Industrial HMI Layout Generation for Context-Sensitive Operator Queries
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Solution Overview
Problem
Current Human Machine Interfaces (HMI) in industrial production facilities are rigid and costly to engineer, failing to account for day-to-day contingencies and operator information needs, leading to inefficiencies in providing relevant information to plant operators.
Innovation Solution
A query-driven and context-sensitive HMI system that processes operator requests using a semantic network to collect and display relevant information, allowing operators to input queries in natural language or voice, and generating visual layouts based on current operational context, thereby automating interaction and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If a rigid HMI structure with upfront engineering is used, then information display consistency is maintained, but adaptability to day-to-day contingencies deteriorates
Solution Approach 1:
The HMI system transitions from a static, pre-configured structure to a dynamic system that adapts to operator needs in real-time. The system uses natural language processing to interpret operator queries and dynamically generates context-sensitive information displays, allowing the interface to evolve based on operational contingencies rather than being constrained by rigid upfront engineering decisions.
Solution Approach 2:
The system changes the parameters of information display by using semantic analysis to determine relevance, context, and operator intent. Instead of fixed display configurations, the HMI dynamically adjusts which parameters (information elements) are displayed based on the operator's natural language query and the current operational context, enabling flexibility while maintaining consistency in information accuracy.
2Loss of information
If extensive upfront engineering is performed to design information displays, then information completeness is improved, but development time and cost increase
Solution Approach 1:
The HMI system performs self-service by automatically analyzing operator natural language queries, retrieving relevant information from the control system databases, and generating appropriate displays without requiring extensive pre-programming. The system serves itself by adapting to new information needs through semantic analysis rather than requiring manual engineering for each scenario, thus maintaining information completeness while reducing development time.
Solution Approach 2:
The natural language processing core serves multiple functions: it interprets various query formats, determines information relevance, retrieves data from multiple system sources, and generates diverse display types. This multi-functional approach replaces the need for separate engineered solutions for each information display scenario, achieving comprehensive information coverage with reduced development effort.
3Stability of the object's composition
If standard operating procedures are used, then operational consistency is maintained, but responsiveness to abnormal situations deteriorates
Solution Approach 1:
The system incorporates feedback loops where operator natural language queries about abnormal situations trigger dynamic information retrieval and display. The HMI analyzes the semantic content of queries, determines relevance to current system state, and provides context-sensitive information that adapts to abnormal conditions while maintaining operational consistency through structured information presentation.
Data Source
AI summary
A method and system controlled by a human machine interface (HMI) connected to an industrial process control and automation system controlling an industrial process. The HMI collects information and data from a semantic network in response to a natural language request input into the HMI by an operator. The HMI generates a visual layout for the received information and data that is displayed to the operator using the visual layout.