Epicor Connected Process Control
Epicor Connected Process Control offers an intuitive software solution designed to create and manage digital work instructions while maintaining strict process control, effectively minimizing the chances of errors in operations. By integrating IoT devices, it captures comprehensive time studies and detailed process data, including images, at the task level, providing unprecedented real-time visibility and quality oversight. The eFlex system is versatile enough to accommodate countless product variations and thousands of components, catering to both component-based and model-based manufacturers alike. Furthermore, work instructions seamlessly connect to the Bill of Materials, guaranteeing that products are assembled correctly every time, even when modifications occur during production. This advanced system intelligently adapts to variations in models and components, ensuring that only the relevant work instructions for the current build at the station are presented, enhancing efficiency and accuracy throughout the manufacturing process. In this way, Epicor empowers manufacturers to maintain high standards of quality control while adapting to the dynamic nature of production demands.
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TRACTIAN
Tractian serves as the Industrial Copilot focused on enhancing maintenance and reliability by integrating both hardware and software to oversee asset performance, streamline industrial operations, and execute predictive maintenance approaches. The platform, powered by AI, enables companies to avert unexpected equipment failures and improve production efficiency. Headquartered in Atlanta, GA, Tractian also has a global footprint with branches in Mexico City and Sao Paulo, thereby expanding its reach. For more information, you can visit their website at tractian.com, where additional resources and details about their offerings are available.
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Azure Digital Twins
Azure Digital Twins serves as an IoT platform enabling the creation of digital replicas of physical entities, spaces, processes, and people. This innovative platform yields critical insights that can significantly improve product development, optimize operational efficiency, lower costs, and enhance customer satisfaction. It provides an intuitive framework for crafting digital representations of interconnected settings using a flexible modeling language. Users can model a wide variety of entities, including buildings, manufacturing plants, agricultural fields, energy systems, transportation networks, sports facilities, and even entire cities. These digital twins come alive in a dynamic execution environment that monitors changes over time. By utilizing powerful query APIs, users can glean actionable insights into the behaviors of their modeled environments and easily integrate with Azure's data analytics services. The open modeling language allows for the creation of customized domain models tailored to any connected setting through the Digital Twins Definition Language, ensuring adaptability across various applications. Thus, Azure Digital Twins not only supports business innovation but also enables organizations to adjust effectively in an ever-evolving digital landscape, making it an invaluable tool for modern enterprises.
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DC-E DigitalClone for Engineering
DigitalClone® for Engineering stands out as the sole software that seamlessly combines various scales of analysis within a unified platform. Recognized globally as the premier tool for predicting gearbox reliability, DC-E excels not only in its modeling and analysis capabilities specific to gearboxes and gear/bearing interactions but also uniquely incorporates fatigue life modeling through advanced, physics-based methodologies (US Patent 10474772B2).
By enabling the creation of a digital twin for gearboxes, DC-E encompasses every phase of an asset's lifecycle—from the optimization of design and manufacturing processes to the selection of suppliers, followed by thorough root cause analysis of failures and condition-based maintenance along with prognostics. This innovative computational environment significantly decreases both the time and costs associated with launching new designs and ensuring their long-term maintenance, ultimately enhancing operational efficiency. Moreover, it empowers engineers to make informed decisions at every stage, leading to improved performance and reliability.
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