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VISIBILITY - Currently unable to see amount of power consumed per machine or plant; need to account for energy used per batch. WASTE - 10% of product fails quality standards, unable to identify point of failure (initial spinning, weaving, final processing, etc). INACCURACY - Acquiring OEE measurements and compiling them is a manual process, which lacks visibility into all parts of the production process and is error-prone. LACK OF INTEROPERABILITY - Outdated machinery still has long, effective lifespans but needs to connect to newer, digital assets
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Cisco IoE innovation Centers around the world enable and showcase local innovation and development. relayr had the unique opportunity to be involved in building the connected openBerlin infrastructure from the very beginning. In a building that was conceived from the outset to be completely monitored and controlled by smart systems, relayr set up the middle layer of connectivity – joining all of the separate legacy systems to allow meaningful cross-platform communication.
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In the Buildings space, connecting to the data in various systems has always been difficult and complicated; controlling those systems was even harder. The number of proprietary gateways, layers of complicated technology, and disparate programming languages has made it impossible to effectively collect and analyze data or control the various systems in the building without monstrous, bloated building automation applications.
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The client is looking to generate higher value from the elevator data that is collected. Sensors and data include:Laser - position of the elevator carLuminosity - Level of light within the carUltrasound - Open shaft doorVibration - Acceleration of the car; vibration of the carMicrophones - abnormal sounds of the carAtmospheric Pressure - Air pressureHumidity - Shaft humidityTemperature - Shaft temperature
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Machine uptime is one of the most vital performance factors for electric rotating machinery. In times when an hour of downtime can equate to thousands of dollars in losses, securing predictability turns into a high priority for all industrial businesses. Manufacturers operate in an extremely volatile environment, thus avoiding unplanned downtime becomes critical for achieving desired business outcomes. Predictive maintenance is no longer a nice-to-have but a necessity to survive and thrive in unfavourable conditions. Start from the basics. Making machines perform better means, first and foremost, understanding how the machine works, extracting relevant data, and gaining meaningful insights into ongoing processes. The power of the machine lies in utilizing its full potential.
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Buildings, like living organisms, consist of multiple systems that need to function seamlessly round the clock. However, maintaining aging equipment and facilities, dealing with utility issues, and controlling costs are ongoing concerns in the buildings industry. These challenges often undermine the well-being of the end-users, leading to dissatisfaction and lower performance. The various components of buildings usually have a long lifespan, and their management involves high risks and unexpected pitfalls. This situation leaves organizations struggling to focus on their core business while delivering a high-quality experience for end-users.
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