This disclosure is directed to techniques for utilizing various sensors and models to evaluate glass as it progresses through the tempering process in order to ensure that the tempered glass is of a proper quality. If, according to any of the various sensor measurements, the tempered glass is not of a proper quality, the system may automatically adjust one or more settings in any of the various components of the system in order to bring future panes of tempered glass back to having the proper quality. The system can measure for any number of glass characteristics or system characteristics, including edge quality, vertical flatness, haze, washing process variables, thermal imaging, distortion, blower information, production data, and furnace process data.

Glass laminates, comprising more than one glass composition, are becoming increasingly common as the industry moves towards lighter and stronger glazing. Bending dissimilar glass compositions can present problems. A mismatch in the glass viscosity curves, especially in the viscoelastic region of the compositions can result in one layer becoming softer than one of the other layers during the thermal bending process. As a result, economical processes, such as gravity or press bending in which multiple glass layers are simultaneously bent, may not be practical to use forcing the use of more expensive single glass layer bending processes. By thermal treatment processes the fictive temperature of at least one of the glass compositions prior to bending can be shifted to better match the other compositions allowing the glass layers to be simultaneously bent.

This disclosure is directed to techniques for utilizing various sensors and models to evaluate glass as it progresses through the tempering process in order to ensure that the tempered glass is of a proper quality. If, according to any of the various sensor measurements, the tempered glass is not of a proper quality, the system may automatically adjust one or more settings in any of the various components of the system in order to bring future panes of tempered glass back to having the proper quality. The system can measure for any number of glass characteristics or system characteristics, including edge quality, vertical flatness, haze, washing process variables, thermal imaging, distortion, blower information, production data, and furnace process data.

This disclosure is directed to techniques for utilizing various sensors and models to evaluate glass as it progresses through the tempering process in order to ensure that the tempered glass is of a proper quality. If, according to any of the various sensor measurements, the tempered glass is not of a proper quality, the system may automatically adjust one or more settings in any of the various components of the system in order to bring future panes of tempered glass back to having the proper quality. The system can measure for any number of glass characteristics or system characteristics, including edge quality, vertical flatness, haze, washing process variables, thermal imaging, distortion, blower information, production data, and furnace process data.

Glass laminates, comprising more than one glass composition, are becoming increasingly common as the industry moves towards lighter and stronger glazing. Bending dissimilar glass compositions can present problems. A mismatch in the glass viscosity curves, especially in the viscoelastic region of the compositions can result in one layer becoming softer than one of the other layers during the thermal bending process. As a result, economical processes, such as gravity or press bending in which multiple glass layers are simultaneously bent, may not be practical to use forcing the use of more expensive single glass layer bending processes. By thermal treatment processes the fictive temperature of at least one of the glass compositions prior to bending can be shifted to better match the other compositions allowing the glass layers to be simultaneously bent.

This disclosure is directed to techniques for utilizing various sensors and models to evaluate glass as it progresses through the tempering process in order to ensure that the tempered glass is of a proper quality. If, according to any of the various sensor measurements, the tempered glass is not of a proper quality, the system may automatically adjust one or more settings in any of the various components of the system in order to bring future panes of tempered glass back to having the proper quality. The system can measure for any number of glass characteristics or system characteristics, including edge quality, vertical flatness, haze, washing process variables, thermal imaging, distortion, blower information, production data, and furnace process data.

This disclosure is directed to techniques for utilizing various sensors and models to evaluate glass as it progresses through the tempering process in order to ensure that the tempered glass is of a proper quality. If, according to any of the various sensor measurements, the tempered glass is not of a proper quality, the system may automatically adjust one or more settings in any of the various components of the system in order to bring future panes of tempered glass back to having the proper quality. The system can measure for any number of glass characteristics or system characteristics, including edge quality, vertical flatness, haze, washing process variables, thermal imaging, distortion, blower information, production data, and furnace process data.