Maintenance Spare Parts Research Articles

Maintenance Spare Parts Prediction Based on Multilevel Migration Learning CNN-ISE-Attention-BiLSTM

Maintenance Spare Parts Prediction Based on Multilevel Migration Learning CNN-ISE-Attention-BiLSTM

A Predictive Model with Data Scaling Methodologies for Forecasting Spare Parts Demand in Military Logistics

This study addresses the challenge of accurately forecasting demand for maintenance-related spare parts of the K-X tank, influenced by high uncertainty and external factors. Deep learning models with RobustScaler demonstrate significant improvements, achieving an accuracy of 86.90% compared to previous methods. RobustScaler outperforms other scaling models, enhancing machine learning performance across time series and data mining. By collecting eight years’ worth of demand data and utilising various consumption data items, this study develops accurate forecasting models that contribute to the advancement of spare parts demand forecasting. The results highlight the effectiveness of the proposed approach, showcasing its superiority in accuracy, precision, recall, and F1-Score. RobustScaler particularly excels in time series analysis, further emphasizing its potential for enhancing machine learning performance on diverse datasets. This study provides innovative techniques and insights, demonstrating the effectiveness of deep learning and data scaling methodologies in improving forecasting accuracy for maintenance spare parts demand.

Principles Integration of Legal Certainty and Justice in Public Transportation Rates Policy

Online and conventional-based public transportation rates can be adjusted to possible fairest calculation by taking into account mileage, gasoline, and spare parts maintenance, this is as well as by primarily paying attention to and considering the driver partners who are members of it. Those circumstances will create effectivity and efficiency in order to have stable economy for Indonesia and the people. This study uses a normative juridical approach with the specification of the research is descriptive analytic. The results of the study show that the conformity policy concept of economic income in transportation businesses of both online-based public transportation and conventional public that integrates the principles of legal certainty and justice must carry out a reconstruction of the provisions of Article 183 paragraph 1 of Law no. 22 of 2009 concerning Road Traffic and Transportation.

Importance measure-based maintenance analysis and spare parts storage configuration in two-echelon maintenance and supply support system

The development of society has put forward higher requirements for the supply of maintenance spare parts. However, the current support index is not comprehensive enough to evaluate the system ability. Meanwhile, the influence of horizontal supply time on spare parts storage is not fully reflected. Therefore, the problem of spare parts storage configuration in two-echelon maintenance and supply support systems is analysed in the paper. First, the state transition rates of different parts are studied under the context. Then a system-level comprehensive support rate based on importance measure is proposed. To determine the number of different spare parts, an optimisation model is established to maximise system support efficiency. Furthermore, a site importance measure based on horizontal supply time is proposed to measure the site priority over spare parts storage. Next, a two-stage decision method is presented for determining the location of spare parts. Finally, the feasibility of the proposed method is verified with the help of an example for the aircraft maintenance and supply support system.

Research on maintenance spare parts requirement prediction based on LSTM recurrent neural network

Abstract The aim of this study was to improve the low accuracy of equipment spare parts requirement predicting, which affects the quality and efficiency of maintenance support, based on the summary and analysis of the existing spare parts requirement predicting research. This article introduces the current latest popular long short-term memory (LSTM) algorithm which has the best effect on time series data processing to equipment spare parts requirement predicting, according to the time series characteristics of spare parts consumption data. A method for predicting the requirement for maintenance spare parts based on the LSTM recurrent neural network is proposed, and the network structure is designed in detail, the realization of network training and network prediction is given. The advantages of particle swarm algorithm are introduced to optimize the network parameters, and actual data of three types of equipment spare parts consumption are used for experiments. The performance comparison of predictive models such as BP neural network, generalized regression neural network, wavelet neural network, and squeeze-and-excitation network prove that the new method is effective and provides an effective method for scientifically predicting the requirement for maintenance spare parts and improving the quality of equipment maintenance.

