A manufacturing support system may be provided. The manufacturing support system may comprise: an obtaining unit (IO) configured to obtain object data of an object to be manufactured; an artificial intelligence, Al, engine (20) configured to receive the object data as an input and to determine a hardware configuration of a manufacturing system for manufacturing the object with reference to information relating to available hardware for the manufacturing system; and an output unit (60) configured to output the determined hardware configuration.

The system performs a process for creating robotic control code for manufacturing products. A Designer UI displays virtual parts and receives inputs for processing and assembling the virtual parts that are required to create a virtual product. The designer identifies options for processing and assembling the virtual parts which are displayed on the user interface. The robot abilities and the options are selected to optimize a metric of the product manufacturing. The inventive toolset produces the robot control codes for performing a sequence of robotic abilities with the selected options to product the product. The robot control codes are used by a simulator which manipulates virtual robots and virtual parts to create a virtual product to check the robot control code. The verified robot control code is used to control real robots to create the product.

The invention proposes producing finished parts for a finished product from blanks in a fully automatic process, the blanks being removed from a warehouse and worked by way of automatically defined tools in working stations of a production line in a defined working sequence to form the finished parts.

Embodiments herein generally relate to methods, systems and devices for automated assembly of building structures. In at least one embodiment, there is provided a method for automated assembly of building structures, the method comprises analyzing assembly data associated with a building structure; based on the analyzing, determining an assembly sequence for assembling building parts to construct the building structure, wherein the assembly sequence comprises a plurality of assembly tasks; generating robot-specific control instructions, for each of one or more assembly robots in a robotic assembly cell, to execute the assembly sequence; and transmitting the robot-specific control instructions to the one or more assembly robots in the robotic assembly cell.

An apparatus is configured including an information obtaining unit that extracts information on plural parts' attributes, locations, and adjoining relations with other parts; a unit that sorts parts by part type and detects a distinctive shape from 3D CAD model; a unit that represents adjoining relations between parts in an assembly graph; a unit that creates disassembling directions and a disassembling sequence based on the assembly graph and, by reversing them, derives an assembling sequence and assembling directions; a unit that computes an index indicating a quality of easiness of assembling a part by subtracting the sum of deficiency points per part from a reference score; a unit that creates virtual worker positions, postures, and viewpoints according to assembling sequence and evaluates workability; and a unit that computes an evaluation value per part by the index of easiness of assembling the part and a total evaluation value of assembly workability.

Embodiments herein generally relate to methods, systems and devices for automated assembly of building structures. In at least one embodiment, there is provided a robotic assembly cell for assembling building structures. The robotic assembly cell comprises a perception sensor system; one or more assembly robots; and at least one processor operable to: receive instructions corresponding to an assembly sequence for assembling a building structure; determine a plurality of building parts required for assembling the building structure based on the assembly sequence; identify each building part within a facility, based on sensor data from the perception sensor system; configure the assembly robot to retrieve the target pieces; and configure the assembly robot to assemble the target pieces according to the assembly sequence.

A method is disclosed for generating a manufacturing model for a medical implant. In the method, image data of a body region is provided, and regions corresponding to structures of different tissue are segmented; a shape of the implant is defined on the basis of the regions corresponding to the structures and an interaction with the implant is determined for at least one structure in a patient-specific manner on the basis of the image data; for a number of structures, the respective interaction with the implant is checked for an exceedance of a critical stress; and the shape of the implant is defined as a manufacturing model. The manufacturing model is then stored on a non-transitory data carrier and/or output via an interface if the critical stress is not exceeded for any checked interaction of the implant with the respective structure.

Embodiments herein generally relate to methods, systems and devices for automated assembly of building structures. In at least one embodiment, there is provided a robotic assembly cell for assembling building structures. The robotic assembly cell comprises a perception sensor system; one or more assembly robots; and at least one processor operable to: receive instructions corresponding to an assembly sequence for assembling a building structure; determine a plurality of building parts required for assembling the building structure based on the assembly sequence; identify each building part within a facility, based on sensor data from the perception sensor system; configure the assembly robot to retrieve the target pieces; and configure the assembly robot to assemble the target pieces according to the assembly sequence.

Methodologies and a device for simulating individual process steps and producing parameters representing each individual process signal profile are provided. Embodiments include collecting, by way of a programmed processor, wafer level data in the form of electrical signatures during processing steps in the production of a semiconductor device; converting the electrical signatures during each of the processing steps into signal matrix (MS) modeling parameters; comparing the MS modeling parameters to predefined MS modeling parameters; and adjusting at least one processing step based on a result of the comparing step for process control.

Embodiments herein generally relate to methods, systems and devices for automated assembly of building structures. In at least one embodiment, there is provided a method for automated assembly of building structures, the method comprises analyzing assembly data associated with a building structure; based on the analyzing, determining an assembly sequence for assembling building parts to construct the building structure, wherein the assembly sequence comprises a plurality of assembly tasks; generating robot-specific control instructions, for each of one or more assembly robots in a robotic assembly cell, to execute the assembly sequence; and transmitting the robot-specific control instructions to the one or more assembly robots in the robotic assembly cell.