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FLiPS is a facility maintenance management system developed with the aim of providing a user experience similar to that of Excel, and it is particularly recommended for customers facing the following challenges: - A user-friendly interface that is easily accepted on-site and the desire to integrate with ERP systems. - The need to centrally manage the quality of manufactured products and facility maintenance. - The desire to visualize the costs, schedules, and actual results necessary for facility maintenance in a calendar format. - The need to understand the frequency and number of unexpected failures and to establish maintenance plans that reflect actual conditions. - The desire to know the optimal cycle for regular inspections and replacements. - The need to streamline budget formulation related to the purchase and maintenance of equipment. Additionally, it has recently been integrated with various IoT-related products, enabling the following capabilities: 1. Automatically creating and notifying maintenance and inspection plans to managers and workers by acquiring sensor data and predicting when thresholds will be exceeded. 2. Integrating with tablet-compatible systems (such as i-Reporter) to aggregate and visualize information from the field.

◆Do you have any of the following concerns?◆ - You have collected failure information but don't know what to do with it. - You want to effectively utilize the collected failure information. - You want to conduct your own analysis based on the failure information but don't know the best method. - You want to connect the results of your analysis to actions that will reduce opportunity loss. ◆Organizing Failure Information Data and Building a System◆ Our company addresses the above concerns by: 1. Clarifying the problem awareness. 2. Presenting and selecting the key performance indicators (KPIs) that should be calculated. 3. Creating a database of failure information. 4. Conducting analysis using the current failure data. 5. Considering actions derived from the analysis results. 6. Building a system to carry out steps 1 to 5. We assist in organizing failure information and building a system that allows customers to select actions that are likely to reduce defects and failures leading to opportunity loss based on the analysis results. The above content assumes that failure information has been collected in advance, but we can also accommodate situations where failure information is extremely limited or not collected. (※1) ※1: Please contact us separately if you would like to see detailed materials.

◆Do you have any of the following concerns?◆ - You have collected failure information but don't know what to do with it. - You want to make good use of the collected failure information. - You want to analyze the failure information yourself but don't know the best method. - You want to connect the results of your analysis to actions that reduce opportunity loss. ◆Organizing Failure Information Data and Building a System◆ Our company addresses the above concerns by: 1. Clarifying the awareness of the problem. 2. Presenting and selecting the key performance indicators (KPIs) that should be calculated. 3. Creating a database of failure information. 4. Conducting analysis using the current failure data. 5. Considering actions derived from the analysis results. 6. Building a system to carry out steps 1 to 5. We assist in organizing failure information and building a system that allows customers to select actions that are likely to reduce defects and failures leading to opportunity loss based on the analysis results. The above content assumes that failure information has been collected in advance or can be collected, but we can also accommodate situations where failure information is extremely limited or not gathered. (*1) *1: Please contact us separately if you would like to see detailed materials.

◆Do you have any of the following concerns?◆ - You have gathered failure information but don’t know what to do with it. - You want to make good use of the collected failure information. - You want to analyze the failure information yourself but don’t know the best method. - You want to connect the results of your analysis to actions that reduce missed opportunities. ◆Organizing Failure Information Data and Building a System◆ Our company addresses the above concerns by: 1. Clarifying the problem awareness. 2. Presenting and selecting the key performance indicators (KPIs) that should be calculated. 3. Creating a database for failure information. 4. Conducting analysis using the current failure data. 5. Considering actions derived from the analysis results. 6. Building a system to carry out steps 1 to 5. We assist in organizing failure information and building a system that allows customers to select actions that could reduce issues and failures leading to missed opportunities based on the analysis results. The above content assumes that failure information has been collected in advance or can be collected, but we can also accommodate situations where failure information is extremely limited or not gathered. (*1) *1: Please contact us separately if you would like to see detailed materials.

We introduce a case where the "FLiPS" maintenance calendar system was implemented for asset management aimed at extending the lifespan of sewer facilities in Sendai City. This page includes not only the "system configuration" such as servers and clients, but also "PDCA for maintenance based on risk assessment" and "examples of risk matrices." By considering various risks and extending the renovation period, cost forecasts have improved. 【Contents】 ■ System Configuration ■ PDCA for Maintenance Based on Risk Assessment ■ Automatic Creation of Maintenance Plans ■ Examples of Risk Matrices ■ Risk information is updated from GIS for pipes and from the FLiPS management screen for facilities. *For more details, please refer to the catalog or feel free to contact us.

