Manufacturing Facility Management Optimization via Simulation
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Solution Overview
Problem
Current plant management systems fail to effectively compare maintenance details with overall management influence, leading to inefficient resource allocation and lack of consideration for maintenance costs and abnormalities in plant operations.
Innovation Solution
A manufacturing facility management optimization device that includes a storage unit for product and raw material prices, a simulation unit for generating operating states, a diagnosis unit for detecting abnormalities, a maintenance proposal unit for specifying corrective actions, and an economic-efficiency evaluation unit for optimizing management indices based on output and consumption data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional plant control technologies using IoT are used to detect abnormalities, then abnormality detection capability is improved, but the ability to evaluate maintenance economic efficiency and optimize resource allocation deteriorates
Solution Approach 1:
The patent merges abnormality detection functionality with economic efficiency evaluation by integrating a diagnosis unit that detects abnormalities with an economic-efficiency evaluation unit that calculates management indices. This combination allows the system to not only detect plant abnormalities but also evaluate the economic impact of maintenance actions, thereby preventing loss of information regarding maintenance efficiency.
Solution Approach 2:
The patent introduces simulation units as intermediaries that generate virtual operating states based on maintenance proposals. These simulation units act as mediators between abnormality detection and economic evaluation, allowing the system to predict outcomes of maintenance actions without disrupting actual plant operations, thus preserving both detection accuracy and evaluation capability.
2Measurement precision
If detailed maintenance monitoring is implemented to track maintenance actions, then maintenance tracking capability is improved, but the ability to analyze overall management impact and optimize resource allocation deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where the economic-efficiency evaluation unit calculates management indices based on simulated operating states and feeds this information back to the maintenance proposal unit. This feedback loop enables the system to continuously optimize maintenance strategies by learning from simulated outcomes, thereby improving both tracking precision and resource allocation efficiency simultaneously.
Solution Approach 2:
The patent performs preliminary simulation of maintenance actions before actual implementation. The simulation unit generates predicted operating states and the economic-efficiency evaluation unit calculates expected management indices in advance, allowing decision-makers to evaluate resource allocation efficiency before committing to maintenance actions, thus avoiding the trade-off between detailed tracking and overall optimization.
3Adaptability or versatility
If multiple maintenance candidates are generated to provide options, then maintenance flexibility is improved, but the complexity of selecting the optimal maintenance strategy increases
Solution Approach 1:
The patent changes the parameter representation of maintenance strategies by evaluating multiple candidates through simulation and expressing their outcomes as standardized management indices. This parameter transformation allows diverse maintenance options to be compared on a common economic efficiency scale, reducing decision-making complexity while maintaining flexibility in selecting optimal strategies.
Data Source
AI summary
This manufacturing facility management optimization device: on the basis of an operation condition of a manufacturing facility, creates, in a simulated manner in time series, an operation state which includes a measurement value, product yield, and quantities of raw materials consumed, of the manufacturing facility; detects an anomaly from the created operation state; identifies maintenance which corresponds to the detected anomaly, corrects the operation condition on the basis of the identified maintenance, and creates a plurality of post-correction operation condition candidates; creates, in a simulated manner in time series, a plurality of post-correction operation state candidates on the basis of the plurality of post-correction operation condition candidates; on the basis of the product yield and the quantities of raw materials consumed in the plurality of pre- and post-correction operation state candidates, and a unit price, creates a management index for the operation state and each of the plurality of post-correction operation state candidates; and, from among the plurality of post-correction operation condition candidates, identifies the candidate which optimizes the management index.