According to an embodiment, a material recommendation apparatus includes an extractor, a creator, a matcher and a recommender. The extractor extracts information about a substance as a candidate for a material for an industrial product, a property of the substance, and a report time of the property from an electronic document. The creator creates, for each substance, time series data in which the property is associated with the report time. The matcher matches the time series data with a pattern. The recommender recommends, as the material, a substance corresponding to time series data that matches the pattern.

According to one embodiment, a manufacturing control system includes a reference data creating unit, first, second and third data storing units, first, second and third data extracting units. The reference data creating unit creates reference data including a reference time related to a product. The first data storing unit stores data related to parts acceptance inspection and related to assembly of the product. The second data storing unit stores data related to inspection in manufacturing. The third data storing unit stores data related to quality assurance inspection and of acceptance inspection at a customer site. The first data extracting unit extracts data related to latest parts acceptance inspection and related to latest assembly of the product. The second data extracting unit extracts data related to inspection in latest manufacturing. The third data extracting unit extracts data related to latest quality assurance inspection and of latest acceptance inspection.

A method to be performed in a production support system configured to process a raw material and to produce a product. And the method includes: acquiring a plurality of element values relating to production elements of the product; determining whether the element values are within allowable ranges in which a quality of the product meets a predetermined allowed quality; resetting the allowable ranges of one or a plurality of other element values to the allowable ranges in which the quality of the product meets the predetermined allowed quality, upon determining that at least one element value exceeds the allowable range; and outputting information about the reset allowable ranges.

This invention concerns apparatus for generating instructions for machines of a manufacturing chain used to manufacture a workpiece. The apparatus comprising a processor arranged to receive a model based definition (MBD) of a workpiece including geometric dimensions and tolerances; receive inputs setting an additive build design for building the workpiece based upon the geometric dimensions; generate additive instructions for an additive manufacturing machine of the manufacturing chain based upon the additive build design; determine a prospective intermediate workpiece product expected from an additive build in accordance with the additive build design; determine differences between the prospective intermediate workpiece product and the model based definition of the workpiece; and generate further instructions for at least one further machine of the manufacturing chain based upon the differences.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a process of manufacturing a product. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for manufacturing a product, based on a causal model that measures causal relationships between input settings and a measure of a quality of the product; ii) determining the measure of the quality of the product manufactured using the configuration of input settings; and iii) adjusting, based on the measure of the quality of the product manufactured using the configuration of input settings, the causal model.

A method for predicting an End of Line (EOL) quality of a product in an assembly plant is provided. The method includes performing a downstream test on a plurality of sub-components for determining a set of attributes. The method also includes receiving, by a control module, the set of attributes of the sub-components. The method further includes performing, by the control module, a root cause investigation on the set of attributes of the sub-components for identifying a subset of attributes from the set of attributes. The subset of attributes contributes to lowering the EOL quality of the assembled product. The method includes developing and validating, by the control module, dynamic prediction models based on the identified subset of attributes associated with the sub-components. The method also includes predicting, by the control module, the EOL quality of the assembled product based on the dynamically validated prediction model.