Abstract: Systems and methods described herein relate to an asset risk predictor that may receive data corresponding to one or more industrial assets and generate a device model corresponding to the one or more industrial assets. The device model may indicate a relationship between a normal operation of a first industrial asset and data acquired by a second industrial asset. The device model may be trained while the first industrial asset and the second industrial asset are in situ and operating within a desired industrial automation process. An alert score may be generated based on the relationship indicated by the device model, where the alert score may be an indication of a likelihood of an event occurring at the first industrial asset. A maintenance work order may be generated based on alert scores and existing work orders.

Abstract: An industrial work order analysis system applies statistical and machine learning analytics to both open and closed work orders to identify problems and abnormalities that could impact manufacturing and maintenance operations. The analysis system applies algorithms to learn normal maintenance behaviors or characteristics for different types of maintenance tasks and to flag abnormal maintenance behaviors that deviate significantly from normal maintenance procedures. Based on this analysis, embodiments of the work order analysis system can identify unnecessarily costly maintenance procedures or practices, as well as predict asset failures and offer enterprise-specific recommendations intended to reduce machine downtime and optimize the maintenance process.

Abstract: An industrial work order analysis system applies statistical and machine learning analytics to both open and closed work orders to identify problems and abnormalities that could impact manufacturing and maintenance operations. The analysis system applies algorithms to learn normal maintenance behaviors or characteristics for different types of maintenance tasks and to flag abnormal maintenance behaviors that deviate significantly from normal maintenance procedures. Based on this analysis, embodiments of the work order analysis system can identify unnecessarily costly maintenance procedures or practices, as well as predict asset failures and offer enterprise-specific recommendations intended to reduce machine downtime and optimize the maintenance process.

Abstract: A method for producing exosomes in a large-scale by using a cyclic tensile bioreactor to stimulate cells to release exosomes. In addition, the exosome having an anti-HLA-G protein specific for cancer is used as a delivery vehicle to deliver therapeutic agents for treating cancer.

Abstract: An industrial work order analysis system applies statistical and machine learning analytics to both open and closed work orders to identify problems and abnormalities that could impact manufacturing and maintenance operations. The analysis system applies algorithms to learn normal maintenance behaviors or characteristics for different types of maintenance tasks and to flag abnormal maintenance behaviors that deviate significantly from normal maintenance procedures. Based on this analysis, embodiments of the work order analysis system can identify unnecessarily costly maintenance procedures or practices, as well as predict asset failures and offer enterprise-specific recommendations intended to reduce machine downtime and optimize the maintenance process.