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.
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Cincoze's Embedded Computer DV-1000 Plays a Key Role in Predictive Maintenance (Graphic: Business Wire)
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.
About Cincoze
Cincoze is a rugged embedded computer brand providing diversified embedded computer solutions tailored to market needs. Its product lines include rugged embedded computers, industrial panel PCs, industrial displays, and embedded GPU computers. Cincoze products meet various vertical markets' application needs, especially factory automation, mechanical automation, machine vision, AIoT, robotics, in-vehicle computing, smart transportation, smart warehousing, and logistics. Over the years, Cincoze has launched many innovative products and won several patents, awards and international certifications.
Tags: Panel PC / Fanless PC / embedded computers / GPU computer / AI / Predictive Maintenance / Machine Learning / Industrial IoT / Information Technology / data analytics
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Contacts
Press
Julia Hsiao
Phone: +886-2-8912-1101 ext.1903
E-mail: julia.hsiao@cincoze.com
www.cincoze.com