Abstract: The present system is a software defined manufacturing (SDM) system that integrates several technologies and methods into a system that automates the process of engineering and operating automated manufacturing systems (aka “automating automation”). In one embodiment, some or all of the below aspects of the “automating automation” system are integrated: modular, configurable, reusable manufacturing cells; computer vision systems; autocalibration systems; a recipe-based programming environment; configuration management system; production analytics; and a marketplace for sharing recipes.

Abstract: A vision analytics and validation (VAV) system for providing an improved inspection of robotic assembly, the VAV system comprising a trained neural network three-way classifier, to classify each component as good, bad, or do not know, and an operator station configured to enable an operator to review an output of the trained neural network, and to determine whether a board including one or more “bad” or a “do not know” classified components passes review and is classified as good, or fails review and is classified as bad. In one embodiment, a retraining trigger to utilize the output of the operator station to train the trained neural network, based on the determination received from the operator station.

Abstract: The present system is a software defined manufacturing (SDM) system that integrates several technologies and methods into a system that automates the process of engineering and operating automated manufacturing systems (aka “automating automation”). In one embodiment, some or all of the below aspects of the “automating automation” system are integrated: modular, configurable, reusable manufacturing cells; computer vision systems; autocalibration systems; a recipe-based programming environment; configuration management system; production analytics; and a marketplace for sharing recipes.

Abstract: A vision analytics and validation (VAV) system for providing an improved inspection of robotic assembly, the VAV system comprising a trained neural network three-way classifier, to classify each component as good, bad, or do not know, and an operator station configured to enable an operator to review an output of the trained neural network, and to determine whether a board including one or more “bad” or a “do not know” classified components passes review and is classified as good, or fails review and is classified as bad. In one embodiment, a retraining trigger to utilize the output of the operator station to train the trained neural network, based on the determination received from the operator station.

Abstract: Methods and apparatus for lamp housing crack detection are provided herein. For example, a method associated with a process chamber having a lamp housing comprises sequentially processing a plurality of substrates in the process chamber, during processing of the plurality of substrates, collecting lamp housing data indicative of a fluid leak in the lamp housing from a sensor operably connected to the lamp housing of the process chamber, determining from the lamp housing data whether lamp housing crack is present, and responsive to determining lamp housing crack is present, at least one of triggering an alert or stopping processing of the process chamber.

Abstract: A vision analytics and validation (VAV) system for providing an improved inspection of robotic assembly, the VAV system comprising a trained neural network three-way classifier, to classify each component as good, bad, or do not know, and an operator station configured to enable an operator to review an output of the trained neural network, and to determine whether a board including one or more “bad” or a “do not know” classified components passes review and is classified as good, or fails review and is classified as bad. In one embodiment, a retraining trigger to utilize the output of the operator station to train the trained neural network, based on the determination received from the operator station.

Abstract: A vision analytics and validation (VAV) system for providing an improved inspection of robotic assembly, the VAV system comprising a trained neural network three-way classifier, to classify each component as good, bad, or do not know, and an operator station configured to enable an operator to review an output of the trained neural network, and to determine whether a board including one or more “bad” or a “do not know” classified components passes review and is classified as good, or fails review and is classified as bad. In one embodiment, a retraining trigger to utilize the output of the operator station to train the trained neural network, based on the determination received from the operator station.

Abstract: The present system is a software defined manufacturing (SDM) system that integrates several technologies and methods into a system that automates the process of engineering and operating automated manufacturing systems (aka “automating automation”). In one embodiment, some or all of the below aspects of the “automating automation” system are integrated: modular, configurable, reusable manufacturing cells; computer vision systems; autocalibration systems; a recipe-based programming environment; configuration management system; production analytics; and a marketplace for sharing recipes.

Abstract: A method for vision-based tool localization (VTL) in a robotic assembly system including one or more calibrated cameras, the method comprising capturing a plurality of images of the tool contact area from a plurality of different vantage points, determining an estimated position of the tool contact area based on an image, and refining the estimated position based on another image from another vantage point. The method further comprises providing the refined position to the robotic assembly system to enable accurate control of the tool by the robotic assembly system.

