Abstract: Methods, apparatus, and processor-readable storage media for automated storage capacity provisioning using machine learning techniques are provided herein. An example computer-implemented method includes obtaining a user-provided input comprising an identification of an amount of storage capacity to be provisioned from a storage system; determining an amount of time for which the amount of storage capacity to be provisioned will last in connection with the storage system by processing the user-provided input in connection with historical data pertaining to storage utilization using one or more machine learning techniques; outputting, to the user, the determined amount of time for which the amount of storage capacity to be provisioned will last; and performing one or more automated actions based at least in part on feedback from the user in response to the outputting of the determined amount of time for which the amount of storage capacity to be provisioned will last.

Abstract: A three-dimensional (3D) printer includes a base plate and a nozzle connectable to a source of molten material and operable to eject the molten material onto the base plate that are movable in orthogonal directions to form a 3D object on the base plate. An error detection system detects a dislocation of the 3D object on the base plate during the 3D printing operation, which can lead to stopping the 3D printing process. The error detection system includes a beam emitter and a detector that work in conjunction with a tag formed on the 3D object to determine whether the object has dislocated.

Abstract: A three-dimensional (3D) printer includes a base plate and a nozzle connectable to a source of molten material and operable to eject the molten material onto the base plate that are movable in orthogonal directions to form a 3D object on the base plate. An error detection system detects a dislocation of the 3D object on the base plate during the 3D printing operation, which can lead to stopping the 3D printing process. The error detection system includes a beam emitter and a detector that work in conjunction with a tag formed on the 3D object to determine whether the object has dislocated.

Abstract: A build plate supported on a movable carriage of a 3D printing machine includes a plurality of clamping surfaces that are engageable by a mechanical clamping system that includes a plurality of clamp assemblies mounted on the movable carriage. Each of the clamp assemblies is associated with a corresponding clamping surface and includes a clamping arm configured to rotate and translate to selectively engage the corresponding clamping surface, a follower arm configured to rotate, and a conversion mechanism configured to convert rotation of the follower arm to rotation and translation of the clamping arm. An actuation mechanism includes an actuation face, corresponding to each follower arm. The actuation mechanism is arranged to simultaneously exert a force against the follower arm of each of the clamp assemblies to rotate the follower arm as the carriage moves from a working station to an unloading station of the 3D printing machine.

Abstract: Methods, apparatus, and processor-readable storage media for automated storage capacity provisioning using machine learning techniques are provided herein. An example computer-implemented method includes obtaining a user-provided input comprising an identification of an amount of storage capacity to be provisioned from a storage system; determining an amount of time for which the amount of storage capacity to be provisioned will last in connection with the storage system by processing the user-provided input in connection with historical data pertaining to storage utilization using one or more machine learning techniques; outputting, to the user, the determined amount of time for which the amount of storage capacity to be provisioned will last; and performing one or more automated actions based at least in part on feedback from the user in response to the outputting of the determined amount of time for which the amount of storage capacity to be provisioned will last.

Abstract: Determining an optimal path through a storage area network from a specific initiator to a specific target includes determining a plurality of possible paths through the storage area network between the specific initiator and the specific target, examining a plurality of previously-determined latency values for each of the paths, the previously-determined latency values being set according to empirical observation of propagation through each of the paths, and choosing a specific one of the paths having a lowest latency value. The previously-determined latency values may be determined by sending a command from the specific initiator to the specific target. The command may avoid queuing any I/O operations at the specific target. The command may be a status request command or a vendor specific command. The source may be a host system and the target may be a storage system. The previously-determined latency may be measured using a PowerPath Management Appliance.

Abstract: Determining an optimal path through a storage area network from a specific initiator to a specific target includes determining a plurality of possible paths through the storage area network between the specific initiator and the specific target, examining a plurality of previously-determined latency values for each of the paths, the previously-determined latency values being set according to empirical observation of propagation through each of the paths, and choosing a specific one of the paths having a lowest latency value. The previously-determined latency values may be determined by sending a command from the specific initiator to the specific target. The command may avoid queuing any I/O operations at the specific target. The command may be a status request command or a vendor specific command. The source may be a host system and the target may be a storage system. The previously-determined latency may be measured using a PowerPath Management Appliance.

Abstract: Methods, systems, and apparatus, including computer program products, for detecting and estimating lost sales. A demand distribution for a product provided by a retail presence is determined. A probability of a lost sales occurrence is evaluated, including determining a predetermined time period and a probability of no sales over the predetermined time period. A determination of whether no sales have occurred over a time period corresponding in length to the predetermined time period is made. If the probability of no sales is below a threshold, an estimate of lost sales is determined.