With the increasing interest in autonomous driving, the complexity of onboard systems is expected to rise, necessitating not only safety requirements but also security assessments. In Europe, security evaluations are already being conducted in parallel with safety assessments, and the attack tree method exists as a means to carry out security evaluations. The security threat analysis tool Attack Tree provided by Isograph Ltd. (UK) is designed to assist in assessing security vulnerabilities in software. For example, the following representations are possible: - Visual representation of how an attack can succeed - Representation of which attacks have the highest likelihood of success using probability distributions Furthermore, it is also possible to express indicators such as: - The method that has the lowest cost and highest probability of success for an attacker - The difficulty of executing the attack and whether special equipment is required Security assessment is a factor directly related to the safety of vehicles. By referencing the probabilities of threats identified using the Attack Tree within the functional safety Fault Tree, it becomes possible to conduct evaluations that consider both safety and threats.

◆Do you have any of the following concerns?◆ - You have collected failure information but don't know what to do with it. - You want to make good use of the collected failure information. - You want to analyze the failure information yourself but don't know the best method. - You want to connect the results of your analysis to actions that reduce lost opportunities. ◆Organizing Failure Information Data and Building a System◆ Our company addresses the above concerns by: 1. Clarifying the problem awareness 2. Presenting and selecting the key performance indicators (KPIs) to be calculated 3. Creating a database of failure information 4. Conducting analysis using the current data 5. Considering actions derived from the analysis results 6. Building a system to carry out steps 1 to 5 We assist in organizing failure information and building a system that allows customers to select actions that could reduce defects and failures leading to lost opportunities based on the analysis results. The above content assumes that failure information has been collected in advance or can be collected, but we can also respond if there is extremely little or no collected failure information. (*1) *1: Please contact us separately if you would like to see detailed materials.

The "Anomaly Detection and Failure Prediction Solution through Data Mining" is a data mining service and system construction service provided by Wavefront Co., Ltd., which engages in the development and sales of software for electronic computers, analysis using software, design, and consultation. This document introduces a general image of service implementation and specific images that reflect the content we frequently receive inquiries about. 【Features】 ■ Anomaly detection and failure prediction ■ Maximization of operational efficiency ■ Optimization of maintenance costs and maintenance cycles ■ Quality improvement *For more details, please refer to the catalog or feel free to contact us.

This document introduces the relationship between failure rate, reliability, unreliability, and failure probability density, among other reliability information. There is a close relationship between reliability, unreliability, failure probability density, and failure rate (which can be viewed from different perspectives as needed); knowing one allows you to understand the other metrics. When managing failures using CMMS/EAM, it is possible to aggregate the number of failures over time. If the number of failures over time is known, the time dependence of failure rate, reliability, and unreliability can be understood. Weibull analysis is a method of failure analysis that leverages this characteristic. [Contents] - The relationship between failure rate, reliability, failure probability density, and unreliability - Detailed explanation of the diagrams - Summary *For more details, please refer to the PDF document or feel free to contact us.

This document introduces Weibull analysis. In Weibull analysis, the number of failures is used as input to determine the unreliability. Once the unreliability is known, the failure rate and reliability can also be determined. (Refer to the relationship between failure rate and reliability) To express the bias in the occurrence of failures, Weibull distribution is used in failure analysis. By using Weibull distribution, it has become possible to express the bias in the occurrence of failures, including the probability density of failure occurrences.

This document introduces examples of conducting reliability assessments for systems. By evaluating the reliability of a system, one can understand the overall reliability of the system and the importance of the components that make up the system. Methods for evaluating reliability include Reliability Block Diagram (RBD) analysis and Fault Tree Analysis (FTA). [Contents] ■ Reliability Block Diagram (RBD) analysis ■ Examples of system reliability assessment ■ Figures 1-6 ■ Considerations for maintenance ■ Development of maintenance plans *For more details, please refer to the PDF document or feel free to contact us.

