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  6. Operational Rate Analysis System Utilizing IoT Data

Operational Rate Analysis System Utilizing IoT Data

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last updated:Feb 16, 2023

ウェーブフロント 本社
ウェーブフロント 本社
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Analyze the failure characteristics specific to facilities, equipment, and devices from failure information and create a database! This will lead to actual actions that reduce customer opportunity losses.

◆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.

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Operational Rate Analysis System Utilizing IoT Data

img008440(4).png
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  • Related Link - http://www.wavefront.co.jp/system_i/
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【Contents】 ■Clarification of Objectives ■Overview of Proposed Evaluation Methods ■Analysis and Database Creation Utilizing Failure Information - Weibull Analysis - Bayesian Statistics - MCMC Method - Numerical Modeling/Database Creation of Analysis Results ■Reliability Evaluation of Operating Equipment - Calculation of Failure Rates for Equipment and Systems Using Reliability Block Diagrams (RBD) - Qualitative Risk Assessment and Identification of Actions and Safeguards - Risk Assessment and Evaluation of System Vulnerabilities and Safety ■Considerations Based on Operating Environment (※2) - Examination of Optimal Maintenance Costs and Cycles - Calculation of Differences in Operating Rates Considering Maintenance Parameters - Creation of Risk Matrix (Including Actions) ■Database Creation and Visualization - Visualization of Equipment Status Using Risk Assessment Methods - Prediction of Necessary Actions and Timing Based on Risks - Evaluation by Overlaying Sensor Values and Operating Conditions - Estimation of Next Work Timing Based on Sensor Values (Implementation of CBM) *For more details, please refer to the catalog or feel free to contact us.

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Applications/Examples of results

Achievements - Railway Operations 1 - Recording and analysis of failure information and inspection data - Implementation of reliability assessments and provision of tools - Construction of risk matrices - Presentation of maintenance strategy formulation methods based on RCM - Railway Operations 2 - Management of inspections, collection and recording of measurement values - Automatic setting of the next maintenance scheduled date based on measurement values - Ordering to construction companies based on automatically set plans - Aerospace - Estimation of failure rates in the absence of failure information (Bayesian statistics) and - Examination and presentation of failure cause analysis methods - Infrastructure - Asset management - Risk calculations and automatic creation of inspection and update scheduled dates based on risk - Automatic budget calculations for the next 100 years - Reevaluation of risks and updates to plans based on inspection results

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ウェーブフロント

ウェーブフロント 本社

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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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