Abstract: A control system employs a model-based multi-variable predictive control for cold rolling mills to improve sheet thickness uniformity to meet or exceed specifications in flatness. Sheet metal thickness and flatness deviations from standard requirements are significantly reduced with attendant improved control accuracy as compared to traditional control approaches that use PID based closed loop controls. The control system is particularly suited for control of 4-hi non-reversible single-stand metal rolling mills. The mill stand has a first work roll and a second work roll respectively positioned between a first back up roll and a second back up roll. A plurality of sensors measures and acquires property data of the sheet of material. A model predictive controller manipulates actuators to regulate thickness and flatness.

Abstract: Control system for cold rolling mills to improve sheet metal thickness uniformity. Sensors monitor the state of the cold rolling mill by measuring (i) roll eccentricity, (ii) roll slips during mill operation, (iii) mill disturbances from roll speed or roll force manifestations, and (iv) unknown disturbances referred to as process noise. The controller analyzes data from sensors to compensate. Data collected during the mill operation by the sensors are delayed in reaching the controller. This communication delay is accounted for by using a filter. Since an objective of the controller software is dynamic identification of eccentricity of the back up rolls, which is non-linear by nature, an Extended Kalman Filter may be used.

Abstract: An apparatus, method, and non-transitory machine-readable medium provide for 360° assistance for a QCS scanner with mixed reality (MR) and machine learning technology. The apparatus includes an optical sensor, a display, a Chatbot, cloud service, and a processor operably connected to the optical sensor and the display. The processor receives diagnostic information from a server related to a field device in an industrial process control and automation system; identifies an issue of the field device based on the diagnostic information; detects, using the optical sensor, the field device corresponding to the identified issue; guides, using the display, a user to a location and a scanner part of the field device that is related to the issue; provides, using the display, necessary steps or actions to resolve the issue; and connects, using a cloud server, a user to get modules of installation, commissioning, annual maintenance (AMC) and training for a quality control system (QCS) as per the selected persona.

Abstract: The present invention relates to the filed of simulation of molecular interactions for assessing diseases and disease therapies.

Abstract: An apparatus, method, and non-transitory machine-readable medium provide for 360° assistance for a QCS scanner with mixed reality (MR) and machine learning technology. The apparatus includes an optical sensor, a display, a Chatbot, cloud service, and a processor operably connected to the optical sensor and the display. The processor receives diagnostic information from a server related to a field device in an industrial process control and automation system; identifies an issue of the field device based on the diagnostic information; detects, using the optical sensor, the field device corresponding to the identified issue; guides, using the display, a user to a location and a scanner part of the field device that is related to the issue; provides, using the display, necessary steps or actions to resolve the issue; and connects, using a cloud server, a user to get modules of installation, commissioning, annual maintenance (AMC) and training for a quality control system (QCS) as per the selected persona.