A method for verifying process orchestration logic for a modular plant includes generating a plant execution model representing the process orchestration logic; analyzing the plant execution model to identify one or more potential failure scenarios; and generating one or more test cases based on the one or more identified failure scenarios.

In one or more arrangements, a system and method for optimizing a set of production equipment (e.g., a production line) is presented. In some arrangements, a worker detection system is configured to track workers present at the production equipment and a control system is configured to adjust operation of the production equipment as a function of data received from the worker detection system. In some arrangements, the worker detection system is configured to detect workers using wearable devices configured to be worn during a work shift. In some arrangements, the control system is configured to receive data relating to workers present at the set of production equipment from the worker detection system and perform one or more control processes to optimize operation of one or more sets of production equipment and/or evaluate safety risks faced by the worker during the work shift based on data received from the wearable devices.

A method of determining an installation site of a robot manipulator at a workstation, the method including: recording a respective image of the robot manipulator and of the workstation of the robot manipulator, and of a workpiece to be machined at the workstation via a camera unit, wherein the respective image contains spatial information; transmitting the respective image to a computing unit; and determining the installation site of the robot manipulator by applying a non-linear optimization of a predefined cost function and/or of a neural network via the computing unit based on a predefined task for machining the workpiece and based on the spatial information determined by the computing unit from the respective image.

The present disclosure discloses an Industrial Internet of Things (IIoT) with a dual independent platform, which comprises a user platform, a service platform, a management platform, a sensor network platform and an object platform that interact in turn. The service platform adopts centralized layout, and the management platform and the sensor network platform adopt independent layout. The present disclosure also discloses a control method of the IIoT with the dual independent platform. The present disclosure builds the IIoT based on the five platform structure, in which the sensor network platform and the management platform are arranged independently, and each corresponding platform includes a plurality of independent sub-platforms, so that the independent sensor network platform and the management platform can be used for each production line device to form an independent data processing channel and transmission channel, and reduce the data processing capacity and transmission capacity of each platform.

A system for controlling a production plant includes a plant automation unit for monitoring and control of the production process within the production plant. A production planning system has information concerning the products to be produced. A model generator generates at least one prediction model for products produced in the production plant. The model generator takes into account the results of the monitoring of the production plant when generating the at least one prediction model. A production optimizer determines an optimized production process within the production plant on the basis of data from the plant automation unit, the production planning system, and the prediction model generated by the model generator. The production optimizer takes into account the production-related specifications of the individual plant parts. A production plant control unit generates target specifications for the plant automation unit on the basis of the optimized production process determined by the production optimizer.

A program generator extracts at least one machining process from a machining program, analyzes the machining process, generates information regarding the machining process, gives the machining process a score based on the information regarding the machining process, and determines a sequence of the machining process based on the given score. The information regarding the machining process includes a machining shape to be formed by the machining process. The machining process is given a score based on the machining shape.

A representation of an initial design domain, at least one subtractive tool assembly, machine degrees of freedom, and a termination criterion are used to iteratively generate intermediate part designs by redistributing the material within the design domain. A measure of inaccessibility of exteriors of the intermediate part designs by the at least one subtractive manufacturing tool assembly are generated. The measure of inaccessibility is used to inform generation of an intermediate part design at a next iteration. The iterative algorithm is terminated when the termination criterion is satisfied, the result of the iterative algorithm being a part design accessible for subtractive manufacturing.

A manufacturing adjustment system includes a decision part and a tolerance setting part. The decision part decides whether part dimensions calculated by a part dimension calculation part fall within a predetermined range of dimensions and a total machining time calculated by a total machining-time calculation part falls within a predetermined time. The tolerance setting part sets a workpiece tolerance for each machine based on the decision result of the decision part when the workpieces are produced by the machines.

A method, arrangement and computer program product for determining overall equipment effectiveness of a robot cell including at least one industrial robot involved in producing products. The arrangement includes an effectiveness determination device, which in turn includes an overall equipment effectiveness determining unit that obtains ideal robot operations data of the robot cell, obtains actual robot operations data of the robot cell, and determines the overall equipment effectiveness based on the ideal robot operations data and the actual robot operations data.

An information technology system for a distributed manufacturing network includes an additive manufacturing management platform configured to manage process and production workflows for a set of distributed manufacturing network entities through design, modeling, printing, and supply chain stages. The information technology system includes an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from the set of distributed manufacturing network entities of the distributed manufacturing network to optimize digital production processes and workflows. The information technology system includes a distributed ledger system integrated with a digital thread configured to provide unified views of workflow and transaction information to entities in the distributed manufacturing network.