Reliability and redundancy allocation analysis applied to a nuclear protection system

Brazil is constructing with national technology two small nuclear reactors for propulsion and for radioisotope production with thermal power levels between 20 and 50 MW. These nuclear reactors fit more in the class of small modular reactors (SMR) than in the class of large nuclear power plants. In this article we apply the design approach of SMRs to propose an architecture of reactor protection systems for the small reactor under construction in the country. To do that the probabilistic analysis of the architecture of a nuclear reactor protection system is evaluated to determine the sensitivity of the components through an Reliability Block Diagram modeling. It was evaluated the modification of the architecture and the addition of redundancies when using components with lower life time than the components usually used for this purpose. The results showed that after one year of operation, the reference RPS system presents a failure probability of 0.17 %. The modified system, with components with lower life time, presents a point reliability value only 0.070 % lower than the reference one, but this difference grows exponentially over time, and in 10 years of operation it can reach values above 95%. Using equipment with lower life time characteristics implies a greater number of redundancies and, additionally, a greater number of maintenance procedures and spare parts. Therefore, this technical feasibility analysis should consider a RAM simulation as well.

Multi objective optimization of ship spare parts maintenance based on Improved Genetic Algorithm

For ship equipment turnover spare parts, if the maintenance interval is too long, the safety and working ability will be reduced; if frequent maintenance is performed, it will cause much waste. Therefore, it is necessary to determine the appropriate maintenance interval for resource optimization. The article analyzes the factors of turnover spare parts maintenance resource optimization. It establishes an equipment parts maintenance time resource optimization model based on maintenance theory and multi-objective decision-making methods, which can ensure the familiar training environment, maintenance type, and update type preventive maintenance mode The satisfaction is the largest, and group decision making and improved genetic algorithm are used to solve the optimal satisfaction. Finally, the effectiveness of the model is verified with examples of ship equipment spare parts.

Discussion about the maintenance period and spare parts of electric multiple units

This article firstly discusses the problem about maintenance period of electric multiple units (EMU); Secondly, the types of spare parts and process of calculating the quantity of them during the life cycle period for 30 years are introduced. At last, the determination process of preventive maintenance(PM) and corrective maintenance (CM) spare parts is introduced in detail by taking the secondary suspension of bogie system as example.

武器装备维修备件需求预测研究

武器装备维修备件需求预测研究

Research on Location Selection Strategy for Airlines Spare Parts Central Warehouse Based on METRIC.

With the increased demands of airlines, it is important to study the location selection strategy for spare parts central warehouse in order to improve the allocation capacity of spare parts maintenance resources and reduce the operating costs of airlines. Based on the M/M/s/∞/∞ multiservice desk model and Multi-Echelon Technique for Recoverable Item Control (METRIC) theory, this paper proposes a spare parts supply strategy based on the spare parts pool network and establishes a location selection model for spare parts central warehouse. The particle swarm optimization (PSO) algorithm is used to iteratively optimize the location for spare parts central warehouse and adjust the location area of the central warehouse combining transportation facilities and geographical environment factors. Finally, the paper compares the operating results for multiple airlines in pooling and off-pooling states and verifies the effectiveness of the spare parts supply model and the advantages of cost control for airlines.

DESIGN PROCESS OF DME STORAGE SYSTEM AS ASSEMBLY PARTS OR MAINTENANCE SPARE PARTS INVENTORY IN OFFSHORE OIL DRILLING PIPING SYSTEM

Discharge Manifold Equipment (DME) is an output pipe from a pump that bears an essential role in a piping system in offshore oil drilling, so it is a must to assure good bears condition whenever used. It is not an easy thing because DME is a significant and heavy component. Also, unfavourable conditions of offshore climate can accelerate its corrosion. Storage with the modular rack uses an offshore container certified DNV 2.7-1 / EN 12079 will be designed to fulfil those needs. The storage has an important role as an element in inventory, both the storage system for assembly parts or maintenance spare parts. This storage will be design using 4 (four) phases from VDI 2221 methods, namely; task clarification, conceptual design, embodiment design, and detailed design. Hydraulic power will be added to the system to support the piston movement so that the storage rack can be moved automatically by the hydraulic system. This storage has given the best solution for a systematic storing DME in the piping system of offshore oil drilling.

