques for Utilizing 3D CAD

Preventing design rework of construction machinery parts by utilizing 3D CAD data.

For construction machinery parts: We will solve the issue of frequent rework and reconsideration due to the discovery of defects in the design process using blooplinter's design rework reduction feature. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing users to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse the verification tasks that relied on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development time through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Utilization of Similar Shape Search for Construction Machinery Parts Production Technology Department

Utilization of Similar Shape Search for Construction Machinery Parts Production Technology Department

Utilizing past assets through similar shape search for the design of jigs and equipment for construction machinery parts.

For construction machinery parts: The production technology department faces the challenge of not being able to find past designs of similar jigs and equipment, leading to new considerations each time. This issue is resolved with the similar shape search function of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing for quick access to necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that were previously reliant on the experience of skilled workers. 【Usage Scenarios】 ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel 【Implementation Effects】 ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Development of young designers for construction machinery parts and utilization of knowledge.

Development of young designers for construction machinery parts and utilization of knowledge.

Accelerating the development of young designers for construction machinery parts by utilizing knowledge from 3D CAD data.

For construction machinery parts: We address the challenge of young designers' training relying on on-the-job training (OJT) at the site, which slows down the training speed, through the young talent development and design knowledge utilization features of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past examples to 3D CAD data, allowing users to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that previously relied on the experience of skilled workers. [Utilization Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of design quality variability and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Cost reduction effects of rework in construction machinery parts design.

Cost reduction effects of rework in construction machinery parts design.

Visualize the costs associated with design rework of construction machinery parts, making it easier to explain the reduction effects to management.

For construction machinery parts: The issue of not visualizing the man-hours and costs due to design rework, making it difficult to explain to management, will be resolved with the design rework reduction feature of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past examples to 3D CAD data, allowing for quick access to necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse the verification tasks that relied on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements according to design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Passing on design know-how to new personnel [Implementation Effects] ■ Reduction of design quality variation and promotion of standardization ■ Shortening of development periods by reducing design and verification man-hours ■ Continuous sharing and promotion of the use of skilled workers' know-how

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AI-FTA Agent for Manufacturing Industry | On-site Decision Support Tool

AI-FTA Agent for Manufacturing Industry | On-site Decision Support Tool

Visualizing the cause of failure and verification procedures from on-site data.

In quality control within the manufacturing industry, maintaining product quality and improving production efficiency are essential. Particularly during incidents on the production line, rapid identification of causes and appropriate responses are crucial. It is important to effectively utilize past failure data and inspection records, relying not on individual knowledge but enabling anyone to quickly identify causes and implement suitable measures. The AI-FTA Agent addresses these challenges and contributes to the efficiency of quality management. 【Usage Scenarios】 - Investigating causes during incidents on the production line - Responding to failures in the quality control department - Transferring the know-how of veteran technicians - Quality improvement activities 【Effects of Implementation】 - Reduction in failure response time - Early resolution of quality issues - Promotion of knowledge transfer - Reduction in quality management costs

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Analyzing consumer psychology with AI! AI support tools for naming and packaging.

Analyzing consumer psychology with AI! AI support tools for naming and packaging.

AI instantly quantifies consumer sensitivity. It scientifically supports product development and promotions while reducing research costs. It also plays a role in selecting effective expressions and justifying proposals.

"Emotional AI Analytics" is an image analysis AI tool that instantly analyzes and visualizes the sound of names, the impression of catchphrases, and package designs using AI trained on consumer data. Without conducting surveys such as marketing research, it enables instant testing of naming, catchphrases, and package designs. Additionally, it allows for easy text mining from your existing documents. 【Features】 ■ Impression evaluation analysis ■ Analysis by age and gender, and by product ■ Analysis results that are easy to grasp intuitively ■ Project registration function ■ Display of average values ■ CSV download of data *For more details, please refer to the related links or feel free to contact us.

  • Business Intelligence and Data Analysis
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Support for the introduction of AI form marketing tools

Support for the introduction of AI form marketing tools

Equipped with continuous effect measurement and analysis functions! Regularly grasp the areas for improvement in sales activities and use it to review further strategies.

At W CREATIVE Co., Ltd., we provide support for the implementation of 'AI Form Marketing Tools' to streamline B2B sales activities and promote your company's performance. This tool significantly reduces the burden on sales teams, allowing them to approach a large number of potential customers in a short time, even if they have a small sales force and cannot dedicate enough time to new business development. Additionally, by directly approaching companies through inquiry forms, it creates new business development opportunities that cannot be obtained through telemarketing or cold calling. 【Features】 ■ Realization of automated sales processes ■ Direct approach to potential customers ■ Improved operational efficiency and cost reduction ■ High probability of successful approaches ■ Integration of inbound and outbound strategies *For more details, please refer to the related links or feel free to contact us.

