Modular Plant Process Scheduling for Resource-Efficient Execution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modular industrial plants face inefficiencies in resource management due to the lack of systematic optimization of process module states and resource interactions, leading to suboptimal resource usage and increased costs.
Innovation Solution
A computer-implemented method that provides resource indicators for each state of process modules, determines candidate programs optimizing resource sequences, and calculates a figure of merit to identify the most efficient execution plan, considering continuous parameters and interdependencies between services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple configurations of modules are used to produce a particular desired product, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements a pool of process modules where each module can serve multiple functions across different product configurations. Modules are designed with universal capabilities to perform various services (heating, cooling, mixing, reacting) depending on the process requirements, allowing the same physical module to be reused in multiple plant configurations for different products
Solution Approach 2:
The system dynamically selects and configures module sequences based on the desired product and process requirements. The modular plant architecture allows flexible reconfiguration of module connections and operational states without physical reinstallation, enabling adaptability through dynamic programming and optimization algorithms that determine the optimal module sequence for each product
2Loss of substance
If process modules are reused across multiple different plants, then loss of substance is reduced, but device complexity increases
Solution Approach 1:
The system recovers and reuses process modules across multiple product plants instead of discarding them after single-use. Modules are maintained in a pool and reassigned to different product configurations, maximizing their utilization and reducing waste. The optimization system tracks module usage and coordinates their reuse across different product cycles
Solution Approach 2:
Process modules are designed with universal service capabilities that allow them to be deployed across multiple different product plants. Each module can perform various process functions (heating, cooling, mixing, chemical reaction) depending on the specific product requirements, enabling the same physical hardware to serve multiple products without modification
3Use of energy by moving object
If the sequence of states of services is modified to optimize resource consumption, then use of energy is improved, but productivity may worsen
Solution Approach 1:
The system optimizes energy consumption by dynamically adjusting operational parameters of process modules, including their sequence and state transitions. The optimization algorithms evaluate different parameter configurations (temperature profiles, flow rates, operational states) to find the optimal balance between energy efficiency and production time, allowing parameter tuning based on specific operational goals
4Use of energy by moving object
If systematic optimization of process module states is implemented, then use of energy is improved, but device complexity increases
Solution Approach 1:
The system implements optimization algorithms that evaluate resource consumption patterns and provide feedback for adjusting module sequences and operational states. The system monitors actual resource usage and compares it against optimized plans, continuously refining the optimization strategies to improve energy efficiency while managing system complexity through automated control
Data Source
AI summary
A computer-implemented method for optimizing execution of an industrial process includes providing a set of resource indicators, each being indicative of an amount of a resource that is required and/or produced by virtue of a particular service being in a particular state; determining a set of candidate programs for execution of the process, each candidate program having a sequence of states of services of process modules such that the sequence accomplishes the industrial process, and the resource requirements of all services in the sequence are fulfilled; determining a set of overall resource requirements for executing the industrial process according to the candidate program; determining a figure of merit for the candidate program; and selecting a candidate program with the best figure of merit as the optimal program for executing the given industrial process.