Automated design of process automation facilities

Patent metadata

Field	Value
Publication number	US-12524581-B2
Application number	US-202117510039-A
Country	US
Kind code	B2
Filing date	Oct 25, 2021
Priority date	Oct 25, 2021
Publication date	Jan 13, 2026
Grant date	Jan 13, 2026

Abstract

Implementations herein leverage knowledge about historical process automation facilities to automate designing a new process automation facility. A first level design input may be processed to generate a first embedding that encodes design aspect(s) of the requested process automation facility with a degree of detail commensurate with a first level of a hierarchy reflected by design documents typically used to design a process automation facility. The first embedding may be used to find first level reference embeddings that encode design aspects of reference process automation facilities. Second level reference embedding(s) may be identified based on mapping(s) from the selected first level reference embedding(s). Each second level reference embedding may encode design aspect(s) of a respective reference process automation facility with a degree of detail that is commensurate with a second level of the design document hierarchy. Based on the second level reference embedding(s), template design document(s) may be provided.

First claim

What is claimed is:

1 . A method for designing at least part of a requested process automation facility, the method implemented using one or more processors and comprising:
processing a first level design input about the requested process automation facility to generate a first embedding, wherein the first embedding encodes design aspects of the requested process automation facility at a first level of abstraction; comparing the first embedding to a plurality of first level reference embeddings to select one or more first level reference embeddings that satisfy a first criterion, wherein the plurality of first level reference embeddings encode design aspects of a respective plurality of reference process automation facilities at the first level of abstraction; identifying one or more second level reference embeddings based on one or more mappings from the selected one or more first level reference embeddings, wherein each of the one or more second level reference embeddings encodes design aspects of a respective one of the plurality of reference process automation facilities at a second level of abstraction that is less abstract than the first level of abstraction; and based on the identified one or more second level reference embeddings, providing one or more template design documents for the requested process automation facility.

2 . The method of claim 1 , wherein the first level design input about the request process automation facility comprises a process flow diagram, and the one or more template design documents for the requested process automation facility include a template piping and instrumentation diagram (P&ID) of at least a portion of the requested process automation facility.

3 . The method of claim 1 , wherein the first level design input about the request process automation facility comprises a natural language input, and the one or more template design documents for the requested process automation facility include a template process flow diagram (PFD) or template piping and instrumentation diagram (P&ID) of at least a portion of the requested process automation facility.

4 . The method of claim 1 , wherein the first level design input about the request process automation facility comprises information about a central control room of the requested process automation facility, and the one or more template design documents for the requested process automation facility include a template design of a field equipment room (FER) of the requested process automation facility.

5 . The method of claim 1 , wherein processing the first level design input to generate the first embedding comprises:
generating a graph based on the first level design input; and processing the graph based on one or more machine learning models to generate the first embedding.

6 . The method of claim 5 , wherein one or more of the machine learning models comprises a graph neural network (GNN).

7 . The method of claim 5 , wherein the graph includes a plurality of nodes representing a plurality of processes to be implemented in the requested process automation facility, and a plurality of edges that define relationships between the plurality of processes.

8 . The method of claim 5 , wherein the graph includes a plurality of nodes representing a plurality of process automation nodes to be implemented in the requested process automation facility, and a plurality of edges that represent network communication channels between the plurality of process automation nodes.

9 . The method of claim 5 , wherein the graph includes one or more nodes representing one or more modular automated process assemblies to be implemented in the requested process automation facility, and a plurality of edges that define relationships between the one or more modular process automation assemblies and other elements of the requested process automation facility.

10 . The method of claim 1 , wherein the one or more second level reference embeddings comprise a plurality of second level reference embeddings generated from a plurality of reference design documents associated with the reference process automation facilities, and one or more of the template design documents is generated based on intransient elements shared amongst the plurality of reference design documents.

11 . The method of claim 1 , wherein the first design input comprises input/output (I/O) information for a process unit of the process automation facility, and the processing includes calculating a number of distributed control nodes (DCNs) for the process unit.

12 . A system for designing at least part of a requested process automation facility, the system including or more processors to:
process a first level design input about the requested process automation facility to generate a first embedding, wherein the first embedding encodes design aspects of the requested process automation facility at a first level of abstraction; compare the first embedding to a plurality of first level reference embeddings to select one or more first level reference embeddings that satisfy a first criterion, wherein the plurality of first level reference embeddings encode design aspects of a respective plurality of reference process automation facilities at the first level of abstraction; identify one or more second level reference embeddings based on one or more mappings from the selected one or more first level reference embeddings, wherein each of the one or more second level reference embeddings encodes design aspects of a respective one of the plurality of reference process automation facilities at a second level of abstraction that is less abstract than the first level of abstraction; and based on the identified one or more second level reference embeddings, provide one or more template design documents for the requested process automation facility.

13 . The system of claim 12 , wherein the first level design input about the request process automation facility comprises a process flow diagram, and the one or more template design documents for the requested process automation facility include a template piping and instrumentation diagram (P&ID) of at least a portion of the requested process automation facility.

14 . The system of claim 12 , wherein the first level design input about the request process automation facility comprises a natural language input, and the one or more template design documents for the requested process automation facility include a template process flow diagram (PFD) or template piping and instrumentation diagram (P&ID) of at least a portion of the requested process automation facility.

15 . The system of claim 12 , wherein the first level design input about the request process automation facility comprises information about a central control room of the requested process automation facility, and the one or more template design documents for the requested process automation facility include a template design of a field equipment room (FER) of the requested process automation facility.

16 . The system of claim 12 , wherein processing the first level design input to generate the first embedding comprises:
generating a graph based on the first level design input; and processing the graph based on one or more machine learning models to generate the first embedding.

17 . The system of claim 16 , wherein one or more of the machine learning models comprises a graph neural network (GNN).

18 . The system of claim 16 , wherein the graph includes a plurality of nodes representing a plurality of processe

Assignees

• Yokogawa Electric Corp

Inventors

• Emerson David
• Wake Ichiro
• Clay Patrick
• Nguyen Vien
• Sawahara Hidenori
• Hammer Mark

Classifications

• G06N3/02

  Neural networks · CPC title

• G05B19/418

  Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] · CPC title

• G06F2111/04

  Constraint-based CAD · CPC title

• G06F30/27

  using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model · CPC title

• G06F30/13 Primary

  Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads · CPC title