SMS Storetraffic
Smart, efficient, anonymous People Counters & Analytics to the real world.
Our solution allows for easy deployment, capture, analysis, and reporting of the number people who enter a physical place. Optionally, we can also capture and report occupancy in real time.
We assist Retailers, Universities, Casinos, Places of Worship, Office Buildings, and other industries in analyzing and taking action on their people traffic trends.
We offer a special package for retailers to measure performance on traffic, including conversion rate and service levels. Our direct integrations make it easy to combine POS data with staff data. The Retail Equation simulator lets users run simulations to improve sales. It can also be used as a learning tool to understand how traffic, staffing, conversion rates, and quality service relate.
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Epicor Connected Process Control
Epicor Connected Process Control provides a simple-to-use software solution that allows you to configure digital work instructions and enforce process control. It also ensures that operations are error-proof. Connect IoT devices to collect 100% time studies and process data, images and images at the task level. Real-time visibility and quality control on a new level! eFlex can handle any number of product variations or thousands of parts, whether you are a component-based or model-based manufacturer. Work instructions can be linked to Bill of Materials, ensuring that products are built correctly every time, even if changes are made during the process. Work instructions that are part a system that is advanced will automatically react to model and component variations and only display the right work instructions for what's currently being built at station.
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Model Predictive Control Toolbox
The Model Predictive Control Toolbox™ offers a comprehensive suite of functions, an intuitive app, Simulink® blocks, and practical reference examples to facilitate the development of model predictive control (MPC) systems. It caters to linear challenges by enabling the creation of implicit, explicit, adaptive, and gain-scheduled MPC strategies. For more complex nonlinear scenarios, users can execute both single-stage and multi-stage nonlinear MPC. Additionally, this toolbox includes deployable optimization solvers and permits the integration of custom solvers. Users can assess the effectiveness of their controllers through closed-loop simulations in MATLAB® and Simulink environments. For applications in automated driving, the toolbox also features MISRA C®- and ISO 26262-compliant blocks and examples, allowing for a swift initiation of projects related to lane keep assist, path planning, path following, and adaptive cruise control. You have the capability to design implicit, gain-scheduled, and adaptive MPC controllers that tackle quadratic programming (QP) problems, and you can generate an explicit MPC controller derived from an implicit design. Furthermore, the toolbox supports discrete control set MPC for handling mixed-integer QP challenges, thus broadening its applicability in diverse control systems. With these extensive features, the toolbox ensures that both novice and experienced users can effectively implement advanced control strategies.
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COLUMBO
A closed-loop universal multivariable optimizer is designed to enhance both the performance and quality of Model Predictive Control (MPC) systems. This optimizer utilizes data from Excel files sourced from Dynamic Matrix Control (DMC) by Aspen Tech, Robust Model Predictive Control Technology (RMPCT) from Honeywell, or Predict Pro from Emerson to develop and refine accurate models for various multivariable-controller variable (MV-CV) pairs. This innovative optimization technology eliminates the need for step tests typically required by Aspen Tech and Honeywell, operating entirely within the time domain while remaining user-friendly, compact, and efficient. Given that Model Predictive Controls (MPC) can encompass tens or even hundreds of dynamic models, the possibility of incorrect models is a significant concern. The presence of inaccurate dynamic models in MPCs leads to bias, which is identified as model prediction error, manifesting as discrepancies between predicted signals and actual measurements from sensors. COLUMBO serves as a powerful tool to enhance the accuracy of Model Predictive Control (MPC) models, effectively utilizing either open-loop or fully closed-loop data to ensure optimal performance. By addressing the potential for errors in dynamic models, COLUMBO aims to significantly improve overall control system effectiveness.
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