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Illustration: What is "Sales Support"?

Illustration: What is "Sales Support"?

Explaining specific methods, improvement examples, and useful tools! We will also introduce successful case studies.

There are many miscellaneous tasks such as administrative work within the company, making it difficult to increase business negotiations. Overtime hours tend to increase as well... Have you ever heard such complaints from within the company? Originally, the important role of sales is to increase revenue. However, it is surprisingly difficult for sales representatives to focus on the key activities that drive revenue. It is necessary to streamline tasks other than business negotiations and create an environment where they can concentrate as much as possible on negotiations. A strong ally in creating this environment is the concept of 'sales support.' *For more details on the column, please refer to the related link. Feel free to contact us for more information.

  • SFA/Sales Support System
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Outbound

Outbound

Introducing an article about the differences with inbound and the creation of sales lists!

In this column, we introduce articles about outbound sales. In "What Does 'Outbound' Sales from Companies Mean?", we also explain the differences from inbound sales. Additionally, the article "Creating Sales Lists: The Key is Information Gathering!" provides information related to new sales and telemarketing. *You can view the detailed content of the column through the related links. For more information, please feel free to contact us.*

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Case Study: Medical Device Manufacturer | Optimization of Sales Pitches and Improvement of Proposal Accuracy through AI

Case Study: Medical Device Manufacturer | Optimization of Sales Pitches and Improvement of Proposal Accuracy through AI

Achieved a high contract rate even with new sales staff, reducing training costs!

A case study of improving the contract rate through the optimization of sales talks using AI at a medical device manufacturer. Challenges: Sales representatives had different approaches to negotiations, resulting in variability in contract rates. They were unable to make appropriate proposals based on customer needs, leading to delays in the progress of negotiations. The utilization of sales data was insufficient, and successful patterns were not shared within the team. Measures: Introduction of an AI sales support tool: Analyzes negotiation data and suggests high-conversion sales talks. Real-time proposal support: AI provides optimal responses and closing talks during negotiations. Analysis of negotiation data: AI identifies high-conversion sales processes and shares them with the entire sales team. Results: The contract rate improved by 25%, stabilizing the sales win rate. With AI proposal support, the speed of negotiation progress increased by 30%. Even new sales representatives achieved high contract rates, reducing training costs.

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Improving Business Efficiency with ChatGPT for Food Processing! AI Utilization Techniques

Improving Business Efficiency with ChatGPT for Food Processing! AI Utilization Techniques

Make your recipe development a little easier with ChatGPT.

In the food processing industry, developing new recipes and improving existing ones is crucial to continue meeting market demands. In particular, creative and efficient recipe development is required to respond to the diversification of consumer preferences and the growing health consciousness. ChatGPT can serve as a sounding board for ideas and help organize existing information, much like an experienced developer. It allows for easy questioning and consultation without the need for special skills, making it accessible even for those unfamiliar with AI. This facilitates a smoother recipe development process and enables more effective use of limited resources. This article will explain in detail how ChatGPT can be utilized in recipe development within the food processing industry, including specific benefits and implementation methods. 【Utilization Scenarios】 - Generating ideas for new menu items - Supporting the analysis of nutritional balance and costs of existing recipes - Suggesting flavor profiles tailored to target demographics - Clarifying cooking procedures 【Effects of Implementation】 - Accelerating the recipe development process - Generating diverse ideas - Reducing the burden on developers - Improving recipes based on data

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Streamlining Operations in Plastic Product Manufacturing with ChatGPT! AI Utilization Techniques

Streamlining Operations in Plastic Product Manufacturing with ChatGPT! AI Utilization Techniques

Solve the challenges of optimizing molding conditions with ChatGPT!

In the plastic manufacturing industry, optimizing molding conditions is crucial for consistently producing high-quality products. Particularly for products with complex shapes or high physical property requirements, even slight deviations in fine condition settings can lead to defects. Therefore, it is necessary to rely not only on experience and intuition but also on data-driven efficient condition settings. This article will discuss how small and medium-sized manufacturers can utilize ChatGPT, detailing specific benefits and implementation methods. 【Utilization Scenarios】 - Examination and optimization of molding conditions - Analysis of past defect data - Understanding the properties of new molding materials - Standardization of work procedures 【Effects of Implementation】 - Improved accuracy in setting molding conditions - Reduction of defective products - Increased production efficiency - Support for skill enhancement of personnel

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Easily record inspection results electronically! You can record inspection results just by taking a photo!