Abstract: The present system is a software defined manufacturing (SDM) system that integrates several technologies and methods into a system that automates the process of engineering and operating automated manufacturing systems (aka “automating automation”). In one embodiment, some or all of the below aspects of the “automating automation” system are integrated: modular, configurable, reusable manufacturing cells; computer vision systems; autocalibration systems; a recipe-based programming environment; configuration management system; production analytics; and a marketplace for sharing recipes.

Abstract: The present invention provides a liquid formulation comprising a) a triazole an/or pyrazole fungicide; and b) at least one cyclodextrin compound. The present invention also provides a method for inhibiting degradation of a triazole fungicide in a liquid formulation, comprising (a) packaging the formulation in a suitable container; (b) reducing oxygen exposure of the triazole fungicide in the formulation as compared to oxygen exposure of the triazole fungicide when the formulation is in contact with air; and (c) closing or sealing the container.

Abstract: Described herein is a computer-implemented method for deploying a software product to an environment. The method comprises defining an environment lock for the environment, the environment lock being configured to selectively prevent deployment of a software product to the environment. The method further comprises receiving a request from a requesting entity to deploy a designated software product to the environment, determining a status of the environment lock, and either permitting or preventing the deployment of the designated software product to the environment by reference to the determined status of the environment lock.

Abstract: The present system is a software defined manufacturing (SDM) system that integrates several technologies and methods into a system that automates the process of engineering and operating automated manufacturing systems (aka “automating automation”). In one embodiment, some or all of the below aspects of the “automating automation” system are integrated: modular, configurable, reusable manufacturing cells; computer vision systems; autocalibration systems; a recipe-based programming environment; configuration management system; production analytics; and a marketplace for sharing recipes.

Abstract: A vision analytics and validation (VAV) system for providing an improved inspection of robotic assembly, the VAV system comprising a trained neural network three-way classifier, to classify each component as good, bad, or do not know, and an operator station configured to enable an operator to review an output of the trained neural network, and to determine whether a board including one or more “bad” or a “do not know” classified components passes review and is classified as good, or fails review and is classified as bad. In one embodiment, a retraining trigger to utilize the output of the operator station to train the trained neural network, based on the determination received from the operator station.

Abstract: Described herein is a computer-implemented method for deploying a software product to an environment. The method comprises defining an environment lock for the environment, the environment lock being configured to selectively prevent deployment of a software product to the environment. The method further comprises receiving a request from a requesting entity to deploy a designated software product to the environment, determining a status of the environment lock, and either permitting or preventing the deployment of the designated software product to the environment by reference to the determined status of the environment lock.

Abstract: The disclosure provides for methods for reducing dust by treating a seed with a dust reducing composition described herein. The disclosure also provides for methods of reducing exposure to vacuum planter dust released during seed planting by applying a composition described herein to a seed. Methods for increasing seed lubricity by coating a seed with a composition described herein are also provided for. Compositions and seeds useful in these methods are also described.

Abstract: A large, waterproof bag that is sized to fit into the bed of a pick-up truck. The bag is fully sealed by a zipper and an overlapping flap at an opening at one end of the bag. The flap covers and protects the zipper. The waterproof bag is used to store luggage and other goods in a safe, waterproof environment in the truck bed. The bag features eight hook assemblies attached at each corner of two opposed surfaces of the bag that can be used to secure the bag in place during travel.

Abstract: The present disclosure includes, among other things, systems, methods and program products for pre-computing image manipulations.

Abstract: A desalination system and method of desalinating liquids are provided. The desalination system includes a supercapacitor desalination unit. A first liquid source to be desalinated is provided to the supercapacitor desalination unit while the system is in a charging mode of operation. A second liquid source comprising saturated or supersaturated liquid is provided to the supercapacitor desalination unit when the system is in a discharging mode of operation.

Abstract: A large, waterproof bag that is sized to fit into the bed of a pick-up truck. The bag is fully sealed by a zipper and an overlapping flap at an opening at one end of the bag. The flap covers and protects the zipper. The waterproof bag is used to store luggage and other goods in a safe, waterproof environment in the truck bed. The bag features eight hook assemblies attached at each corner of two opposed surfaces of the bag that can be used to secure the bag in place during travel.