Cincoze DV-1000 Embedded Computer playing a key role in Predictive Maintenance
Photo Credit To Cincoze

Cincoze DV-1000 Embedded Computer playing a key role in Predictive Maintenance

Cincoze DV-1000 Embedded Computer playing a key role in Predictive Maintenance

With the evolution of IIoT and AI technology, more and more manufacturing industries are introducing predictive maintenance to collect equipment data on-site.

Predictive maintenance collects machine equipment data and uses AI and machine learning (ML) for data analysis, avoiding manual decision-making and strengthening automation to reduce the average cost and downtime of maintenance and increase the accuracy of machine downtime predictions.

These factors extend machine lifetime and enhance efficiency, and in turn increase profits. Cincoze’s Rugged Computing – DIAMOND product line includes the high-performance and essential embedded computer series DV-1000, integrating high-performance computing and flexible expansion capabilities into a small and compact body.

The system can process large amounts of data in real time for data analytics. It is the ultimate system for bringing preventive maintenance to industrial sites with challenging conditions.

Strong Computing Power

Performance is the top priority. It lies at the core of predictive maintenance, where data from different devices must be collected, processed, and analyzed in real-time, and then connected with a cloud platform.

The high-performance and essential embedded computer series DV-1000 offers high-performance computing, supporting a 9/8th gen Intel® Core™ i7/i5/i3 (Coffee Lake-R S series) processor and up to 32GB of DDR4 2666 MHz memory.

Storage options include a 2.5″ SATA HDD/SSD tray, 2× mSATA slots, 1× M.2 Key M 2280, and NVMe high-speed SSD. The DV-1000 meets the performance requirements necessary for multi-tasking and on-site data analytics in smart manufacturing and can also be used in fields such as machine vision and railway transportation.

Built-in I/O and Modular Expansion

The key to on-site predictive maintenance is the connection to various pieces of equipment, requiring integrated sensors to collect information such as vibration, sound, temperature, voltage, and weight, for big data analytics.

The DV-1000’s built-in I/O is equipped with the most appropriate I/O interfaces for industrial applications, including 2× GbE LAN, 2× COM, and 6× USB, to connect to different types of sensors and other equipment. Cincoze’s exclusive CMI modular technology enables flexible expansion of COM or DIO, and MEC modules provide USB3.0, and LAN expansion, easily meeting predictive maintenance requirements of various sensor interfaces and networking capabilities.

Robust, Wide Temperature Design with Industrial Certification

Harsh industrial environments are a huge challenge for the stable operation of predictive maintenance.

The DV-1000 uses all industrial grade components to withstand wide temperatures (-40°C- 70°C) and implements protection measures like wide voltage (9-48VDC). Even with the interference experienced in various harsh environments, the DV-1000 still operates reliably. Its body is the size of an A5 piece of paper, allowing easy installation even in space-restricted industrial areas.

The DV-1000’s robust design has received many industry-specific certifications, such as EMC and the US Military Standard (MIL-STD-810G), ensuring its reliability as a high-performance computing system that may be the key for companies needing to introduce predictive maintenance.

Cincoze DV-1000 Embedded Computer playing a key role in Predictive Maintenance

Post source : Cincoze

About The Author

Anthony brings a wealth of global experience to his role as Managing Editor of Highways.Today. With an extensive career spanning several decades in the construction industry, Anthony has worked on diverse projects across continents, gaining valuable insights and expertise in highway construction, infrastructure development, and innovative engineering solutions. His international experience equips him with a unique perspective on the challenges and opportunities within the highways industry.

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