KR-102961598-B1 - METHOD AND SYSTEM FOR AIRCRAFT ROTABLE PARTS CYCLE MANAGEMENT

Abstract

A circulation management system for aircraft repair parts may include a memory and a processor for storing instructions. When executed by the processor, the instructions can control the process of the system receiving an aircraft part request from an airline, checking the inventory of aircraft parts classified as NO-GO or IF-GO according to the MEL (Minimum Equipment List) criteria in the home base stock, providing parts from the home base stock to the airline while simultaneously requesting automatic replenishment from the parts supplier's inventory, sending the replaced parts to a repair plant to circulate them back to the inventory after repair, and calculating and charging a pooling program fee per aircraft.

Inventors

• 이상현

Assignees

• 굿맨에어솔루션즈 주식회사

Dates

Publication Date

20260508

Application Date

20250529

Claims (5)

1. In a circulation management system for aircraft repair parts, Memory for storing instructions; and Includes a processor, When the above instructions are executed by the processor, the system Receive a request for aircraft parts from an airline, Check the inventory of aircraft parts classified as either NO-GO or IF-GO according to the MEL (Minimum Equipment List) criteria in the home base stock, and While providing parts from the above home base stock to the airline, request automatic replenishment from the parts supplier's inventory, It manages the process of sending replaced parts to a repair factory to be returned to inventory after repair, and It controls the calculation and billing of pooling program usage fees per aircraft, and Parses the part number (P/N) included in the part request received from the airline and matches it with the part classification table stored in the database, and It automatically determines the corresponding grade among the NO-GO, IF-GO, and GO categories defined in the above parts classification table, and in the case of NO-GO parts, generates an emergency alert message indicating that the aircraft is inoperable and transmits it to the airline's flight operations management system, searches for available stock within a specified period including 24 hours in the home base stock inventory management system, and sets a priority allocation flag. In the case of IF-GO parts, the Ministry of Land, Infrastructure and Transport's regulation database is queried to extract the conditional operational period of the part, the remaining time from the current point in time until the said conditional operational period is calculated to automatically generate a replacement schedule and transmit it to the airline's maintenance schedule system, and For GO parts, maintenance schedule data received from airlines is analyzed to assign delivery priority values and reflect them in the logistics management system; to ensure real-time inventory synchronization between the home base stock near Incheon Airport and the backup stock at the parts supplier, API communication is established between the inventory management systems installed at each stock location; when a parts dispatch event occurs from the home base stock, a replenishment request message in JSON format containing dispatch information is transmitted to the parts supplier system, and the replenishment completion status is periodically checked within a specified period including 48 hours; if not completed, an escalation process is executed. Scanning the RFID tag or barcode attached to the part removed and replaced by the airline to extract the unique part identifier, querying the manufacturing date, installation history, and repair history in the part history database using the said identifier as a key, filtering the repairable factories for the part from the list of FAA or EASA certified repair factories, and calculating the transportation distance and estimated repair time to each factory to select the optimal route, Service tag information of repaired parts is received and parsed in XML format, and a transaction including the part identifier, repair date, repair details, and certification number is generated and transmitted to a blockchain network to be stored as an immutable record, and It converts accumulated parts usage history data by aircraft type and airline into feature vectors and inputs them into a time-series forecasting model to predict the demand for each part at future points in time, and dynamically adjusts safety stock levels based on the forecast results, To calculate the monthly pooling program fee per aircraft, a pricing function is defined using the usage frequency, unit price, and average repair cost of each part type as variables, and the weights of each variable are dynamically adjusted and applied according to the contract conditions of each airline, and A system that controls the execution of an optimization algorithm that simulates the total cost of ownership over multiple years and the estimated cost of direct purchase for multiple contracted part items to generate a comparative analysis report and recommends part combinations that maximize cost reduction effects.
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3. In Article 1, When the above instructions are executed by the processor, the system Flight cycle counter values, accumulated engine operating time values, takeoff and landing event logs, GPS coordinate-based flight route data, and atmospheric temperature and humidity data by altitude extracted from the aircraft's FDR (Flight Data Recorder) are converted into a standardized format and stored as a multidimensional tensor structure, and It forms an integrated dataset by combining maintenance history data, including parts replacement dates, fault codes, and repair details received from the maintenance management system, and The above integrated dataset is input into an ensemble deep learning model including an LSTM (Long Short-Term Memory) network and a GRU (Gated Recurrent Unit) to output the remaining life of each component as a probability distribution with a mean and standard deviation, and confidence intervals are calculated through Monte Carlo simulation, and For parts whose calculated remaining life is predicted to be below a user-set threshold, generate a part replacement recommendation alert 30 days prior to the point in time when the failure probability exceeds the threshold level by calculating backward, and calculate the conditional probability of the part being converted to a NO-GO grade using Bayesian inference and display it as a percentage, It utilizes a web crawler to collect information on inventory quantities, unit prices, and lead times by part from the online catalogs and inventory management systems of aircraft parts suppliers worldwide, maps the collected data to the suppliers' geographical coordinates to display it in the form of a heatmap on a map-based visualization interface, and in the event of an emergency, receives the requested part and location as input to automatically search for and match suppliers capable of providing the shortest delivery time using Dijkstra's algorithm, It decomposes monthly and quarterly usage changes from past parts usage history into periodic and trend components through Fourier transform, analyzes the correlation with seasonal temperature, humidity, and precipitation data received from the Korea Meteorological Administration API using Pearson correlation coefficients to derive demand increase patterns by environmental factors, such as engine starting-related parts during the winter and summer seasons and electrical system-related parts during the rainy season, and generates an