FutureMain Co., Ltd.
Offering Optimal Maintenance and Management of Manufacturing Facilities
Sun-hwi Lee, CEOFutureMain has developed the Expert Reliability Based Maintenance Solution (ExRBM), a predictive maintenance solution that automatically identifies defects to optimally maintain the main asset of any manufacturing facility. This highly effective solution improves productivity and strengthens a company's manufacturing competitiveness.
The predictive maintenance method involves anticipating and responding to abnormalities occurring in a facility through identification and diagnosis. It collects and analyzes data through sensors throughout the facility, compares this data with normal vibration patterns, and diagnoses abnormalities.
“Global companies’ diagnosis programs only transmit data that deviate from normal patterns or indicate failures, without the need for separate messages or analysis,” says Sun-hwi Lee, CEO of FutureMain. “ExRBM stands head and shoulders above its international competitors’ products. In the case of ExRBM, if data anomalies are detected, problems are automatically analyzed, the cause is diagnosed, and a related message is displayed.”
Presenting Expert-Level Cause Diagnosis and Response
To analyze bigger volumes of data and save time, ExRBM filters out useless data and performs comparison analysis automatically. In addition, it automatically extracts reliable data and presents expert-level cause diagnosis and response measures with a single click, using big data and AI algorithms, eliminating the need for data analysis experts. As a result of the verification test by a certified Korean authority, the diagnosis accuracy of ExRBM is 98.3 percent.
As an example, global manufacturing company ‘K’ was allotting around three days to repairs when a facility went down prior to implementing FutureMain’s predictive maintenance system. Assuming that the operating time of the facility was 16 hours per day, and the loss due to downtime was $7,500.00 per hour, the total loss cost per facility was about $360,000.00.
After introducing the predictive maintenance system, the facility failure rate, which had reached about 70 percent, was significantly reduced to about 8 percent, and the annual maintenance cost, which had been at least $113,000.00, was reduced by 1/3.
The STF Complex Analysis’ Diagnostic Technology
ExRBM uses ‘STF complex analysis’ diagnostic technology that is distinct from the existing monitoring system (VMS). Vibration Spectra, historical data Trends, and defect Frequency can be used to analyze faults at an early stage. If you perform tasks such as simple component replacement during the initial stage of failure before the failure occurs, the facility can be restarted normally. In the event of a serious failure, however, enormous costs are incurred, such as machinery replacement, and downtime is increased, significantly reducing productivity and leading to decreased sales.
ExRBM's UX and UI are intuitive and user-friendly. Instead of the conventional graph style, the ExRBM screen comprises 3D facility images that can be easily checked, accurately presenting the facility status by location using 4-step status alarms. Even inexperienced operators can evaluate the real-time facility status at a glance and respond to defects. Out of the many solutions implemented in smart factories, predictive maintenance technology significantly reduces costs and maintenance upon its introduction.
ExRBM is used in power plants, petrochemicals, oil, gas, heavy industry, energy, secondary batteries, and battery plants. It efficiently monitors machines and automatically diagnoses and notifies early-stage defects. In addition, the ExRBM Lite version can be used as a SaaS-type service in conjunction with a cloud server and is intended for use at manufacturing companies and factories in various industries such as logistics centers, automobile production processes, shipbuilding, aviation, food, cosmetics, and pharmaceutical production. FutureMain provides a variety of solutions, services, and products for domestic and foreign manufacturing companies that want to transform their factories into smart factories through digital innovation.
Another advantage of ExRBM is that it can be used in conjunction with vibration monitoring systems. ExRBM has high compatibility and scalability so that it can be linked with existing systems such as PLC, MES, CMMS, and ERP, allowing the data to be viewed together on the ExRBM screen.
Building an Integrated machinery Management System
In order for manufacturing companies to be globally competitive, they must improve yields to increase productivity, maintain high quality, reduce production costs, and have a safe work environment. To this end, future manufacturing companies will secure their competitiveness through digital innovation.
FutureMain goes beyond detecting machinery abnormalities to ensure efficient operation of factory machinery and continues research to develop key technologies for digital innovation. We are pursuing the establishment of an integrated facility management system that combines process management data and facility operation data so that manufacturing companies can secure expertise in stable operation and efficient management of facilities, and ExRBM is being actively utilized for this purpose.
ExRBM uses ‘STF complex analysis’ diagnostic technology that is distinct from the existing monitoring system (VMS). Vibration Spectra, historical data Trends, and defect Frequency can be used to analyze faults at an early stage. If you perform tasks such as simple component replacement during the initial stage of failure before the failure occurs, the facility can be restarted normally. In the event of a serious failure, however, enormous costs are incurred, such as machinery replacement, and downtime is increased, significantly reducing productivity and leading to decreased sales.
ExRBM's UX and UI are intuitive and user-friendly. Instead of the conventional graph style, the ExRBM screen comprises 3D facility images that can be easily checked, accurately presenting the facility status by location using 4-step status alarms. Even inexperienced operators can evaluate the real-time facility status at a glance and respond to defects. Out of the many solutions implemented in smart factories, predictive maintenance technology significantly reduces costs and maintenance upon its introduction.
ExRBM is used in power plants, petrochemicals, oil, gas, heavy industry, energy, secondary batteries, and battery plants. It efficiently monitors machines and automatically diagnoses and notifies early-stage defects. In addition, the ExRBM Lite version can be used as a SaaS-type service in conjunction with a cloud server and is intended for use at manufacturing companies and factories in various industries such as logistics centers, automobile production processes, shipbuilding, aviation, food, cosmetics, and pharmaceutical production. FutureMain provides a variety of solutions, services, and products for domestic and foreign manufacturing companies that want to transform their factories into smart factories through digital innovation.
