A system and method for facilitating predictive maintenance of an equipment is disclosed. The system may include a data capturer, a plurality of edge computing nodes and a cloud computing device. Each edge computing node may include a first processor. The cloud computing device may include a second processor. The first processor may receive the raw input data from the data capturer and may process the raw input data to obtain a representative data. The representative data may include an insight pertaining to a deviation in the at least one variable and a corresponding remedial action to be taken to correct the deviation. The deviation may be related to a deterioration in the condition of the equipment. The respective edge computing node may facilitate a regulation of the deviation by performing an automated actuation based on the corresponding remedial action.

Methods, apparatus, and computer program products for analyzing, monitoring, and/or modeling the manufacture of a type of part by a manufacturing process. Non-destructive evaluation data and/or quality related data collected from manufactured parts of the type of part may be aligned to a simulated model associated with the type of part. Based on the aligned data, the manufacturing process may be monitored to determine whether the manufacturing process is operating properly; aspects of the manufacturing process may be spatially correlated to the aligned data; and/or the manufacturing process may be analyzed.

Systems and methods for production line optimization include: receiving, from each of a plurality of equipment along the production line, equipment data at each interval of a plurality of intervals, the equipment data including equipment speed data, equipment state data, and equipment fault data; analyzing the equipment data with one or more optimization rules to identify an optimization setting; and, outputting the optimization setting to a production line device for modification of the production line.

A system and method for facilitating predictive maintenance of an equipment is disclosed. The system may include a data capturer, a plurality of edge computing nodes and a cloud computing device. Each edge computing node may include a first processor. The cloud computing device may include a second processor. The first processor may receive the raw input data from the data capturer and may process the raw input data to obtain a representative data. The representative data may include an insight pertaining to a deviation in the at least one variable and a corresponding remedial action to be taken to correct the deviation. The deviation may be related to a deterioration in the condition of the equipment. The respective edge computing node may facilitate a regulation of the deviation by performing an automated actuation based on the corresponding remedial action.

Methods, apparatus, and computer program products for analyzing, monitoring, and/or modeling the manufacture of a type of part by a manufacturing process. Non-destructive evaluation data and/or quality related data collected from manufactured parts of the type of part may be aligned to a simulated model associated with the type of part. Based on the aligned data, the manufacturing process may be monitored to determine whether the manufacturing process is operating properly; aspects of the manufacturing process may be spatially correlated to the aligned data; and/or the manufacturing process may be analyzed.

An information processing apparatus executes a simulation of a state of a process which is being performed in a semiconductor manufacturing apparatus, by using a simulation model of the semiconductor manufacturing apparatus. The information processing apparatus includes: a physical sensor data acquisition unit that acquires physical sensor data measured in the semiconductor manufacturing apparatus that is performing the process according to process parameters; a simulation execution unit that executes the simulation by the simulation model according to the process parameters, thereby outputting virtual sensor data; a simulation result determination unit that performs a pre-detection of a part of the semiconductor manufacturing apparatus that needs to be replaced, based on a difference between the physical sensor data and the virtual sensor data; and a part order unit that orders the part of the semiconductor manufacturing apparatus based on a result of the pre-detection.

A method for monitoring machining processes in workpiece processing including steps of planning a processing process on the basis of a predetermined final shape of a workpiece to be achieved in the processing process and of quality features of the final shape of the workpiece and simulating the planned processing process in a computer-aided simulation. Target values of parameters of the simulated processing process occurring during the simulated processing process are detected and stored in the context of the computer-aided simulation. During the real processing process carried out according to the planned and simulated processing process, the parameters considered in the simulation are monitored and the actual values thereof are detected. By comparing actual values of parameters detected during the real processing process with the target values of these parameters detected during the simulation, the quality of the processing process and/or of the processed workpiece is assessed.

The present disclosure relates to manufacturing a pharmaceutical compound according to a manufacturing process. The manufacturing process comprises process parameters and rules that use the process parameters as literals. A control system determines a partition of the rules into subsets of rules, each being independent from the other subsets of rules in relation to the literals used in the rules. The controller creates simplified representations of the manufacturing process, which comprise the literals from a corresponding subset of rules and are created by eliminating literals used by other subsets of rules. The controller checks compliance of the manufacturing process based on the simplified representations of the manufacturing process by comparing values of the literals of a current process execution against literals in the simplified representations and adjusts the manufacturing process where the comparing identifies a difference. The controller repeats the steps of checking and adjusting until no differences are identified.

An Asset Performance Monitoring (APM) based-system includes an APM workflow engine receiving measured data values for dependent process variables from a process. A process and control simulator includes a dynamic operator training simulations (OTS) model. The APM workflow engine initializes the OTS model at a defined operating point at values for independent process variables from the measured data values to synchronize to the OTS model. The OTS model simulates at the defined operating point to generate model predicted values for key dependent process variables used to generate a trained data model that generates trained model predicted values for the key dependent process variables. The trained model predicted values are compared to the measured data values to generate symptom inputs processed by fault models to identify a suspected fault with the processing equipment/process. The APM workflow engine triggers an alert relating to inspection or maintenance action regarding the processing equipment/process.

This industrial system is characterized by being provided with: a storage unit that stores design data used when constructing an industrial line; a simulation execution unit that executes a simulation of movement of the industrial line, based on the design data; and a detection unit that compares a result of the simulation with the movement of the industrial line during operation and detects an abnormality in components of the industrial line. With such a configuration and movement, the present invention can be utilized for line operation support and high-resolution abnormality detection.