A numerical value controller for a machine tool includes a storage unit storing a machining program for drilling a hole in a workpiece in accordance with relative movement between a tool and workpiece in a depth direction, and a control unit controlling the relative movement between the tool and workpiece based on the machining program and that moves the tool relative to the workpiece in the depth direction from a return point to a hole bottom point. The return point is a position retracted in the depth direction from a workpiece surface where the tool starts to perform drilling. The machining program includes a command for a workpiece height point as a position of the workpiece surface. The control unit moves the tool relative to the workpiece in the depth direction at a relative rate higher than a cutting feed rate from the return point to the height point.

A method and a device are provided for simplifying a flow-hole screw process, in which the difference between a process parameter and its smoothed value is employed as a criterion for changing said process parameter or another process parameter in order in particular to be able to determine the changeover point between hole forming and thread forming.

A drilling machine and a drilling method including drilling a first bore in a material with a drilling machine by applying a torque to a drilling tool for imparting a rotation at a first rotational speed to the drilling tool, and applying a thrust to the drilling tool for advancing the drilling tool at a first feed speed into the material, wherein a drilling parameter is measured while drilling the first bore, and a second rotational speed and a second feed speed are determined based on the drilling parameter, then drilling a second bore at the second rotational speed and at the second feed speed.

Provided is a technique that enables appropriate speed adjustment in a speed-adjusted section and inhibition of burring and tool damage without unduly extending cycle time. A speed adjustment device according to the present invention is provided with: a storage unit that stores a calculation method for an adjusted speed of a driving axis in a speed-adjusted section, the adjusted speed being determined in accordance with a tool being used, the shape of a workpiece in the speed-adjusted section, and path information; a speed-adjusted section identification unit that identifies the speed-adjusted section and the shape of the workpiece in the speed-adjusted section on the basis of shape data of the workpiece and the path information; and an adjusted speed calculation unit that determines the calculation method for the adjusted speed of the driving axis in the speed-adjusted section on the basis of tool data, the shape of the workpiece in the identified speed-adjusted section, the path information, and stored information that is stored in the storage unit, and calculates the adjusted speed in the speed-adjusted section on the basis of the determined calculation method.

A method for a well includes obtaining a dynamic input parameter combination for the well, determining measurements for a rotating control device using a sensor, and predicting a rotating control device wear estimate using rotating control device estimation methods, the measurements, and the dynamic input parameter combination. The method for a well further includes maximizing an instantaneous rate of penetration, while reducing rotating control device failure, to determine an optimized average rate of penetration using the rotating control device wear estimate. Finally, the optimized average rate of penetration is executed for a well.

A system includes a core drill and an automatic feed device. The core drill has a human machine interface (HMI) for controlling the core drill and the automatic feed device. A menu navigation of the HMI is automatically controllable in dependence on an operating state of the core drill or the automatic feed device. The menu navigation includes menu pages where the menu pages are displayable in dependence on the operating state of the core drill or the automatic feed device such that the menu navigation is controllable automatically depending on the operating state of the core drill or the automatic feed device.

Described herein are methods and manufacturing systems that select fasteners for pre-feeding and, in some examples, pre-feed the selected fasteners. These methods involve aggregating historical manufacturing data, comprising hole identifications and fastener grip lengths, previously selected for these hole identifications. A specific grip length and a corresponding fastener repeatability rating are then determined for each hole identification from this historical manufacturing data. For example, a specific grip length corresponds to the most frequently selected grip length for this hole identification. In some examples, the historical manufacturing data is analyzed using machine learning. The fastener repeatability rating is compared to an operating threshold, in some examples, to determine if the corresponding grip length should be selected for a particular hole location. This grip length selection is then used for pre-feeding a corresponding fastener into an automated drilling machine, thereby saving significant processing time relative to conventional processes.

Described herein are methods and manufacturing systems that select fasteners for pre-feeding and, in some examples, pre-feed the selected fasteners. These methods involve aggregating historical manufacturing data, comprising hole identifications and fastener grip lengths, previously selected for these hole identifications. A specific grip length and a corresponding fastener repeatability rating are then determined for each hole identification from this historical manufacturing data. For example, a specific grip length corresponds to the most frequently selected grip length for this hole identification. In some examples, the historical manufacturing data is analyzed using machine learning. The fastener repeatability rating is compared to an operating threshold, in some examples, to determine if the corresponding grip length should be selected for a particular hole location. This grip length selection is then used for pre-feeding a corresponding fastener into an automated drilling machine, thereby saving significant processing time relative to conventional processes.

Described herein are methods and manufacturing systems that select fasteners for pre-feeding and, in some examples, pre-feed the selected fasteners. These methods involve aggregating historical manufacturing data, comprising hole identifications and fastener grip lengths, previously selected for these hole identifications. A specific grip length and a corresponding fastener repeatability rating are then determined for each hole identification from this historical manufacturing data. For example, a specific grip length corresponds to the most frequently selected grip length for this hole identification. In some examples, the historical manufacturing data is analyzed using machine learning. The fastener repeatability rating is compared to an operating threshold, in some examples, to determine if the corresponding grip length should be selected for a particular hole location. This grip length selection is then used for pre-feeding a corresponding fastener into an automated drilling machine, thereby saving significant processing time relative to conventional processes.

A system includes a core drill and an automatic feed device. The core drill has a human machine interface (HMI) for controlling the core drill and the automatic feed device. A menu navigation of the HMI is automatically controllable in dependence on an operating state of the core drill or the automatic feed device. The menu navigation includes menu pages where the menu pages are displayable in dependence on the operating state of the core drill or the automatic feed device such that the menu navigation is controllable automatically depending on the operating state of the core drill or the automatic feed device.