The Availability Workbench is software designed to support the implementation of RCM (Reliability-Centered Maintenance) and RAMS analysis (Reliability, Availability, Maintainability, and Safety analysis). The Availability Workbench focuses on the failures of components (system systems) that make up plants and systems, using reliability engineering methods to assist with the following: - Quantitative evaluation of the availability of plants and systems - Development of maintenance plans aimed at eliminating causes of failure - Evaluation of the effectiveness of condition monitoring - Spare parts and workforce planning - Assessment of the lifecycle costs of plants and systems By using the Availability Workbench, it becomes possible to conduct Failure Mode, Effects, and Criticality Analysis (FMECA) and to predict reliability, availability, and lifecycle costs (LCC) with constraints on spare parts and other resources.

This document introduces the evaluation of systems (systems and subsystems) and management through CMMS/EAM. It covers issues encountered when applying Reliability Centered Maintenance (RCM), considerations for implementing RCM, reliability information, evaluation of reliability and availability at the system level, formulation of maintenance strategies, and management points in CMMS/EAM. [Contents] ■ Reliability Centered Maintenance ■ Issues when applying RCM ■ Considerations for implementing RCM and reliability information ■ Evaluation of reliability and availability at the system level and formulation of maintenance strategies ■ Management points in CMMS/EAM ■ Conclusion *For more details, please refer to the PDF document or feel free to contact us.

AiPOST is an information sharing and management system developed with the aim of systematizing the circulation of paper-based forms. It is particularly recommended for customers facing the following issues: - Wanting to share information that occurred on-site immediately, but having no means other than phone calls, resulting in no record being kept. - Wanting to circulate information related to events that occurred on-site, but having inconsistent methods among individuals, making it difficult to know where the information is. - Having made a work request but being unable to grasp the current status. - Distributing information via email, but finding it difficult to determine which information is relevant to them due to the variety of types. - Wanting to centrally manage inquiry information from customers and analyze it in Excel as needed. Additionally, there has been an increase in the use of AiPOST in conjunction with business systems and email, allowing for the following functionalities: 1. Sending email notifications when information or requests related to the user arrive. 2. Managing the progress of business operations on the AiPOST side, simplifying the status confirmation of requests and information distribution. 3. Treating AiPOST as an input terminal in conjunction with maintenance systems, allowing for overall management of equipment information within the maintenance system.

We support the construction of systems related to data collection and visualization, analysis, product improvement, optimization of operating conditions, and predictive maintenance by combining simulation technology, reliability evaluation, and equipment maintenance expertise. The main target equipment includes: - Various plants - Semiconductor manufacturing equipment - Air conditioning systems In this study, we will support the construction of systems by utilizing different tools and systems according to the customer's requests and objectives, such as: - 1D simulation software (1D CAE) - 3D simulation software (3D CAE) - Reliability and safety evaluation software - Statistical analysis software - Machine learning/AI software - IoT information collection infrastructure - Equipment maintenance management systems - Tablet systems Additionally, in conducting this study, we recommend starting small by narrowing down the target equipment.

AiPOST is an information sharing and management system developed with the aim of systematizing the circulation of paper-based forms. It is particularly recommended for customers facing the following issues: - Unable to grasp the current status after making a work request - Distributing information via email, but the types are varied, making it difficult to understand which information is relevant to them - Wanting to centrally manage inquiry information from customers and analyze it in Excel as needed Additionally, recently there has been an increase in the use of AiPOST in conjunction with business systems and email, allowing for the following: 1. Notifications via email when information or requests relevant to them arrive 2. Management of work progress on the AiPOST side, simplifying the status confirmation of requests and information distribution 3. Treating AiPOST as an input terminal in conjunction with maintenance systems, allowing for overall management of equipment information through the maintenance system.