inventory reallocation command that dynamically adjusts the holding quantity of each part in the home base stock according to the predicted demand growth rate, It monitors the parts inventory status and utilization rates of airlines operating the same aircraft model in real time, searches for spare parts from other airlines within a radius when an AOG situation occurs at a specific airline requiring urgent parts, matches airlines with temporarily available parts, automatically calculates optimal rental conditions considering reliability scores based on past transaction history and transportation costs based on distance, specifies transaction conditions via a blockchain-based smart contract, obtains electronic signatures from both parties, and automatically executes the transaction. A system that estimates the difference between publicly disclosed MTBF values by manufacturer and failure time data collected in the actual operating environment using a Kalman filter, calculates an adjusted reliability score by training a multivariate regression model characterized by manufacturer, year of manufacture, manufacturing plant, operating environment temperature, and operating altitude, and controls the application of a price adjustment coefficient according to the grade and differentiates risk grades for each part when joining a pooling program based on the said reliability score.
4. In Article 1, When the above instructions are executed by the processor, the system Events throughout the entire lifecycle of aircraft parts, such as manufacturing, repair, transportation, installation, and removal, are stored as immutable records on a blockchain network, and for each event, a transaction is generated that includes a timestamp, location information, worker information, and a certificate hash value. When trading parts, a consortium blockchain is formed involving all stakeholders, including airlines, parts suppliers, repair shops, and logistics companies; after verifying the validity of the transaction through a consensus algorithm, smart contracts are automatically executed to simultaneously process payment settlement and the transfer of parts ownership. It collects temperature, humidity, vibration, and pressure data in real time from IoT sensors attached to aircraft parts, records the history of exposure to environments outside the normal range on a blockchain to detect potential quality degradation of parts in advance, and utilizes this as evidence in the event of a warranty claim. Upon the issuance of Airworthiness Directives by global aviation authorities, the serial numbers of the relevant parts are immediately looked up on the blockchain to automatically identify affected aircraft and inventory, generate a compliance schedule based on mandatory replacement deadlines, and notify relevant airlines. By tracking the origin and certification status of sub-components used during parts repair via blockchain, the mixing of uncertified parts is prevented at the source, and reliability scores for repair quality are accumulated and managed to be utilized as performance evaluation indicators for each repair shop. To prevent price collusion or unfair trade practices during parts transactions between airlines, transaction prices are encrypted and recorded on a blockchain, while a privacy protection mechanism is applied that allows decryption only upon request from regulatory authorities, and A system that predicts when a part reaches its expected lifespan, classifies recyclable materials of parts scheduled for disposal in advance, and controls disposal at the optimal price through a reverse auction system with a recycling company.
5. In Article 1, When the above instructions are executed by the processor, the system It receives a real-time data stream transmitted from an ACARS transceiver installed on the aircraft, parses system parameters including engine exhaust gas temperature (EGT), engine rotational speed (N1, N2), fuel flow rate, oil pressure, hydraulic system pressure, electrical system voltage and frequency, and cabin pressurization values, and calculates the deviation from the normal range by comparing in real-time with a threshold table defining the normal operating range for each parameter, and If the calculated deviation shows an increasing trend across multiple consecutive data points, the slope is calculated through linear regression analysis, and parameters whose slope exceeds a critical slope are flagged as an anomaly, and A list of candidate parts is generated by querying the system architecture database for part groups associated with flagged parameters, and the conditional probability that the failure of each candidate part will cause an anomaly in the observed parameter is calculated using the Bayesian network's confidence propagation algorithm and sorted in order of highest failure probability. Converts PDF Service Bulletin (SB) files and revised maintenance manuals downloaded from the aircraft manufacturer's technical documentation repository into text using Optical Character Recognition (OCR), extracts part numbers, maintenance work codes, and compliance deadlines using the Named Entity Recognition (MOR) function of a natural language processing engine, identifies new or changed requirements by comparing the extracted information with the existing maintenance requirements database, estimates the expected increase in demand for affected parts based on past similar case data, and generates inventory securing recommendations for the relevant airline. Data on parts replacement cycles for multiple aircraft operating on the same route is collected and grouped by route to calculate the average replacement cycle and standard deviation for each group; parts exhibiting a replacement cycle faster than the average on a specific route are identified; runway surface conditions, average temperature, humidity, salinity, and altitude are queried from the airport database for the relevant route to quantify the impact of each environmental factor on the reduction of part lifespan through multiple linear regression analysis; and route-specific adjustment coefficients are calculated to propose differentiated replacement cycles. Executes a workflow that collects worker IDs, work start times, work end times, and event logs generated during work from the maintenance work management system, calculates a fatigue index by determining cumulative and continuous work times per worker, defines high-risk work conditions through correlation analysis with past maintenance error data, and automatically activates a double inspection process when such conditions are met. It accesses the accident investigation report database of the International Aviation Safety Organization to extract the manufacturer, model number, manufacturing date, and design version of the accident-causing part, generates a list of risk parts by searching for parts with identical attributes among those registered in the company's system via SQL queries, calculates a risk score by analyzing the current operating status and maintenance history of each part, and automatically generates special inspection work orders for parts exceeding a threshold, A system that controls the generation of a decision support report recommending preemptive purchasing prior to the point where cost increases are expected, by receiving aviation fuel spot prices, futures prices, major currency exchange rates, and aviation industry-related geopolitical risk indices in real time from external economic indicator APIs, predicting future price volatility through a time series analysis model, simulating the impact on procurement costs by component.