Easily record inspection results electronically! You can record inspection results just by taking a photo!

Quality management record and reporting tasks more accurately and more efficiently.

"Near Miss," "Corrective Action Report," "Inspection Results Report" — You can record these reports more easily and accurately. Smart Report is an AI reporting support tool that allows you to easily input and voice-record various reports (abnormality reports, inspection results, corrective actions, etc.) occurring in quality management on your smartphone or PC, automatically structuring and digitizing the data. ◆ Main Features - Standardization of Reports & Prevention of Omissions You can input reports according to a standardized format, and AI automatically organizes and checks them. This eliminates individual variability, allowing for the accumulation of consistent quality data regardless of who reports. - Real-Time Sharing & Accumulation Recorded data is shared and saved in real-time. This speeds up initial responses to quality issues and root cause investigations. - Reducing the Burden on the Field Supports voice input on smartphones. You can report by simply "speaking" during work breaks, eliminating the need to boot up a PC. Support the "visualization" and "rapid response" of quality management with a new reporting infrastructure. Let's improve both the accuracy and efficiency of quality management tasks with Smart Report. 【Contact Information】 Tel: 044-430-0743 Mail: seizo@toukei.co.jp Contact: Sano, Anzai

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  • Document and Data Management
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<Latest Information> Skill Inheritance and On-Site Improvement Support Tool 'Time Prism'

<Latest Information> Skill Inheritance and On-Site Improvement Support Tool 'Time Prism'

Introducing the initiative for skill inheritance using the video manual "Time Prism" at the seminar! Also featuring news on the 2023 IT introduction subsidy system.

This document introduces how to use the video manual "TIMEPRISM," along with various information related to Japan Seiko Giken, including the "Small and Medium Enterprises Skill Succession Support Seminar" (Wink Aichi) and the "Improvement Experience Seminar" held in Shinjuku. Regarding the Small and Medium Enterprises Skill Succession Support Seminar, participation is free for the first 50 applicants! *Limited to small and medium enterprises with headquarters or business locations in Aichi Prefecture. The deadline is approaching, so if you are interested, please apply as soon as possible. ★Information about the 2023 IT Implementation Subsidy Program will also be provided! Please take a moment to read through it. 【Contents】 ■Announcement of the Small and Medium Enterprises Skill Succession Support Seminar *Venue details are listed in the basic information section below ■Announcement of the Improvement Experience Seminar *Details are listed in the basic information section below ■FISMA TOKYO | Tokyo Fashion Industry Equipment Exhibition Exhibitor Information ■[News] 2023 IT Implementation Subsidy Program ■[News] Planned participation in the Asia Karakuri Improvement Exhibition in Thailand 2024 ■[Product Introduction] Introduction of the i-Reporter Field Document Electronic System

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Would you like to fully utilize model-based development in your company?

Would you like to fully utilize model-based development in your company?

Achieve effective model-based development! [NDR provides full support]

The introduction of model-based development enables early detection of problems by conducting verification from the upstream process, eliminating waste caused by rework, and leading to cost reduction. Our company leverages 30 years of development experience to provide support in building environments such as MILS, SILS, RP, and HILS using MATLAB/Simulink for simulation development, offering proposals and support that consider not only individual areas but the entire process to meet our customers' needs. It has been widely adopted in the manufacturing industry, including the embedded and automotive sectors! ■ We are currently offering a free collection of case studies on simulation development. 【Features】 ■ Efficiently reduce prototyping and experimental costs! Significantly shorten development time! ■ Simulate various situations that are difficult to test in reality! ■ Construct accurate programs that reduce human errors through automatic generation! *For more details, please contact us or download the catalog to view it.

  • Email/Fax transmission
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Reducing Rework in Automotive Design: Techniques for Utilizing 3D CAD

Reducing Rework in Automotive Design: Techniques for Utilizing 3D CAD

Preventing automotive design rework in advance by utilizing 3D CAD data.

For the automotive sector: We will solve the issue of frequent rework and reconsideration due to the discovery of defects in the design post-process with the design rework reduction feature of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing you to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that were previously reliant on the experience of skilled professionals. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Confirmation of differences during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled professionals' know-how

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Development of young automotive designers and utilization of knowledge.

Development of young automotive designers and utilization of knowledge.

Accelerating the development of young automotive designers through the utilization of 3D CAD data knowledge.