Reliability Workbench is a tool based on reliability engineering used to evaluate and analyze reliability and safety assessments, as well as maintenance content for equipment, in accordance with functional safety. It has been adopted by many companies both domestically and internationally as a tool to evaluate the reliability and safety of equipment required by functional safety standards such as IEC61508 and ISO26262, with over 14,000 installations worldwide. Reliability Workbench is composed of modules for each function, addressing safety requirements such as those in ISO26262. For example: - Prediction: Failure rate calculations corresponding to various handbooks (such as SN29500) - Safety Assessment: Safety evaluations - Fault tree: Fault tree analysis - FMECA: Failure Mode, Effects, and Criticality Analysis and other modules as mentioned above. The main industries where it has been implemented are as follows: - Automotive - Railways - Aerospace - Plants - Industrial equipment

FLiPS is an asset management system developed with the aim of providing a user experience similar to Excel, and it is particularly recommended for customers facing the following challenges: - A user-friendly interface that is easily accepted on-site, with a desire for integration with ERP systems - The need to centrally manage the quality of manufactured products and the condition of equipment - The desire to visualize the costs, schedules, and actual results necessary for equipment maintenance in a calendar format - The need to understand the frequency and number of unexpected failures and to establish maintenance plans that reflect actual conditions - The desire to know the optimal cycle for regular inspections and replacements - The need to streamline budget formulation related to the purchase and maintenance of equipment Additionally, it is now integrated with various IoT-related products, enabling the following capabilities: 1. Automatically creating and notifying maintenance and inspection plans when sensor data indicates thresholds are likely to be exceeded, notifying both managers and workers 2. Integrating with tablet-compatible systems (such as i-Reporter) to aggregate and visualize information from the field.

FLiPS is a system that allows for centralized management of items required by the Pharmaceutical Affairs Law and medical device safety management guidelines, such as: - Start and end inspection checklists - Maintenance inspection planning sheets - Evaluation of maintenance inspections - Management of documents related to equipment - Repair records This system not only manages the above information but also allows for the output of reports and forms in any desired Excel format. If you use a tablet for maintenance inspection tasks, there is also a record of transferring input data from the tablet to FLiPS. Additionally, it is possible to manage items necessary for analysis using reliability engineering in conjunction.

FLiPS is a system that can centrally manage the following items required by the Green Management Promotion Manual. - Vehicle management - Maintenance inspection schedule - Evaluation and results of maintenance inspections - Management of documents related to various vehicles (maintenance procedures, maintenance inspection checklists, etc.) - Future vehicle introduction plans This system not only manages the above information but also allows for the output of reports and forms in any desired Excel format. If you use a tablet for maintenance inspection tasks, there is also the capability to reflect the input data from the tablet to FLiPS in real-time.

FLiPS is an equipment ledger management system developed with the aim of providing a user experience similar to Excel, and it is particularly recommended for customers facing the following challenges: - A user-friendly interface that is easily accepted on-site, with a desire for integration with ERP systems. - The need to centrally manage the quality of manufactured products linked to the equipment ledger. - The desire to visualize costs, schedules, and actual performance necessary for equipment maintenance in a calendar format. - The need to understand the frequency and number of unexpected failures to establish a maintenance plan that aligns with actual conditions. - The desire to know the optimal cycle for regular inspections and replacements. - The need to streamline budget formulation related to equipment purchase and maintenance management. Additionally, it has recently been integrated with various IoT-related products, enabling the following capabilities: 1. Automatically creating and managing maintenance and inspection plans by acquiring sensor data and notifying administrators and operators when thresholds are likely to be exceeded. 2. Integrating with tablet-compatible systems (such as i-Reporter) to aggregate and visualize information from the field.

AiPOST is an information sharing and management system developed with the aim of systematizing the circulation of paper-based forms. It is particularly recommended for customers facing the following issues: - Unable to grasp the current status after making a work request - Distributing information via email, but the types are varied, making it difficult to understand which information is relevant to them - Wanting to centrally manage inquiry information from customers and analyze it in Excel as needed Additionally, there has been an increase in the use of AiPOST in conjunction with business systems and email, allowing for the following functionalities: 1. Notifications via email when information or requests relevant to the user arrive 2. Managing the progress of tasks on the AiPOST side, simplifying the status checks and information distribution 3. Treating AiPOST as an input terminal in conjunction with maintenance systems, allowing for overall management of equipment information within the maintenance system.

