A method controls sheet metal processing of a sheet metal component to be manufactured with a plurality of processing steps. The method includes: A) reading in machine tool data and data of the sheet metal component to be manufactured, which includes (in any order): a) reading in the processing steps of the sheet metal component to be manufactured; b) reading in property parameters of the sheet metal component to be manufactured; c) reading in at least one basic processing capability of the machine tools; and d) reading in capability parameters of the machine tools. The method also includes B) creating a machine tool matrix made from machine tools suitable for manufacturing the sheet metal component; C) determining an optimized processing sequence in a form of a sequence of machine tools from the machine tool matrix; and D) outputting the optimized processing sequence.

One embodiment provides a pre fabricated kit for assembling a supporting framework comprising a plurality of customized beams or supports with a connection openings/hole patterns selected from a set of connection hole patterns and using a plurality of generic connectors which fit on the interior of the customized beams or supports.

A work center for automated subtractive machining includes machine frame components, material and parts handling components, control components, and communications components. The machine frame components may include a fixturing system, a CNC, a column, a spindle, and a cutting tool. The material and parts handling components may include material handling robotics, machined part handling robotics, material viewing, machined part viewing, and racks for stock materials, tools, and finished parts. The control components may include robotics controllers, viewer controllers, fixturing control, and an interactive process plan automation control (IPPAC). The IPPAC may include process planning/editing hardware & software, process control hardware & software, a device command interpreter, CAM hardware & software, SCADA hardware & software, which may include SCADA supervisory control and/or SCADA data acquisition components, database hardware & software, and communications hardware & software.

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.

A Web-based system and method creates one or more qualitatively distinct process plans for machining a part. The surfaces of the part are modeled and parameters for a plurality of CNC machining tools are obtained, including the orientations along which the tool cuts away raw material. A maximal set of translations for each tool is also obtained, where each translation includes a collision-free orientation of the tool and a maximal machinable volume of material removable from the part in that orientation. A search engine navigates through a hierarchically-structured search space that starts at an initial state and transitions to successive states based on actions that satisfy a cost constraint function. Each state and each action includes a tool, orientation of the tool, and a maximal machinable volume. The search ends when a goal condition is satisfied. The actions constitute the process plan.

A computer-implemented method for automating manufacturing supply chain planning, comprising: (a) providing a computer processor for processing data; (b) providing at least one input device; (c) providing at least one output device; (d) providing a computer readable storage device; (e) providing a first ontology for defining a product in terms of the method of manufacture of said product or for defining a plurality of products in terms of the method of manufacture of said products; (f) providing a second ontology for defining the capabilities of a plurality of manufacturing facilities; and g) providing a knowledge representation and reasoning system executed on said computer processor.

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.

Producing a product, differently detailed structural information about a structure of the product and digital machining information about a machining process are read in. The structural information is examined as to whether a respective item of structural information is given further detail by a respective other structure. A plurality of machining sequences are generated from the structural information and machining information so that an item of structural information from a first machining sequence is given detail by an item of structural information from a second machining sequence. The first machining sequence is transmitted to a first planning module and the second machining sequence is transmitted to a second planning module. The planning modules generate an action sequence as a planning result, which is considered by the second planning module during generation of the action sequence. Control signals are output by the action sequence generated by the second planning module.

A design and manufacturing system includes a multi-axis machine tool including a cutting head able to support a plurality of available tools and a part support, the cutting head and part support fully controllable in at least two axes, a design system operable using a computer to generate a 3-D model of a part to be manufactured, and a machine learning model operable using the computer to analyze the part to be manufactured to identify features and develop a manufacturing plan at least partially based on the multi-axis machine tool and the plurality of available tools, the manufacturing plan including a type of tool used for each feature, a feed-rate for each type of tool for each feature, and a speed of the tool for each type of tool for each feature.

A Web-based system and method creates one or more qualitatively distinct process plans for machining a part. The surfaces of the part are modeled and parameters for a plurality of CNC machining tools are obtained, including the orientations along which the tool cuts away raw material. A maximal set of translations for each tool is also obtained, where each translation includes a collision-free orientation of the tool and a maximal machinable volume of material removable from the part in that orientation. A search engine navigates through a hierarchically-structured search space that starts at an initial state and transitions to successive states based on actions that satisfy a cost constraint function. Each state and each action includes a tool, orientation of the tool, and a maximal machinable volume. The search ends when a goal condition is satisfied. The actions constitute the process plan.