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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Aizon
Aizon: Intelligent GxP Manufacturing
Aizon delivers an AI-powered platform that redefines how pharmaceutical and biotech manufacturers operate under GxP requirements. Our solutions empower teams to enhance efficiency, raise yields, and maintain the highest standards of product quality.
- Aizon Execute — Intelligent Batch Record (iBR): Digitize production quickly to reduce manual errors, lower deviations, and accelerate the release of compliant batches.
- Aizon Unify — Contextualized Intelligent Lakehouse: Connect and contextualize data from diverse sources to improve decision-making and achieve operational excellence.
- Aizon Predict — GxP AI Industrialization: Use predictive AI models to fine-tune critical process parameters, increase Right-First-Time outcomes, and deliver higher manufacturing performance.
Aizon enables manufacturers to move beyond traditional compliance and embrace true operational intelligence—learning from the past, acting decisively in the present, and innovating for the future.
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Aspen DMC3
Improve accuracy and sustainability in advanced process control (APC) frameworks by merging linear and nonlinear variables through advanced deep learning methodologies, thus enhancing their functional effectiveness. Realize better returns on investment through rapid deployment of controllers, consistent model adjustments, and optimized workflows that make it easier for engineers to adopt these systems. Revolutionize model development with the aid of artificial intelligence and simplify the calibration of controllers by employing guided wizards that define both linear and nonlinear optimization objectives. Increase controller uptime by utilizing cloud solutions for the retrieval, visualization, and analysis of real-time key performance indicators (KPIs). In today's fast-paced global economy, the energy and chemical sectors must adapt with greater flexibility to market fluctuations to maximize profit margins. Aspen DMC3 stands out as a cutting-edge digital tool that helps organizations achieve a throughput increase of 2-5%, a yield boost of 3%, and a 10% reduction in energy consumption. Delve into the advantages provided by next-generation advanced process control technologies to maintain competitiveness and efficiency in the sector. The incorporation of these innovative solutions not only tackles pressing operational issues but also equips companies for enduring success in a marketplace that is becoming increasingly competitive. Additionally, embracing these advancements can foster a culture of continuous improvement, further driving operational excellence.
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MPCPy
MPCPy is a Python-based library specifically created to facilitate the testing and implementation of occupant-integrated model predictive control (MPC) in building systems. This innovative tool focuses on utilizing data-driven, simplified physical or statistical models to predict the performance of buildings and improve control methodologies. It consists of four key modules that offer object classes for tasks such as data importation, engagement with either real or simulated systems, estimation and validation of data-driven models, and optimization of control inputs. While MPCPy acts as a comprehensive integration platform, it relies on a variety of free, open-source third-party software for executing models, conducting simulations, implementing parameter estimation techniques, and optimizing solvers. This includes Python libraries for scripting and data manipulation, as well as specialized software solutions designed for specific functions. Importantly, the tasks involving modeling and optimization of physical systems are currently based on the requirements of the Modelica language, which significantly enhances the package's flexibility and capabilities. Overall, MPCPy empowers users to harness sophisticated modeling methods within a dynamic and cooperative environment, ultimately fostering improved building system performance. Furthermore, it opens up opportunities for researchers and practitioners alike to experiment with cutting-edge control strategies tailored to real-world scenarios.
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