Many companies have proposed maintenance methods utilizing large-scale data and AI (artificial intelligence/machine learning), and there are numerous reports on their effectiveness. However, with a few exceptions, the management of maintenance on-site is primarily conducted using various formats such as paper, Excel, Access, and PDF, and the information managed differs by department. Our company provides services to address the following objectives through the construction of equipment records: 1. We want to organize the ledger of data that serves as the foundational requirements for the introduction of a maintenance system. 2. We want to utilize the accumulated failure information on-site to establish inspection cycles that minimize costs. 3. We want to consider maintenance methods tailored to the situation, as even the same equipment may have different usage conditions and environments. 4. We want to create a risk matrix from accident and failure information. 5. We want to graph the relationship between maintenance items, reliability, and costs to serve as a guideline for planning. The steps for constructing equipment records are as follows: 1. Digitization of various information. 2. Organization and classification of the digitized information. 3. Implementation of various analyses according to objectives. 4. Addition of management items based on the analysis results.

Many companies have proposed maintenance methods utilizing large-scale data and AI (artificial intelligence/machine learning), and there are numerous reports on their effectiveness. However, except for some companies, the management of maintenance on-site is predominantly done using various formats such as paper, Excel, Access, and PDF, and the information managed differs by department. Our company provides services to address the following objectives through the organization of equipment ledgers: 1. We want to organize the ledger of data that serves as the fundamental requirement for the implementation of a maintenance system. 2. We want to utilize the failure information accumulated on-site to establish inspection cycles that minimize costs. 3. We want to consider maintenance methods tailored to the situation, as the usage conditions and environments differ even for the same equipment. 4. We want to create a risk matrix from accident and failure information. 5. We want to graph the relationship between maintenance items, reliability, and costs to serve as a guideline for planning. The steps for organizing the equipment ledger are as follows: 1. Digitization of various information. 2. Organization and classification of the digitized information. 3. Implementation of various analyses according to objectives. 4. Addition of management items based on the analysis results.

Support from fault rate calculation to report creation in a seamless manner! Reliability Workbench is a tool based on reliability engineering used for evaluating and analyzing reliability and safety in accordance with functional safety standards. It has been adopted by many companies both domestically and internationally as a tool for evaluating the reliability and safety of equipment required by functional safety standards such as IEC61508 and ISO26262, with a total of 8,000 sites having implemented it worldwide. The main industries where it has been adopted are as follows: - Automotive - Railways - Aircraft - Plants - Industrial equipment In Japan, many automotive-related companies, including Denso Corporation, as well as railway-related customers such as Japan Signal and Nabtesco, have adopted this tool, with over 50 customers in the automotive and railway sectors alone. Additionally, this tool has the following features that support standardization and simplification of work: - Integration with electronic CAD - Database creation of failure data - Automatic deployment of failure modes and distribution ratios to FMEA - Cross-referencing between FMEA and FaultTree+

This document explains, based on our company's implementation results and experience, the necessary considerations for threshold examination, which is always a concern when conducting predictive maintenance, as well as what indicators should be used when considering and implementing predictive maintenance. Additionally, we focus on the analysis of causal relationships with quality-related issues, which we have received many inquiries about in recent years, in conjunction with equipment maintenance. When building IoT and predictive maintenance systems, it is essential to start with a system that is around 60 to 70 points rather than aiming for a perfect score of 100 from the beginning. Gradually improving the system towards the desired state is necessary. This document introduces some of the essence of that approach.

The electronic form system "ConMas i-Reporter" allows for faster and more accurate record reporting tasks than paper forms by creating forms on tablet devices. It is widely used across various industries wherever forms are needed, including manufacturing, maintenance inspection work, construction site records, warehouse management, and dental treatment. 【Benefits of Product Implementation】 - Daily report creation time reduced from 45 minutes to 5 minutes [Metal parts manufacturer] - Elimination of data entry to PC, allowing for completion of creation and reporting on-site. [Construction company] - 60% reduction in man-hours leading to winning an internal improvement contest [Plastic products manufacturing and sales company] - Paperless transition resulting in a reduction of approximately 120,000 sheets of paper [Pharmaceutical company] - Standardization of techniques enabling newcomers to perform at the same level as veterans [Motorcycle manufacturer] *For more details about the product, please download the PDF materials. sales@wavefront.co.jp 045-682-7070