Research on Decision-making Method for Allocation of Product Maintenance Spare Parts

Under the current market situation, improving the efficiency and quality of after-sales service has become one of the effective means for improving the competitiveness of an enterprise. In this paper, the cost coefficient method is introduced into the research on decision-making method for allocation of product maintenance spare parts. By analyzing the factors influencing the transportation of maintenance spare parts, a model is established for the allocation cost coefficient of maintenance spare parts. The optimal transportation route of maintenance spare parts is calculated by using A-star algorithm. The optimal allocation scheme is obtained according to the table-manipulation method on linear programming. The feasibility of the model is verified by an example. The method is scientific, reasonable, simple and easy to learn. With strong generalization and operability, the method can effectively improve the allocation efficiency of maintenance spare parts and save the cost of after-sales service.

Multi-echelon inventory allocation of multi-indenture spare parts considering maintenance ratio

The existing multi-indenture spare parts maintenance has a certain maintenance proportion, a multi-echelon inventory allocation method with maintenance ratio for multi-indenture spare parts was proposed. Multi-echelon inventory allocation model for multi-indenture spare parts was established, which integrates maintenance rate into METRIC (Multi-echelon technique for recoverable item control) model, and then the marginal analysis method was applied to solve this model. First, the theory of multi-echelon inventory allocation model with maintenance ratio for multi-indenture spare parts was elaborated, and the mathematical model was established with the spare parts inventory cost as the optimization objective, the fleet availability as the constraints. Then, the procedure of solving the model by using marginal analysis method is discussed. Finally, taking an aircraft multi-indenture LRU (Line repairable units) as the research object, multi-echelon inventory allocation was investigated by considering maintenance ratio. The feasibility and effectiveness of the developed method are verified by an example analysis.

Maintenance Spare Parts Demand Forecasting for Automobile 4S Shop Considering Weather Data

Maintenance spare parts demand forecasting is an important foundation of maintenance spare parts inventory control, which is an essential responsibility for managers of an automobile 4S shop. Although the existence of the effect of weather conditions on maintenance spare parts demand has been verified, the study on maintenance spare parts demand forecasting for an automobile 4S shop considering weather data has not been found. In this paper, a novel method is proposed for maintenance spare parts demand forecasting for an automobile 4S shop considering weather data. By taking into account three dimensions of weather data (i.e., temperature, visibility, and slipperiness) and delayed effects of weather conditions on maintenance spare parts demand, a vector of numerical weather data with 30 weather factors is constructed to represent the related weather conditions of a given day. Then, a back propagation (BP) neural network is trained and the weights of the 30 weather factors are determined. Similar historical cases of the target case are extracted, and two forecasting models are respectively trained based on extreme learning machine (ELM) and support vector machines (SVM) using the similar historical cases. The final forecasting model is determined by comparing the fitting precisions of the two forecasting models. The experimental study is conducted based on the real data of an automobile 4S shop. The results show that weather data is critical to maintenance spare parts demand forecasting for an automobile 4S shop, and the extraction of similar historical cases is an effective approach to capture the complex effect mechanism of weather data on maintenance spare parts demand.

The spare part maintenance of cake breaker conveyor with reliability centered spares method

The company that this research conducted is a manufacturing industry that produces CPO. Many machines in the production section need maintenance activities so that existing machines can work without inhibiting the production process. At seed processing station, there is CBC machine that experienced frequent occurrence damage. The machine applies corrective maintenance regardless of reliability machine production components, consequently, often occur sudden machine damage. Calculation of time interval-based maintenance policy scheduled discard task and needs a replacement component (spare part) that should be available are concerned with an optimal using method of Reliability-centered Spares (RCS). Based on the results of the calculations are based on a policy scheduled discard task then obtained a policy to perform maintenance on a screw conveyor components is 91 days, hangers and bearings are 40 days, jig-drilled couplings is 21 days. The result of the method of RCS acquired number of screw conveyor parts needs with this type of repair of repairable spare is 3 units for one year, while jig-drilled couplings with this type of repair repairable, need spare part 27 units for a year, as well as the hangers and bearing with this type of repair of repairable spare part, needs 21 units for one year.