Another advantage of ExRBM is that it can be used in conjunction with vibration monitoring systems. ExRBM has high compatibility and scalability so that it can be linked with existing systems such as PLC, MES, CMMS, and ERP, allowing the data to be viewed together on the ExRBM screen.
Building an Integrated machinery Management System
In order for manufacturing companies to be globally competitive, they must improve yields to increase productivity, maintain high quality, reduce production costs, and have a safe work environment. To this end, future manufacturing companies will secure their competitiveness through digital innovation.
ExRBM Stands Head And Shoulders Above Its International Competitors’ Products. In The Case Of ExRBM, If Data Anomalies Are Detected, Problems Are Automatically Analyzed, The Cause Is Diagnosed, And A Related Message Is Displayed
FutureMain goes beyond detecting machinery abnormalities to ensure efficient operation of factory machinery and continues research to develop key technologies for digital innovation. We are pursuing the establishment of an integrated facility management system that combines process management data and facility operation data so that manufacturing companies can secure expertise in stable operation and efficient management of facilities, and ExRBM is being actively utilized for this purpose.
Nurturing Specialized Personnel for Facility Management
ExRBM, predictive maintenance management system, is a technology that has many stages to process and to define fault factors such as finding defects in operating machinery, predicting failures in advance, suggesting appropriate countermeasures and more. It is similar to that of a doctor examining a patient and suggesting appropriate prescriptions.
FutureMain has continued to conduct research to find unexpected defects during the operation process, prevent failures in advance, and build more accurate diagnostic capabilities. As a result, we developed ExRBM, a facility predictive maintenance system. This solution combines facility domain knowledge, artificial intelligence, and big data analysis technology. ExRBM has been proposed to manufacturing companies that do not have facility management experts or have difficulty in diagnosis even if they have a monitoring system in place. By establishing ExRBM, operators can quickly identify the status of the facility, suggest causes of defects and countermeasures, and manage the facility easily and efficiently.
The key to smarter facility management lies not only in implementing various solutions, but also in ensuring that users fully understand the solutions and utilize them efficiently. Sun hwi Lee, CEO of FutureMain, emphasizes, “Continuous customer support is necessary for customers to more effectively implement predictive maintenance management, and it is important to secure competent talent and competent global partners.”
To apply these contents.
First, in line with the global expansion of its business, FutureMain is nurturing Global Talent and promoting localization.
Second, the manufacturing process is one of the most complex combinations, from recipe selection to various method processes and optimal operation, condition measurements. Accordingly, FutureMain focuses on educating expert specialist so that they can clearly understand manufacturing facilities and processes.
Third, a lot of experience is needed to accurately diagnose status and predict failures. FutureMain's engineering service provide training in conjunction with companies so that they can experience the entire process, from facility diagnosis to repair and operation in the field and provide continuous diagnostic services to customer.
Fourth, manufacturing facilities are intricately connected that experts in each field share knowledge and draw conclusions. FutureMain invites experts from various fields and forms an expert network to enable free discussion and provide active support.
In order to increase the competitiveness of manufacturing companies, FutureMain is taking the lead in nurturing specialized personnel for facility management. As part of this, the company is building a big data platform with government agencies to disclose the machinery data it has so far and providing expert knowledge through seminars and training to help manufacturing companies operate more efficiently.
ExRBM, predictive maintenance management system, is a technology that has many stages to process and to define fault factors such as finding defects in operating machinery, predicting failures in advance, suggesting appropriate countermeasures and more. It is similar to that of a doctor examining a patient and suggesting appropriate prescriptions.
FutureMain has continued to conduct research to find unexpected defects during the operation process, prevent failures in advance, and build more accurate diagnostic capabilities. As a result, we developed ExRBM, a facility predictive maintenance system. This solution combines facility domain knowledge, artificial intelligence, and big data analysis technology. ExRBM has been proposed to manufacturing companies that do not have facility management experts or have difficulty in diagnosis even if they have a monitoring system in place. By establishing ExRBM, operators can quickly identify the status of the facility, suggest causes of defects and countermeasures, and manage the facility easily and efficiently.
The key to smarter facility management lies not only in implementing various solutions, but also in ensuring that users fully understand the solutions and utilize them efficiently. Sun hwi Lee, CEO of FutureMain, emphasizes, “Continuous customer support is necessary for customers to more effectively implement predictive maintenance management, and it is important to secure competent talent and competent global partners.”
To apply these contents.
First, in line with the global expansion of its business, FutureMain is nurturing Global Talent and promoting localization.
Second, the manufacturing process is one of the most complex combinations, from recipe selection to various method processes and optimal operation, condition measurements. Accordingly, FutureMain focuses on educating expert specialist so that they can clearly understand manufacturing facilities and processes.
Third, a lot of experience is needed to accurately diagnose status and predict failures. FutureMain's engineering service provide training in conjunction with companies so that they can experience the entire process, from facility diagnosis to repair and operation in the field and provide continuous diagnostic services to customer.
Fourth, manufacturing facilities are intricately connected that experts in each field share knowledge and draw conclusions. FutureMain invites experts from various fields and forms an expert network to enable free discussion and provide active support.
In order to increase the competitiveness of manufacturing companies, FutureMain is taking the lead in nurturing specialized personnel for facility management. As part of this, the company is building a big data platform with government agencies to disclose the machinery data it has so far and providing expert knowledge through seminars and training to help manufacturing companies operate more efficiently.