The document titled "Data Mining and IoT Technology Utilization for Equipment Maintenance & Manufacturing Quality Control System" introduces the equipment maintenance and manufacturing quality control system developed by Wave Front Co., Ltd., which engages in the development and sales of software for electronic computers, analysis using software, design, and consultation. It clearly presents the positioning of various products such as the calendar-type equipment maintenance & manufacturing quality control system "FLiPS" and the reliability analysis and optimization system "AWB/RWB." [Contents] ■ Positioning of each product within the solution and the image of each product ■ Positioning of each product within the solution ■ Positioning of each product within the solution and data exchange between products *For more details, please refer to the catalog or feel free to contact us.

This document explains, based on our company's implementation results and experience, the necessary considerations for threshold examination, which is always a concern when conducting predictive maintenance, as well as what indicators should be used when considering and implementing predictive maintenance. Additionally, we focus on the analysis of causal relationships with quality-related issues, which we have received many inquiries about in recent years, alongside equipment maintenance. When building IoT and predictive maintenance systems, it is essential to start with a system that is around 60 or 70 points in completeness, rather than aiming for a perfect 100-point system from the beginning, and to gradually improve the system towards the desired state. This document introduces some of the essence of that approach.

This document explains, based on our company's implementation results and experience, the necessary considerations for threshold discussions that inevitably arise when conducting predictive maintenance, as well as what indicators should be used when considering and implementing predictive maintenance. Additionally, we focus on the analysis of causal relationships with quality-related issues, which we have received many inquiries about in recent years, in conjunction with equipment maintenance. When building IoT and predictive maintenance systems, it is essential to start with a system that is around 60 to 70 points in completeness, rather than aiming for a perfect 100-point system from the beginning, and to gradually improve the system towards the desired state. This document introduces some of the essence of that approach.

This document explains, based on our company's implementation results and experience, the necessary considerations for threshold examination, which is always a concern when conducting predictive maintenance, as well as what indicators should be used when considering and implementing predictive maintenance. Additionally, we focus on the analysis of causal relationships with quality-related issues, which we have received many inquiries about in recent years, in conjunction with equipment maintenance. When building IoT and predictive maintenance systems, it is essential to start with a system that has a completion level of around 60 to 70 points, rather than aiming for a perfect score of 100 from the beginning, and to gradually improve the system towards the desired state. This document introduces some of the essence of that approach.

The tablet-based electronic reporting system "i-Reporter" digitizes Excel-based forms used in equipment inspections, quality checks, reports, inspections, checklists, and business reports in the manufacturing and construction industries! It enables usage on iPads, iPhones, and Windows. By allowing easy and error-free input on-site, it enhances productivity and promotes your company's work style reform. 【Solving these issues】 ◆ Increased printing costs and risk of loss due to handwritten paper management ◆ Difficulties in on-site entries, leading to mistakes and omissions ◆ Slow information transmission, making search and sharing difficult *In the construction industry, there are cases where work has been reduced by about 25% per day. For more details, please contact us or download the PDF to view.

This is a tool that aggregates data from various sources such as Excel, text data, and different databases onto a single screen, visualizing valuable information intuitively in real-time through graphs. In the case of manufacturing sites, it enables real-time visualization of production line and equipment information, allowing for the early detection and prevention of signs of defects, which can lead to a reduction in defective products. The graph data on the screen can be directly exported to Excel, PowerPoint, or PDF, reducing the time and costs associated with report creation. ☆ A one-month free trial is currently available. 【Implementation Effects】 ■ Real-time visualization of production sites, improving operational efficiency ■ Reduction of defective products by one-fifth ■ Visualization of "bottlenecks" in the production line, leading to reduced overtime ■ Reduction in report creation costs ■ Acceleration of the PDCA cycle ■ Immediate access to desired information for analysis *For more details about the product, please download the PDF materials.

