Robotic capability model for artificial intelligence assisted manufacturing supply chain planning

A knowledge representation and reasoning system for configuring manufacturing supply chain operation for the production of bespoke products, comprising:

• a) at least one computer processor for processing data;
• b) at least one input device;
• c) at least one output device;
• d) a computer readable storage device;
• e) a first predicate calculus ontology which is configured to:
• i) define a plurality of manufacturing domain ontology concepts,
• ii) define a product in terms of specifications which are expressed in terms of said manufacturing domain ontology concepts;
• f) a second predicate calculus ontology which is configured to define the capabilities of a plurality of manufacturing facilities;
• g) a knowledge representation and reasoning system which is operatively configured for automated reasoning by means of predicate calculus logic wherein the elements of logic are first class citizens of predicate calculus logic and which is operatively configured to integrate computation selected from the group consisting of object oriented computation and relational computation and functional computation with said system of predicate calculus logic and which is executed on said computer processor which is configured to:
• i) access said computer readable storage device for reading said first predicate calculus ontology and said second predicate calculus ontology,
• ii) receive a request describing the specification of said product in terms of said first predicate calculus ontology via said input device,
• iii) deduce through a system of predicate calculus and automated reasoning using said request in (ii) and using said second predicate calculus ontology a manufacturing plan detailing how to produce the product described in (ii) using a list of manufacturing facilities, and
• iv) transmit said manufacturing plan via said output device;
• and
• whereby the creation of manufacturing supply chain functionality is enabled that transforms bespoke product specifications into manufacturing production plans thereby enabling real-time and ad-hoc supply chain planning, and the efficacy of the combination of the computer processor, the input device, the output device and the computer readable storage device in curating manufacturing production plans is improved through the integration of aspects of computation with the knowledge representation and reasoning system.

A knowledge representation and reasoning system coupled with an embedded neural network for configuring manufacturing supply chain operation for the production of bespoke products, comprising:

• a) at least one computer processor for processing data;
• b) at least one input device;
• c) at least one output device;
• d) a computer readable storage device;
• e) a first predicate calculus ontology which is configured to:
• i) define a plurality of manufacturing domain ontology concepts,
• ii) define a product in terms of specifications which are expressed in terms of said manufacturing domain ontology concepts;
• f) a second predicate calculus ontology which is configured to define the capabilities of a plurality of manufacturing facilities;
• g) a knowledge representation and reasoning system coupled with an embedded neural network which is operatively configured for automated reasoning by means of predicate calculus logic wherein the elements of logic are first class citizens of predicate calculus and which is operatively configured to integrate computation selected from the group consisting of object oriented computation and relational computation and functional computation with said system of predicate calculus logic and which is configured to evaluate predicate satisfaction according to a mode of satisfaction selected from the group consisting of partial satisfaction of logical predicates and full satisfaction of logical predicates and which is executed on said computer processor which is configured to:
• i) access said computer readable storage device for reading said first predicate calculus ontology and said second predicate calculus ontology,
• ii) receive a request describing the specification of said product in terms of said first predicate calculus ontology via said input device,
• iii) apply structural regression over an ontology selected from the group consisting of said first predicate calculus ontology and said second predicate calculus ontology using said embedded neural network and partial satisfaction of logical predicates to compute a predicted inference,
• iv) deduce through a system of predicate calculus and automated reasoning using said request in (ii) and using said second predicate calculus ontology and using said predicted inference in (iii) a manufacturing plan detailing how to produce the product described in (ii) using a list of manufacturing facilities, and iv) transmit said manufacturing plan via said output device;
• and
• whereby the creation of manufacturing supply chain functionality is enabled that transforms bespoke product specifications into manufacturing production plans thereby enabling real-time and ad-hoc supply chain planning, and the efficacy of the combination of the computer processor, the input device, the output device and the computer readable storage device in curating manufacturing production plans is improved through the integration of aspects of computation with the knowledge representation and reasoning system, and the processes of curating manufacturing production plans for supply chains is improved by allowing said predicate calculus knowledge representation and reasoning system to perform weighted inference according to statistical relevance and by allowing said predicate calculus knowledge representation and reasoning system to effect imputation of incomplete input data to arrive at actionable supply chain plans and by allowing said predicate calculus knowledge representation and reasoning system to logically reason with imprecise input data.