Description

Method and System for Aircraft Rotable Parts Cycle Management The present invention relates to the aircraft maintenance, repair, and overhaul (MRO) industry, particularly to the supply chain management and logistics technology of aircraft parts. More specifically, this invention relates to a parts supply management method and system based on an 'Aircraft Parts Pooling Program,' which operates in real-time a cyclical management method in which, instead of the airline directly possessing expensive rotable parts that are essential for operational safety and efficiency, the airline immediately receives them when needed through a shared parts pool, and repairs used parts to replenish the pool. In addition, the present invention can be applied to technology fields that reduce the inventory burden on airlines, maximize parts availability, optimize parts repair and logistics processes to minimize aircraft downtime, and strengthen the competitiveness of the domestic aviation MRO industry. While the aviation industry contributes to the national economy through passenger and cargo transportation, the profitability of aircraft operations themselves is relatively low. Conversely, ancillary businesses such as aircraft maintenance, repair, and overhaul (MRO), in-flight catering, and circuit board operations generate high returns; in particular, the MRO business is a core sector directly linked to the safe operation of airlines. Accordingly, many overseas airlines are spinning off their MRO divisions to enhance expertise and maximize profitability. The South Korean government also recognizes the importance of the MRO industry and is pursuing various support policies to redirect maintenance demand, which amounts to 1.2 trillion won annually, back to the domestic market. However, the aircraft parts supply sector is becoming an obstacle to the development of the domestic MRO industry due to various characteristics. First of all, aircraft parts are highly diverse (60,000 to 70,000 per aircraft), and in particular, while rotable parts account for only about 10% of the total number of parts, they are so expensive that they represent 70% of the value. Furthermore, the barriers to entry are very high, as aircraft parts can only be produced and handled by a small number of aircraft manufacturers, such as Airbus and Boeing, and their certified suppliers, or by companies certified by the U.S. Federal Aviation Administration (FAA) or the European Aviation Safety Agency (EASA). Due to the lack of a domestic production base, the industry relies 100% on imports. Additionally, aviation regulations designate parts (NO-GO, IF-GO, GO) that determine whether an aircraft can operate in the event of a defect to ensure safe operation. Specifically, airlines are required to maintain a Minimum Equipment List (MEL) for 'NO-GO' parts that render an aircraft unoperable. Due to these regulations, airlines, particularly low-cost carriers (LCCs) with limited capital, face a significant financial burden in directly holding inventory of expensive repair parts. To address this, some airlines participate in 'pooling programs' operated by large overseas MRO companies or parts suppliers to lease and use parts. FIG. 1 is a block diagram showing the configuration of a circulation management system for repair parts for an aircraft according to one embodiment. FIG. 2 is a flowchart illustrating a method for managing the circulation of repair parts for an aircraft according to one embodiment. FIG. 3 is a flowchart illustrating a method for managing the circulation of repair parts for an aircraft according to one embodiment. FIG. 4 is a flowchart illustrating a method for managing the circulation of repair parts for an aircraft according to one embodiment. FIG. 1 is a block diagram showing the configuration of a system according to one embodiment. A system (100) according to one embodiment may include a processor (120) and a memory (130), and some of the illustrated components may be omitted or substituted. A system (100) according to one embodiment may be a server or a terminal. According to one embodiment, the processor (120) is a component capable of performing operations or data processing regarding the control and/or communication of each component of the system (100), and may be composed of one or more processors. The memory (130) may store information related to the method described above or store a program in which the method described above is implemented. The memory (130) may be volatile memory or non-volatile memory. The memory (130) may store various file data, and the stored file data may be updated according to the operation of the processor (120). According to one embodiment, the processor (120) can execute a program and control the device (100). The code of the program executed by the processor (120) can be stored in memory (130). Operations of the processor (120) can be performed by loading instructions stored in memory (130). The system (100) can