Motion Board meets various data utilization needs in manufacturing sites. By centralizing data that was managed separately by each system and analyzing it from multiple perspectives, you can gain new insights that you may not have noticed before. ◆ Are you facing these challenges? ◆ ◇ Delays in understanding the situation on the ground, making it difficult to quickly notice problems ◇ The hassle of entering handwritten daily reports into Excel, requiring primary and secondary processing ◇ The occurrence of defective products and yield issues in the production site ◇ Difficulty in promptly detecting equipment anomalies ◇ Data management is fragmented across systems, making it hard to access necessary information quickly We solve these kinds of issues in production, inspection, and reporting tasks on-site. ◆ Free trial available now ◆

Are you spending too much time on recording, inspecting, and reporting tasks, or understanding issues on-site? By combining the real-time BI dashboard "Motion Board" with the tablet-based electronic reporting system "i-Reporter," you can solve on-site challenges such as: "I want to streamline recording and reporting tasks using paper forms." "I want to eliminate data entry into Excel." "I want to improve the delay in analysis that takes several days from collecting daily reports to implementing countermeasures." ◆ Benefits of Implementation ◆ ◇ Timely identification of defect causes and countermeasures, reducing defective products by 1/5. ◇ By using iPads for input, the manual data entry time into Excel, which used to take about 80 minutes daily, has been reduced to 0 minutes. ◇ Visualization of line "bottlenecks" has led to a reduction of 1 hour in overtime each day. ◆ For more product details, please download the materials ◆

The high-speed database "DR.Sum" is a "front database" that accumulates various data from the field. With "DR.Sum," you can obtain the information you want when you need it, without having to request data extraction from the IT department, which was previously necessary. It can also handle large volumes of data, such as 10 billion records, and can aggregate 1 billion records in just one second. "We spend too much time on data extraction and processing, preventing us from doing other tasks." "The burden of regularly creating documents like monthly reports and meeting materials is significant." "We cannot quickly obtain the information we need when necessary." We solve these problems! ★ Over 6,100 companies have implemented it! ★ 【Features】 - An interface that anyone can use without programming - High-speed aggregation of large-volume data - No increase in costs even with an increase in the number of users - Easy maintenance - Integration with higher-level systems is also possible

The high-speed database "DR.Sum" is a "front database" that accumulates various data from the field. With "DR.Sum," you can obtain the information you want when you need it, without having to request data extraction from the IT department, which was previously necessary. It can also handle large volumes of data, such as 10 billion records, and can aggregate 1 billion records in just one second. "We spend too much time on data extraction and processing, preventing us from performing other tasks." "The burden of regularly creating documents like monthly reports and meeting materials is significant." "We cannot quickly obtain the information we need when we need it." We solve these problems! ★ Over 6,100 companies have implemented it! ★ 【Features】 - A user-friendly interface that requires no programming - High-speed aggregation of large volume data - Costs do not increase with an increase in the number of users - Easy maintenance - Integration with higher-level systems is also possible

The high-speed database "DR.Sum" is a "front database" that accumulates various data from the field. With "DR.Sum," you can obtain the information you need when you need it, without having to request data extraction from the IT department, which was previously required. It is also capable of handling large volumes of data, such as 10 billion records, and can aggregate 1 billion records in just one second. - "Data extraction and processing take too much time, preventing other tasks." - "The burden of regularly creating materials such as monthly reports and meeting documents is significant." - "I cannot quickly obtain the information I need when necessary." We solve these kinds of problems! ★ Over 6,100 companies have implemented it! ★ 【Features】 - A no-programming interface that anyone can use - High-speed aggregation of large-volume data - Costs do not increase even with an increase in the number of users - Easy maintenance - Integration with higher-level systems is also possible

This tool aggregates data from various sources such as Excel, text data, and different databases onto a single screen, visualizing valuable information intuitively in real-time through graphs. In the manufacturing field, it enables real-time visualization of production line and equipment information, allowing for the early detection and prevention of signs of defects, which can lead to a reduction in defective products. The graph data displayed on the screen can be directly exported to Excel, PowerPoint, or PDF, reducing the time and cost of report creation. ☆ A one-month free trial is currently available. 【Implementation Effects】 ■ Real-time visualization of production sites, improving operational efficiency ■ Reduction of defective products by one-fifth ■ Visualization of "bottlenecks" in production lines, leading to reduced overtime ■ Reduction in report creation costs ■ Acceleration of the PDCA cycle ■ Immediate access to desired information for analysis *For more product details, please download the PDF materials.

