Core Remanufacturing Prioritization Using A Priori Inspection Data
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Solution Overview
Problem
Remanufacturing processes face challenges due to the variable nature of input materials, particularly used products and components (cores) with different degrees of wear-and-tear, leading to uncertainties in core quality and condition, which affects inventory management, production planning, and resource allocation, resulting in inefficiencies and increased costs.
Innovation Solution
A method for core remanufacturing evaluation that involves acquiring and analyzing data to assess the internal condition of cores, identifying faults, determining necessary parts and processes, computing a utility measure for remanufacturing, and prioritizing cores based on this analysis to optimize the remanufacturing process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ERP solutions are used for remanufacturing, then general manufacturing processes can be managed, but they fail to distinguish the variable nature of core inputs and cannot provide accurate core condition assessment
Solution Approach 1:
The evaluation system segments core assessment into multiple independent modules: data acquisition module, data analysis module, fault identification module, and utility computation module. Each module handles a specific aspect of core evaluation, making the complex system manageable and scalable while improving assessment accuracy through specialized processing at each stage.
Solution Approach 2:
The system performs preliminary data collection and analysis on cores before they enter the remanufacturing process. By assessing core condition, identifying faults, and computing utility measures in advance, the system enables proactive decision-making about which cores to prioritize for remanufacturing, rather than reacting to problems during production.
2Measurement precision
If comprehensive core data analysis is performed to assess internal condition and identify faults, then core prioritization accuracy improves, but data processing time and computational resources increase
Solution Approach 1:
The system applies partial analysis by focusing computational resources on the most critical aspects of core assessment. Rather than analyzing every possible parameter equally, the system identifies and prioritizes the most influential factors affecting core utility and remanufacturing value, achieving high prioritization accuracy with reduced processing time.
Solution Approach 2:
The system transforms raw core data into meaningful parameters through standardized processing. By converting diverse data sources (operational data, sensor data, inspection data) into unified parameters and utility measures, the system enables efficient comparison and prioritization while reducing the complexity of raw data processing.
3Productivity
If variable core conditions are not assessed, then processing can proceed quickly without evaluation, but inventory management and production planning become inefficient due to uncertainties
Solution Approach 1:
The system implements feedback by using the results of core condition assessment and utility computation to guide subsequent remanufacturing decisions. The computed utility measures feed into prioritization algorithms that determine processing sequences, ensuring that cores are handled according to their actual condition and value, thereby improving both efficiency and reliability.
Solution Approach 2:
By performing comprehensive core evaluation before remanufacturing, the system establishes a reliable foundation for production planning. The preliminary assessment of core condition, fault identification, and utility computation ensure that subsequent processing steps are optimized for each specific core, improving overall productivity while maintaining consistent quality outcomes.
Data Source
AI summary
A method for core remanufacturing evaluation. The method may include acquiring available core data for a selected core from a plurality of cores; analyzing the available core data related to the selected core to assess an internal condition of the selected core and identify faults; identifying, based on the internal condition and the identified faults, part and processes needed to remanufacture the core; deriving metrics for part and processes needed to remanufacture the core; computing, from the derived metrics, a utility measure representing an estimate of potential value generated or potential impact generated if the core is remanufactured; determining a remanufacturing priority based on the computed utility measure; and performing remanufacturing of the selected core based on the determined remanufacturing priority.