Supervisor Engine Task Assignment for Process Plant Downtime
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Solution Overview
Problem
Current process control systems in plants face limitations such as data archiving issues due to memory constraints, inefficient data communication, and siloed data structures, leading to cumbersome troubleshooting and predictive modeling processes with potential inaccuracies.
Innovation Solution
Implementing a computer-implemented, automated method using a supervisor module that assigns tasks to personnel based on data from an expert system, coupled with big data historians and context-aware mobile user-interface devices for improved workflow management and data access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is archived in centralized databases with limited memory, then data storage is achieved, but data access efficiency deteriorates and troubleshooting becomes cumbersome
Solution Approach 1:
The patent segments the centralized database into distributed data stores across multiple portable computing devices. Each device maintains local data storage and processing capabilities, eliminating the single-point bottleneck of centralized databases. This segmentation allows operators to access relevant data locally without querying a central repository, significantly reducing troubleshooting time while maintaining adequate storage capacity across the distributed system.
Solution Approach 2:
The patent transitions from a two-dimensional centralized storage model to a multi-dimensional distributed architecture where data exists across spatial (multiple devices), temporal (historical and real-time), and hierarchical (local and cloud) dimensions. This dimensional expansion enables simultaneous data access from multiple points, improving both storage scalability and access efficiency.
2Reliability
If traditional wired communication paths are used, then system reliability is improved, but system complexity and installation difficulty increase
Solution Approach 1:
The patent replaces the mechanical wired communication infrastructure with wireless communication technology. Portable computing devices communicate with process control systems, administrative computing devices, and each other via wireless networks, eliminating the need for physical cable installations while maintaining communication reliability through modern wireless protocols and redundancy mechanisms.
Solution Approach 2:
The wireless communication infrastructure serves multiple functions simultaneously: data transmission between portable devices and control systems, inter-device communication for collaboration, cloud connectivity for data synchronization, and mobile access for operators. This multi-functionality reduces overall system complexity compared to dedicated wired connections for each communication need.
3Reliability
If centralized administrative computing devices are placed in control rooms, then data security is improved, but operator mobility and response time deteriorate
Solution Approach 1:
The patent segments the centralized administrative computing functionality into distributed portable computing devices that operators can carry throughout the facility. Each portable device maintains secure access controls and encryption, distributing security enforcement across multiple devices rather than relying solely on physical control room security. This enables operators to securely access and interact with process data at the point of need.
Solution Approach 2:
The portable computing devices serve as secure intermediaries between operators and the process control systems. They implement authentication, authorization, and encrypted communication protocols, acting as mobile security gateways that maintain data protection while enabling field access. This intermediary layer preserves security requirements while eliminating the need for operators to return to centralized control rooms.
4Measurement precision
If manual task assignment is used, then personnel expertise matching is achieved, but task assignment efficiency and productivity deteriorate
Solution Approach 1:
The supervisor module continuously monitors operator locations, current task status, skill profiles, and work item requirements, using this feedback to dynamically optimize task assignments. The system learns from assignment outcomes and adjusts future assignments based on performance data, maintaining high skill-matching accuracy while operating at automated speeds.
Solution Approach 2:
The patent transforms the task assignment process from a static manual procedure to a dynamic automated system that continuously adjusts assignment parameters based on changing conditions. The supervisor module evaluates multiple parameters simultaneously (operator skills, location, availability, task priority, historical performance) and optimizes assignments in real-time, achieving both precision and speed that manual processes cannot match.
5Stability of the object's composition
If siloed data structures are maintained, then data integrity within each system is preserved, but predictive modeling accuracy and cross-system analysis deteriorate
Solution Approach 1:
The patent merges previously siloed data structures into an integrated data architecture that combines process control data, maintenance management data, operator profile data, and environmental data into a unified framework. This integration maintains the integrity of source systems through standardized data interfaces while enabling cross-system analytics and predictive modeling that leverage correlations across all data types.
Solution Approach 2:
The unified data structure functions as a composite information architecture, combining heterogeneous data types from multiple sources while preserving the unique properties of each data category. Like composite materials that combine different substances to achieve superior properties, this composite data structure enables predictive analytics that leverage the strengths of each data source while maintaining the stability and integrity of individual data systems.
Data Source
AI summary
A supervisor engine cooperates with an expert system in a process control environment to automatically generate, assign, track, and manage work items. The supervisor engine creates work items according to data received from the expert system, selects available personnel to execute work items, sends work items to the selected personnel, schedules the execution of the work items, and creates and stores permissions that allow the assigned personnel to complete a target function of the work item at an assigned time. The supervisor engine determines required skill sets, roles, certifications, and/or credentials associated with a work item, and selects personnel to perform the work item according to a personnel profile specifying a skill set, a role, certifications, and/or credentials associated with the personnel. Alternatively or additionally, the supervisor engine assigns a work item according to the presence of personnel at or near the target equipment.