Are you spending too much time on recording, checking, and reporting tasks for forms, or on understanding issues at the site? By combining the real-time BI dashboard 'Motion Board' with the tablet-based electronic form system 'i-Reporter', you can solve on-site challenges such as: "I want to streamline recording and reporting tasks using paper forms." "I want to eliminate data transcription to Excel." "I want to improve the delay in analysis that takes several days from collecting daily reports, so that countermeasures can be implemented more quickly!" ◆ Benefits of Implementation ◆ ◇ Timely identification of causes of defects and implementation of countermeasures, reducing defective products by 1/5. ◇ Input using iPads has reduced manual data entry time to Excel from about 80 minutes daily to 0 minutes. ◇ Visualization of line "bottlenecks" has reduced overtime by 1 hour each day. ◆ For more product details, please download the materials ◆

The document titled "Total Solutions for Ensuring Safety, Reliability, and Maintenance" introduces the equipment maintenance and manufacturing quality management systems of Wave Front Co., Ltd., which engages in the development and sales of software for electronic computers, analysis using software, design, and consultation. It clearly presents the positioning of various products such as the calendar-type equipment maintenance and manufacturing quality management system "FLiPS" and the reliability analysis and optimization system "AWB/RWB." [Contents] - Positioning of each product within the solution and the image of each product - Positioning of each product within the solution - Positioning of each product within the solution and data exchange between products *For more details, please refer to the catalog or feel free to contact us.

The document titled "Total Solutions for Ensuring Safety, Reliability, and Maintenance" introduces the equipment maintenance and manufacturing quality management systems of Wavefront Co., Ltd., which engages in the development and sales of software for electronic computers, as well as analysis, design, and consultation using software. It clearly presents the positioning of various products such as the calendar-type equipment maintenance and manufacturing quality management system "FLiPS" and the reliability analysis and optimization system "AWB/RWB." [Contents] - Positioning of each product within the solution and images of each product - Positioning of each product within the solution - Positioning of each product within the solution and data exchange between products *For more details, please refer to the catalog or feel free to contact us.

"MotionBoard" is a tool for "business improvement in production sites" that intuitively visualizes valuable information in real-time. [Main Reasons for Selection & Implementation Effects] ■ Visualizes production sites in real-time, improving operational efficiency ■ Reduces defective products to one-fifth (By detecting and preventing signs of defects in advance, it leads to a reduction in defective products) ■ Visualizes "bottlenecks" in the production line, reducing overtime hours ■ Reduces report creation costs ■ Accelerates the PDCA cycle ■ Immediate access to desired information for analysis ■ Reduces time and costs for report creation (Graph data on the screen can be directly output to Excel, PowerPoint, or PDF) ☆ A one-month free trial is available!

The front database "Dr.Sum" solves these kinds of problems! "I can't perform other tasks because data extraction and processing take too much time." "The burden of regularly creating documents such as monthly reports and meeting materials is significant." "I can't quickly obtain the information I need when I need it." "I have to rely on the IT department for data creation requests, which takes time." ★Over 6,100 companies have implemented it★ 【Main Features】 - A user-friendly interface that anyone can use without programming - High-speed aggregation of large volumes of data - No increase in costs even with an increase in the number of users - Easy maintenance - Integration with higher-level systems is also possible

We will visualize the personalized maintenance operations! 【Main Reasons for Selection & Implementation Effects】 ■ Real-time visualization of the production site, improving operational efficiency ■ Reduction of defective products to one-fifth (By detecting and preventing signs of defects in advance, we can reduce defective products) ■ Visualization of "bottlenecks" in the production line, leading to reduced overtime ■ Reduction in report creation costs ■ Acceleration of the PDCA cycle ■ Immediate access to desired information for analysis ■ Reduction in time and costs for report creation (You can directly output graph data on the screen to Excel, PowerPoint, or PDF)