Manufacturing cloud system with applied AI
A multi-tenant, cloud-based Software-as-a-Service (SaaS) manufacturing platform offers a variety of industrial applications to end customers—including but not limited to MES, ERP, quality management, supply chain management, and customer relationship management (CRM)—and implements associated architectural features that address a number of issues relating to data sharing, security, scalability, and other concerns.
1 . A system, comprising:
a memory that stores executable components; and
a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising:
internal services that implement a manufacturing cloud system, wherein the manufacturing cloud system is a multi-tenant Software-as-a-Service (SaaS) system that executes an industrial manufacturing execution system (MES) on a cloud platform, and the manufacturing cloud system collects and stores data from industrial systems owned by multiple customer entities;
a tagging component configured to tag items of the data with metadata to yield tagged data, wherein the metadata for a data item, of the items of the industrial data, collected from a first customer entity of the customer entities identifies a data type of the data item and indicates whether the data item is sharable with a second customer entity, of the customer entities, that is upstream or downstream in a supply chain relative to the first customer entity; and
an artificial intelligence (AI) component configured to infer a future status of a manufacturing process performed by an industrial system owned by the second customer entity based on a prediction of an event that occurs at the first customer entity, and to render the future status on a user interface delivered to a client device associated with the customer entity, wherein the artificial intelligence component predicts the event based on application of AI analysis to the tagged data.
2 . The system of claim 1 , wherein
the user interface visualizes information about the manufacturing process, and
the AI component is further configured to customize the user interface based on application of AI to a monitored usage of the user interface.
3 . The system of claim 2 , wherein the user interface is a virtual reality presentation of the manufacturing process.
4 . The system of claim 1 , wherein the AI component is configured to generate and deliver, based on application of AI to the tagged data, a proactive notification regarding the future status to the user interface.
5 . The system of claim 4 , wherein
the event is at least one of a change in an inventory level of a part or material produced by the first customer entity and required by the manufacturing process, an outage of a machine at the first customer entity that produces the part or material, or a transportation delay, and
the proactive notification comprises at least one of a notification to order the part or material required for the manufacturing process.
6 . The system of claim 4 , wherein the AI component is further configured to set, based on application of AI to the tagged data or monitored user interactions with the user interface, a frequency of delivery for the proactive notification or an event type that is to trigger the proactive notification, and to deliver the proactive notification according to the frequency or the event type.
7 . The system of claim 1 , wherein the status is at least one of a completion status of a task associated with the manufacturing process, a time of completion of the manufacturing process, a status of a machine of the industrial system, or a fulfillment status of a pending order for product or material.
8 . The system of claim 1 , wherein the AI component is configured to update an analytic model used to apply the AI to the tagged data based on user feedback identifying an incorrect inference of the status made by the AI component.
9 . The system of claim 1 , further comprising a simulation component that executes a simulation of the manufacturing process using a digital twin of the industrial system,
wherein the AI component is configured to infer the future status of the manufacturing process based on application of AI to the simulation.
10 . The system of claim 9 , wherein
the simulation component is configured to execute, using the digital twin, a simulation of a version of the manufacturing process that incorporates a defined modification to the industrial system, and
the AI component is configured to predict, based on application of AI to the simulation, an effect of the modification, and to render information about the effect on the user interface.
11 . The system of claim 10 , wherein the information about the effect comprises at least one of an expected product throughput, an expected machine downtime, an expected energy consumption, or an effect on another manufacturing process.
12 . The system of claim 1 , wherein
the tagging component is configured to determine whether the data item is sharable with the second customer entity based on a business relationship between the first customer entity and the second customer entity defined by tenant map data, and
the business relationship is at least one of a relationship between a supplier and a manufacturer, a relationship between a manufacturer and a shipper, or a relationship between a manufacturer and a retailer.
13 . A method, comprising:
implementing, by a system comprising a processor, a manufacturing cloud system, wherein the manufacturing cloud system is a multi-tenant Software-as-a-Service (SaaS) system that executes an industrial manufacturing execution system (MES) on a cloud platform, and the manufacturing cloud system collects and stores data from industrial systems owned by multiple customer entities;
tagging, by the system, items of the data with metadata to yield tagged data, wherein the metadata for a data item, of the items of the industrial data, collected from a first customer entity of the customer entities identifies a data type of the data item and indicates whether the data item is sharable with a second customer entity, of the customer entities, that is upstream or downstream in a supply chain relative to the first customer entity;
inferring, by the system, a future status of a manufacturing process executed by an industrial system owned by the second customer entity based on a prediction of an event that occurs at the first customer entity, wherein the inferring comprises inferring the future status based on application of AI to the tagged data; and
rendering, by the system, the future status on a user interface delivered to a client device associated with the customer entity.
14 . The method of claim 13 , further comprising:
visualizing, by the system, information about the manufacturing process on the user interface; and
customizing, by the system, the user interface based on application of AI to a monitored usage of the user interface.
15 . The method of claim 14 , wherein the user interface is a virtual reality presentation of the manufacturing process.
16 . The method of claim 13 , further comprising generating and delivering, by the system based on application of AI to the tagged data, a proactive notification regarding the future status of the manufacturing process to the user interface.
17 . The method of claim 16 , wherein the proactive notification comprises at least one of a notification to order a part or material required for the manufacturing process based on one or more of a usage rate of the part or material, a production schedule, or a predicted supply chain issue.
18 . The method of claim 16 , further comprising:
setting, by the system based on application of AI to the tagged data or monitored user interactions with the user interface, a frequency of delivery for the proactive notification or an event type that is to trigger the proactive notification, and
delivering, by the system, the proactive notification according to the frequency or the event type.
19 . A non-transitory computer-readable medium having stored thereon instructions that, in response to execution, cause system comprising a processor to perform operations, the operations comprising:
implementing a manufacturing cloud system, wherein the manufacturing cloud system is a multi-tenant Software-as-a-Service (SaaS) system that executes an industrial manufacturing execution system (MES) on a cloud platform, and the manufacturing cloud system collects and stores data from industrial systems owned by multiple customer entities;
tagging items of the data with metadata to yield tagged data, wherein the metadata for a data item, of the items of the industrial data, collected from a first customer entity of the customer entities identifies a data type of the data item and indicates whether the data item is sharable with a second customer entity, of the customer entities, that is upstream or downstream in a supply chain relative to the first customer entity;
inferring a future status of a manufacturing process executed by an industrial system owned by the second customer entity based on a prediction of an event that occurs at the first customer entity, wherein the inferring comprises inferring the future status based on application of AI to the tagged data; and
rendering the future status on a user interface delivered to a client device associated with the customer entity.
20 . The non-transitory computer-readable medium of claim 19 , further comprising:
visualizing information about the manufacturing process on the user interface; and
customizing the user interface based on application of AI to a monitored usage of the user interface.