The invention relates to a system (1) for controlling a production plant (3) consisting of a plurality of plant parts (2), in particular a metallurgical production plant for producing industrial goods such as metal semi-finished products and/or metal end products, wherein each plant part (2) has an input quality window (4), an output quality window (5) and a process window (6), wherein the input quality window (4) of a plant part (2) defines the quality characteristics of the input product that are required by the plant part (2) and the output quality window (5) of a plant part (2) defines the quality characteristics of the output product that are allowed by the plant part (2) after processing the input product, wherein, in a production plant (3) consisting of the plurality of plant parts (2), the output quality window (5) of an upstream plant part (2) corresponds to the input quality window (4) of the downstream plant part (2), wherein the process window (6) defines the setting values (7) that can be implemented by the respective plant part (2) for a plant automation unit of the plant part (2), wherein each plant part (2) detects the current state by means of sensors (8) and adapts the process window (6) of the plant part (2) to the detected current state, and wherein the system (1) for controlling the production plant (3) consisting of the plurality of plant parts (2) determines setting values (7) for the respective plant automation unit for each plant part (2), the setting values being within the process windows (6) and that the product produced in the production plant (3) meets the quality characteristics required by the input quality windows (4) and output quality windows (5) of the plurality of plant parts (2).

The invention further relates to a corresponding method and computer program.

Aspects of the disclosed technology provide a computational model that utilizes machine learning for detecting errors during a manual assembly process and determining a sequence of steps to complete the manual assembly process in order to mitigate the detected errors. In some implementations, the disclosed technology evaluates a target object at a step of an assembly process where an error is detected to a nominal object to obtain a comparison. Based on this comparison, a sequence of steps for completion of the assembly process of the target object is obtained. The assembly instructions for creating the target object are adjusted based on this sequence of steps.

A method for checking the quality of a workpiece, a surface section of the workpiece is finished with a manufacturing device. A reference signal representing a time dependent difference between an ideal tool position and a real tool position of a tool of the manufacturing device in a reference phase is determined when finishing the workpiece. A test signal representing a time dependent difference between an ideal tool position and a real tool position of a tool of the manufacturing device in an operation phase is determined when finishing the workpiece. A mean value and a standard deviation value from the reference signal is determined. Data points of the test signal are determined, where the test signal deviates from the mean value more than a defined multiple of the standard deviation value. The surface quality of the workpiece is estimated by using the determined data points.

A method, apparatus, and system for managing nonconformances in laminates. A nonconformance management system comprises a sensor system and an analyzer in a computer system. The sensor that records layup information about the layup of layers on a workpiece platform and records inspection information about the laminate located on an inspection platform, wherein the laminate is formed from curing the workpiece. The analyzer in the computer system identifies a laminate nonconformance in the laminate using the inspection information, generates nonconformance information about the laminate nonconformance, and displays the nonconformance information about the laminate nonconformance on the laminate using a display system for an augmented reality display.

Provided are a system, method, and computer program product for optimizing a manufacturing process. The method includes generating a time-sequenced data structure associated with a manufacturing process and transforming the time-sequenced data structure to a positionally-dimensioned data structure by identifying a zone for each parameter of a plurality of parameters, determining a time delay factor for each zone, and generating the positionally-dimensioned data structure using a data matrix transformation based on the time-sequenced data structure, each zone, and each time delay factor. The method also includes identifying a set of empty entries in the time-sequenced data structure or the positionally-dimensioned data structure and imputing data. The method further includes determining a new value for a process parameter value based on the positionally-dimensioned data structure and at least one algorithm and optimizing the manufacturing process based on the new value.

A production process execution system has implementation modules which provide instructions for implementing the production process, recording modules which record the implemented steps of the production process, a control layer which monitors and controls the implementation modules and the recording modules, a cognition layer which monitors the production process, calculates process quality and provides feedback to a user through the implementation modules as to the correctness of the implemented steps. The system is enhanced by improvements in video recording, model training and digital recording of system operation and parameters. These features facilitate the creation of a closed system which provides user monitoring and system generated feedback.

Aspects of the disclosed technology provide a computational model that utilizes machine learning for detecting errors during a manual assembly process and determining a sequence of steps to complete the manual assembly process in order to mitigate the detected errors. In some implementations, the disclosed technology evaluates a target object at a step of an assembly process where an error is detected to a nominal object to obtain a comparison. Based on this comparison, a sequence of steps for completion of the assembly process of the target object is obtained. The assembly instructions for creating the target object are adjusted based on this sequence of steps.

An information management method includes acquiring a component serial number identifying an individual of a target component used in each process and a unit serial number (or a product serial number) identifying an individual of an intermediate product (or a product) manufactured by the process according to work order of the process. The information management method includes registering the component serial number in a hierarchy of the target component in the acquired order in a BOM database, and registering the unit serial number (or the product serial number) in a hierarchy of the process in the acquired order in a BOP database.

A method for checking the quality of a workpiece, a surface section of the workpiece is finished with a manufacturing device. A reference signal representing a time dependent difference between an ideal tool position and a real tool position of a tool of the manufacturing device in a reference phase is determined when finishing the workpiece. A test signal representing a time dependent difference between an ideal tool position and a real tool position of a tool of the manufacturing device in an operation phase is determined when finishing the workpiece. A mean value and a standard deviation value from the reference signal is determined. Data points of the test signal are determined, where the test signal deviates from the mean value more than a defined multiple of the standard deviation value. The surface quality of the workpiece is estimated by using the determined data points.

In order to provide a checking facility for checking workpieces and also a treatment facility for treating workpieces, which enable efficient and reliable quality optimisation, it is proposed that workpiece parameters are detected, for example by means of an automatic checking station, and a workpiece-specific data set is created on this basis and/or from facility parameters.