The predictive maintenance (PdM) technology utilizing data analysis and machine learning (ML) plays a crucial role in Industry 4.0, as it enables proactive device management, efficiency optimization, maintenance scheduling, and minimizing downtime, ensuring stronger sustainability. Timely and accurate data collection is the key to successfully deploying PdM.
The data also needs to have integrity. The power supply can monitor DC voltage (VDC) and current (IDC), peak current (IPEAK), operating time, and replacement time. It is necessary to use a motor status monitor to monitor parameters such as vibration, temperature, current, and insulation resistance (ground fault).
Many devices such as high-voltage control panels, power transformers, hydraulic equipment, motors and bearings, gearboxes, etc. require thermal state monitoring devices, and all of these power sources, motors, and thermal monitoring devices need to send data through Ethernet/IP or Modbus TCP connection technology for real-time analysis.
This article first briefly introduces PdM and its numerous advantages, as well as how to integrate it into the Industry 4.0 system architecture. Then, delve into the numerous PdM devices and software provided by Omron. Finally, explore how to utilize artificial intelligence (AI) to optimize PdM performance.
PdM is one of the three methods for equipment and facility maintenance. In terms of balancing environmental and business costs, this approach falls between reactive maintenance and preventive maintenance (Figure 1). A key consideration when choosing between these three options is how to balance the relative importance between environmental costs and commercial costs.
PdM is between reactive maintenance and preventive maintenance
Figure 1: PdM falls between reactive maintenance and preventive maintenance, balancing business and environmental factors. (Image source: Omron)
Reactive maintenance is to deal with faults after they occur, which increases both environmental and business costs. Preventive maintenance identifies impending failures through regular manual inspections, prioritizing the lowest environmental costs, but this may result in prolonged equipment downtime and excessive business expenses. This maintenance method is considered another form of reactive maintenance, driven by pre-set and subjective plans rather than direct equipment failures.
The emergence of advanced sensors and AI and ML tools has driven the development of PdM technology. This technology can use technological means to balance environmental and business costs.
Flexible and scalable
PdM technology is not a one size fits all choice. PdM technology has scalability and flexibility, suitable for centralized monitoring of single critical equipment, multiple equipment, or the entire facility. In this way, enterprises can start deploying PdM on a small scale and gradually expand, minimizing production stoppages caused by retrofitting existing facilities as much as possible.
The scalable technology solution is implemented through compatibility with multiple components, including sensors, monitoring units, and controllers that can be extended and accessed according to requirements. The use of industrial communication protocols such as Ethernet/IP and Modbus TCP simplifies integration with existing systems and supports multiple enhanced features, such as simultaneous remote monitoring of multiple devices.
Use corresponding scalable software for data analysis and manage equipment from different locations in the centralized office control center or workshop site.
These solutions can be integrated with existing equipment without the need for major repairs, improving flexibility. After optimization, these solutions can be used in almost all industries, such as food and beverage, automotive, medical equipment manufacturing, semiconductors and electronics, military and aerospace, logistics and warehousing, etc.
This flexibility is supported by a wide range of PdM devices, covering multidimensional solutions such as power monitoring, motor operating conditions (current, vibration, temperature, insulation resistance), and thermodynamic operating conditions. In addition, standard software function blocks (FBs) can be used for data collection, communication, data processing and analysis, setting alarms and sending notifications, data recording and reporting, as well as implementing customized PdM analysis based on AI and ML.
State monitors replace simple sensors
The use of state monitors instead of simple sensors to track device performance and achieve proactive maintenance is a key difference between PdM and other methods. Like sensors, state monitors are also installed together with the monitored devices.
However, sensors can be deployed through relatively simple protocols such as IO Link, while state monitors require more complex connection technologies such as EtherNet/IP or Modbus TCP. State monitors can perform local data processing and typically display states that are not typically related to sensors.
Through one or more communication hubs, the status monitor can be connected to higher-level devices, such as human-machine interfaces (HMI) that enable centralized data visualization, or to programmable logic controllers (PLC) or centralized monitoring systems with more comprehensive data analysis tools (including AI and ML) (Figure 2).
Omron PdM solution suite that can be deployed separately (click to enlarge)
Figure 2: Omron's PdM solution suite can be deployed separately, starting with small-scale monitoring of critical assets and gradually expanding to the entire manufacturing or logistics site, providing a comprehensive solution. (Image source: Omron)
Deeply explore
Omron offers a range of PdM devices and software. For example, the S8VK-X Ethernet connected smart power supply can measure multiple performance parameters, including Vout and Iout for monitoring energy consumption, as well as IPEAK for determining overload conditions.
This type of power supply can measure actual operating time. This type of power supply also uses the Arrhenius equation to estimate the remaining life of electrolytic capacitors, which indicates that for every 10 ℃ increase in capacitor temperature, its life is approximately halved. By combining the actual operating temperature of the equipment, the predicted results are ultimately displayed in the form of remaining years or percentage of lifespan.
The rated power of the S8VK-X power supply is 30 W to 480 W, with output voltages of 5 VDC, 12 VDC, and 24 VDC. This series of power supplies also offers models with integrated displays, such as the S8VK-X48024A-EIP power supply, which has a rated voltage of 24 VDC and a power of 480 W; or models without integrated displays, such as the S8VK-X03005-EIP power supply, which has a rated voltage of 5 VDC and a power of 30 W.
Motor status monitoring is an important aspect of PdM technology, and Omron's K6CM motor maintenance monitor is suitable for all types of water pumps, as well as motors in HVAC, agriculture, escalators, and most other motor applications.
The motor maintenance monitor can be used to monitor vibration and temperature, insulation resistance, and motor current. In addition, there are models suitable for three-phase input power supplies ranging from 100 V to 240 VAC, 24 VAC, or 24 VDC.
K6CM-VBMD-EIP can monitor vibration and temperature through 24 VAC/VDC voltage. All temperature monitors are used in conjunction with the K6CM-VB1 vibration and temperature sensor, which consists of a sensor head located on the motor and a preamplifier connecting it to the monitor.
The combination of K6CM-ISMD-EIP and K6CM-ISZBI52 zero current transformer (ZCT) and insulation resistance conversion (IRT) sensor operating at 24 VAC or 24 VDC voltage can monitor the health status of insulation resistance. The ZCT function is used to measure leakage current in three-phase motor circuits, while the IRT function is used to measure insulation resistance between motor windings and ground.
The combination of K6CM-CIMA-EIP with a working voltage of 100 VAC to 240 VAC and K6CM-CICB400 current sensor with a rated current of 400 A can also detect the motor status of three-phase induction motors. Other models of current sensors with a current range of 5 A to 600 A can also be used.
These monitors use Omron's complete current diagnostic technology, which can detect abnormal conditions such as air pockets or air pollution by quantifying the deviation between the ideal sine wave and the measured current waveform. By analyzing the frequency components of the measured current waveform, deviations, load imbalances, or foreign object adhesion can be quantified.
The K6PM thermal state monitoring system can be used to implement PdM technology on various industrial equipment, such as high-voltage control panels, transformers, hydraulic equipment, data centers, bearings, gearboxes, etc. The system includes the K6PM-THS3232 thermal imaging controller and the K6PM-THMD-EIP thermal imaging infrared (IR) sensor, which can monitor temperatures from 0 ° C to+200 ° C.
A K6PM thermal state controller can monitor up to 31 IR sensors. Free PC monitoring software includes abnormal temperature detection algorithm and three-level temperature alarm. The software also supports user-defined alarm thresholds.