The invention relates to a modular conveyor system, comprising multiple individual conveyor modules, wherein an individual conveyor module comprises at least one conveyor device, at least one power supply, at least one actuator for driving the conveyor device, an output unit for the control of the actuator and an integrated control unit, wherein the integrated control unit has a computing unit for processing information and a communications unit, and wherein the communications unit is designed to carry out the communication of the individual conveyor modules with a central control system, on the one hand, and/or the communication of the individual conveyor modules with one another, on the other hand, in such a way that the communication of the individual conveyor modules with one another is implemented at two logical communication levels. The invention further relates to a method for controlling modular conveyor systems.

Implementations described herein generally relate to a method for detecting anomalies in time-series traces received from sensors of manufacturing tools. A server feeds a set of training time-series traces to a neural network configured to derive a model of the training time-series traces that minimizes reconstruction error of the training time-series traces. The server extracts a set of input time-series traces from one or more sensors associated with one or more manufacturing tools configured to produce a silicon substrate. The server feeds the set of input time-series traces to the trained neural network to produce a set of output time series traces reconstructed based on the model. The server calculates a mean square error between a first input time series trace of the set of input time series traces and a corresponding first output time series trace of the set of output time-series traces. The server declares the sensor corresponding to the first input time-series trace as having an anomaly when the mean square error exceeds a pre-determined value.

Systems and methods to provide low carbon intensity (CI) hydrogen through one or more targeted reductions of carbon emissions based upon an analysis of carbon emissions associated with a combination of various options for feedstock procurement, feedstock refining, processing, or transformation, and hydrogen distribution pathways to end users. Such options are selected to maintain the total CI (carbon emissions per unit energy) of the hydrogen below a pre-selected threshold that defines an upper limit of CI for the hydrogen.

Conveyor system, for instance for conveying goods, packages and the like including at least two wired motor-roller controllers, wherein each wired motor-roller controller has at least one motor-roller control port and at least one wired signal bus port, at least two wireless motor-roller controllers, wherein each wireless motor-roller controller has at least on motor-roller control port and a wireless port, and wherein the two wired motor-roller controllers are connected in series along the signal bus via the signal bus port, wherein at each wired motor-roller controller senses a signal strength of wireless signals of the wireless motor-roller controllers, and the wired motor-roller controllers exchange information about the sensed signal strengths.

In order to efficiently convey a conveyance target, a conveyance system includes: a carriage configured to be capable of conveying a plurality of conveyance targets; and a carriage controller configured to perform an allocation process of allocating, to the carriage, a conveyance target to be conveyed, the carriage controller performing the allocation process such that, in a case where a region in which the carriage is movable is divided into a plurality of areas, areas of destinations of the plurality of conveyance targets that are to be simultaneously conveyed by the carriage are the same.

Asynchronous conveyor networks serving as inter-process transport mechanisms eliminate transport capacity constraints of vehicle-based systems in integrated circuit (IC) manufacturing environments. Demand variability may be buffered without the use of off-line-storage such as stockers. The variability in wait times for transport service is also eliminated. Overall factory cycle times are thus reduced while manufacturing capacity is simultaneously increased. An autonomous conveyor network automated materials handling system combines clean frictionless conveyor principles with a unique network layout to fulfill the logistics requirements of IC manufacturing environments. Mechanical conveyor-to-tool interfaces, also referred to as equipment delivery interfaces (EDi's), bridge the conveyor network to individual tools. An operating software module integrates the functionality of the conveyor network and EDi's. The result is a full capability factory logistics system.

There is provided a machining system in which for automation of loading and unloading of an article with respect to a machining device, an operation of a robot can be easily set from a machine controller of the machining device. The machining system includes a machine controller and a robot controller. The machine controller includes a communication section configured to read from a storage section setting data and a robot operation program which correspond to the type of the machined article as set by a setting section when a determination section determines that the moving robot is disposed at a predetermined position, and transmit the same to the robot controller.

Methods and systems for training a robotic manipulator. The system may include one or more sensor devices and a robotic manipulator for executing an item grasping strategy to grasp an item. The system may further evaluate the item grasping strategy to determine whether the strategy was successful.

Methods and systems for assessing a robotic grasping technique. The system in accordance with various embodiments may include a warehouse management system for retrieving and storing items, a robotic manipulator for grasping an item, and analysis module configured to receive data regarding a first grasp attempt by the robotic manipulator and analyze the received data to determine whether the robotic manipulator successfully grasped the item.

A substrate processing method is provided. The substrate processing method includes placing a substrate storage container storing a substrate on a load port; automatically determining a type of the substrate stored in the placed substrate storage container; by referring to a storage unit that stores a parameter data set related to a transport condition for each substrate type, controlling transport of the substrate stored in the substrate storage container based on the parameter data set corresponding to the automatically determined type of the substrate to process the substrate, and, after automatically determining the type of the substrate, and before transporting the substrate stored in the substrate storage container, performing mapping based on conditions set in the parameter data set to detect an abnormality of the substrate stored in the substrate storage container.