Metoda oceny krytyczności części zapasowych oparta o rozmyty proces hierarchii analitycznej AHP i funkcję strat Taguchi

Effective and efficient operation of a manufacturing system highly depends on the timely and correct implementation of maintenance operations. One of the most important factors affecting the successful implementation of maintenance operations is the determination of suitable inventory control policies for maintenance spare parts. Effective spare parts inventory management requires the criticality evaluation of spare parts. In this study, a novel spare parts criticality evaluation approach is proposed. First, the evaluation criteria are determined based on literature review and expert opinion and Fuzzy Analytical Hierarchy Process (AHP) is used to determine the criteria weights. Next, Taguchi loss functions and simulation modeling are employed for the calculation of loss values for the spare parts. Finally, a criticality ranking of the spare parts is obtained based on the weighted loss values which are calculated using criteria weights and loss values. The applicability of the proposed approach was tested by applying it to a spare part criticality evaluation problem faced by a manufacturing company.

Multi-level product support, Availability, System dynamics

By using the principle of the system dynamics research, an availability model of product maintenance spare parts support system and the dynamic mechanism of multi-level support process was constructed. Dynamic analysis of control feedback relationship in multilevel maintenance support system and the maintenance spare parts flow in the system is carried out. Satisfactory strategies for improving the availability of products were explored by means of analysis of product support parameters in spare parts supply and maintenance. Dynamic simulation was carried out in multilevel support model of product cycle to verify the effectiveness of product support strategy.

A hybrid fuzzy MCDM approach based on fuzzy revised DEMATEL and ANP to evaluate fleet maintenance management

This study shows to the importance of maintenance management to increase the vehicles fleet availability. In reality there are several factors related to the maintenance process and procedures, maintenance outsourcing, spare parts, fleet size, age and environment having a direct and indirect influence with varying degrees affecting fleet management. In this sense two methods have been combined: fuzzy revised DEMATEL and analytic network process (ANP), to evaluate the levels of interdependence as well as relative weight of selected factors and then a model was proposed with five dimensions and their relative weights were calculated. This proposed approach has been implemented in public administration as a strategic decision support. Following this study the result shows that, Outsourced Maintenance Providers dimension is the weighted factor affecting maintenance service. By contrast, the lowest weight factors were Procedures and Technical Skills.

Inventory-transportation integrated optimization for maintenance spare parts of high-speed trains.

This paper presents a 0–1 programming model aimed at obtaining the optimal inventory policy and transportation mode for maintenance spare parts of high-speed trains. To obtain the model parameters for occasionally-replaced spare parts, a demand estimation method based on the maintenance strategies of China’s high-speed railway system is proposed. In addition, we analyse the shortage time using PERT, and then calculate the unit time shortage cost from the viewpoint of train operation revenue. Finally, a real-world case study from Shanghai Depot is conducted to demonstrate our method. Computational results offer an effective and efficient decision support for inventory managers.

Preventive maintenance task balancing with spare parts optimisation via big-bang big-crunch algorithm

Work balancing increasingly plays an important role in both the production and maintenance functions. However, the literature on work balancing problems in transfer line manufacturing systems provides little information on the contributions of maintenance technicians and spare parts with a focus on penalty, technicians’ costs and incentives for staff. Unlike existing reports, the current investigation attempts to solve the maintenance task balancing problem. It combines preventive maintenance technicians’ assignments with product demand and spares utilisation in a transfer line manufacturing system. It uses an optimisation framework that measures the success of post-line balancing solution performance in a system from a holistic perspective. The novelty of the approach lies in the integration of technicians and spare parts theory and the introduction of penalty, technicians’ costs and incentive for staff. The proposed optimisation method was applied to a case study for detergent manufacturing system as a means of testing the effectiveness and robustness of the approach. The results show that the proposed model appears to be effective. Some simulations were also carried out to complement practical results.