Constraints are received on initial components and intermediate components. Information is received on the products to be produced including a quantity of each of the products to be produced and a specification that specifies how the intermediate components are to be combined to form each of the products. An optimization is performed that includes the continuous conversion of initial components into the intermediate components as well as subsequent production of the products, subject to the constraints on each of the initial components, the constraints on each of the intermediate components, and the quantity of each of the products to be produced.

A system and method are provided for recording and then displaying comments containing recommended actions to take in response to abnormal conditions arising during process operations. The comments can be ranked by an operator based on their success in remedying abnormal conditions with the highest ranked actions displayed first.

Various embodiments enable batch inspection of a plurality of workpieces by and inspection instrument such as a coordinate measuring machine. Some embodiments present user interfaces, including graphical user interfaces, to enable an operator to configure a batch inspection system and a batch inspection job, and to monitor and control execution of a batch inspection job.

Various embodiments enable batch inspection of a plurality of workpieces by and inspection instrument such as a coordinate measuring machine. Some embodiments present user interfaces, including graphical user interfaces, to enable an operator to configure a batch inspection system and a batch inspection job, and to monitor and control execution of a batch inspection job.

A computer-implemented method to control technical equipment that performs a production batch-run of a production process, the technical equipment providing data in a form of time-series from a set of data sources, the data sources being related to the technical equipment, includes: accessing a reference time-series with data from a previously performed batch-run of the production process, the reference time-series being related to a parameter for the technical equipment; and while the technical equipment performs the production batch-run: receiving a production time-series with data, identifying a sub-series of the reference time-series, and comparing the received time-series and the sub-series of the reference time-series, to provide an indication of similarity or non-similarity, in case of similarity, controlling the technical equipment during a continuation of the production batch-run, by using the parameter as control parameter.

The present invention discloses a model-free online recursive optimization method for a batch process based on variable period decomposition. Variable operation data closely related to product quality is acquired, optimization action on each subset is integrated on the basis of time domain variable division on the process by utilizing a data driving method and a global optimization strategy is formed, based on which an online recursive error correction optimization strategy is implemented. According to the method, the online optimization strategy is formed completely based on the operation data of the batch process without needing prior knowledge or a model of a process mechanism. Meanwhile, the optimized operation locus line has better adaptability by using the online recursive correction strategy, and thus the anti-interference requirement of the actual industrial production is better met.

A system for production of liquid food (P) comprises a food processing arrangement (2) and a computer device (3), e.g. a PLC. The computer device (3) sequentially executes a control program (5A) to control the food processing arrangement (2) to perform processing steps for producing the liquid food (P) from one or more ingredients in accordance with a predefmed recipe. The program comprises command instructions that each allocates a respective processing step to a predefined control command among a predefmed set. To enable parallelism, despite the sequential execution by the computer device (3), the set of control commands comprises a start command which is associated, by the computer device (3), with an action of: starting the food processing step that is allocated to the start command and proceeding, without waiting for the food processing step to be completed, to a subsequent instruction in the list of instructions.

Methods and apparatus to define stages for multi-variate batch control analytics are disclosed. An example method includes determining, with the processor, a current stage in a current batch process based on a current value of a batch stage parameter. The current value of the batch stage parameter determined based on process control data associated with process parameters in the current batch process. The current stage determined independent of batch events defined by at least one of a start or an end of procedures, unit procedures, operations, or phases in a batch recipe. The example method further includes applying, with the processor, a model to the current batch process, the model corresponding to the current stage.

A method and system are provided for validating process data on a process recorder/controller. The method and system involves: configuring the validation criteria of the process variables, by defining value and time tolerances with respect to an ideal performance; receiving in real-time process data, including one or more process values, for a batch process at the recorder/controller responsible for recording the process data; performing a batch validation process on the recorder/controller, the batch validation process analyzing in real-time the one or more process values to validate the batch process based on at least a batch validation criteria; and transmitting from the recorder/controller validation information including a validation result for presentation on a device to a user, and/or recording at least on the recorder/controller the validation information including at least the validation result, wherein the validation result indicates whether the batch process is conformant or non-conformant.

Embodiments include a computer-implemented method (and system) for performing automated batch data alignment for modeling, monitoring, and control of an industrial batch process. The method (and system) loads, scales, and screens plant historian batch data for an industrial batch process. The method (and system) selects a reference batch as basis of the batch alignment, defines and adds or modifies one or more batch phases, and selects one or more batch variables based on one or more profiles and corresponding curvatures of the batch data. The method (and system) estimates one or more weightings, adjust one or more tuning parameters and uses a sliding time window combined with DTW, DTI and GSS algorithms, performs the batch alignment in offline mode or online mode.