For the automotive sector: We address the challenge of young designers' training relying on on-the-job training (OJT) in the field, which slows down the training speed, with the young talent development and design knowledge utilization features of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past examples to 3D CAD data, allowing users to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that were previously dependent on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development time through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Cost reduction effects of automotive design rework.

Cost reduction effects of automotive design rework.

Visualize the costs associated with automotive design rework and make it easier to explain the reduction effects to management.

For the automotive industry: We address the challenge of not being able to visualize the man-hours and costs associated with design rework, making it difficult to explain to management, through the design rework reduction feature of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past examples to 3D CAD data, allowing users to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that relied on the experience of skilled workers. [Use Cases] ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Confirmation of differences during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variation in design quality and promotion of standardization ■ Shortening of development time through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Modularization of automobiles and reuse of design data

Modularization of automobiles and reuse of design data

Streamlining the development of automotive derivatives through modularization and design data reuse.

For the automotive industry: We address the challenge of not advancing the modularization of parts and mechanisms, leading to redesign for each derivative model, with the design data reuse feature of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past examples to 3D CAD data, allowing for quick access to necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that previously relied on the experience of skilled professionals. 【Usage Scenarios】 ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel 【Implementation Effects】 ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development time through reduction of design and verification man-hours ■ Continuous sharing and promotion of the use of skilled professionals' know-how

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Utilization of Similar Shape Search for the Automotive Parts Production Technology Department

Utilization of Similar Shape Search for the Automotive Parts Production Technology Department

Utilizing past assets through similar shape search for the design of jigs and equipment for automotive parts.

For automotive parts: The production technology department faces the challenge of not being able to find past designs of similar jigs and equipment, leading to new considerations each time. This issue can be resolved with the similar shape search function of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing for quick access to necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that relied on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Confirmation of differences during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Cost reduction effects of rework in automotive parts design.

Cost reduction effects of rework in automotive parts design.

Visualize the costs associated with design rework of automotive parts and make it easier to explain the reduction effects to management.

For automotive parts: The issue of not being able to visualize the man-hours and costs due to design rework, making it difficult to explain to management, will be resolved with blooplinter's design rework reduction feature. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing for quick access to necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse the verification tasks that were previously reliant on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements according to design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variation in design quality and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Reduction of estimated cost examination through similar shape search for automotive parts.

Reduction of estimated cost examination through similar shape search for automotive parts.

Accelerating the estimation and rough cost analysis of automotive parts through similar shape search.

For automotive parts: The challenge of taking time to search for similar parts every time we consider estimates and rough cost calculations, resulting in slow proposal speed, is resolved by the similar shape search function of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing users to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that were previously reliant on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checks of requirements according to design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Passing on design know-how to new personnel [Implementation Effects] ■ Reduction of variation in design quality and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the use of skilled workers' know-how

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Improving quality through automated requirement checks in shipbuilding design.

Improving quality through automated requirement checks in shipbuilding design.

Automate the checking of shipbuilding design requirements to be faster and more reliable.

For shipbuilding: We address the issue of design requirement check omissions being discovered in later processes or after mass production, leading to correction costs, with the automatic requirement checking feature of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing for quick access to necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse the verification tasks that relied on the experience of skilled workers. [Usage Scenarios] ■ Fast search for past similar design cases ■ Automatic checking of requirements in accordance with design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel [Implementation Effects] ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development time through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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Training young ship designers and utilizing knowledge

Training young ship designers and utilizing knowledge

Accelerating the training of young shipbuilding designers by utilizing knowledge from 3D CAD data.

For shipbuilding: We address the challenge of young designers' training relying on on-the-job training (OJT) at the site, which slows down the training speed, with the young talent development and design knowledge utilization features of blooplinter. 'blooplinter' is a knowledge utilization tool that links design know-how and past cases to 3D CAD data, allowing users to quickly find the necessary information. It manages past drawings, design decisions, trouble cases, and check items alongside 3D shapes, enabling anyone to reuse verification tasks that were previously dependent on the experience of skilled workers. 【Usage Scenarios】 ■ Fast search for past similar design cases ■ Automatic checks of requirements in accordance with design standards ■ Difference confirmation during design changes ■ Sharing of trouble cases and prevention of recurrence ■ Transmission of design know-how to new personnel 【Implementation Effects】 ■ Reduction of variability in design quality and promotion of standardization ■ Shortening of development periods through reduction of design and verification man-hours ■ Continuous sharing and promotion of the utilization of skilled workers' know-how

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