Search Results (34)

The automobile industry is one of the world’s largest manufacturing sectors and a key contributor to economic growth. Demand forecasting plays a critical role in supply chain management within the automotive sector. Reliable forecasts are essential for production planning, inventory control, and meeting market demands efficiently. However, accurately predicting demand remains a challenge due to the influence of external factors such as socioeconomic trends and weather conditions. This study presents a systematic literature review of the forecasting methods employed within the automotive industry, encompassing both vehicle and spare parts demand. Following PRISMA guidelines, 63 publications were identified and analyzed, covering traditional statistical models such as ARIMA and SARIMA, as well as state-of-the-art artificial intelligence approaches, including artificial neural networks. The review finds that classical statistical models remain prevalent for vehicle demand forecasting, Croston’s method dominates spare parts forecasting, and AI-based techniques increasingly outperform conventional models in recent studies. Furthermore, the review compiles a broad set of external variables influencing demand and highlights the common challenges associated with demand forecasting. It concludes by outlining potential directions for future research. Full article

Three-Dimensional Printing (3DP) is rapidly emerging as a pivotal technology for advancing Facilities Management (FM) toward smart and sustainable buildings. This systematic review, following PRISMA 2020 guidelines, critically evaluates 3DP applications, benefits, and challenges across core FM domains—construction, maintenance and repair, supply chain management, and specialized applications—through analysis of 179 studies. To our knowledge, this represents the first comprehensive, FM-specific systematic review of 3DP implementation frameworks. Evidence synthesis reveals that 3DP enables on-demand, localized manufacturing of bespoke components, with documented inventory cost reductions in maintenance applications, substantial production cost decreases for complex geometries, and significant lead time improvements from traditional procurement cycles to rapid on-demand fulfillment for spare parts applications. However, quantitative evidence remains limited and context-dependent, particularly regarding economic feasibility and scalability. 3DP adoption in FM faces significant barriers: quality assurance protocols, workforce readiness, BIM/IoT integration challenges, and regulatory uncertainty. This review identifies the absence of validated decision-making frameworks to guide FM professionals on 3DP implementation versus traditional alternatives, a fundamental research and practice gap. Through structured quality assessment and stakeholder analysis, we propose strategic recommendations emphasizing cross-sector collaboration, standardization development, and workforce upskilling. A novel conceptual decision framework supports practical implementation decisions. These findings position 3DP as potentially transformative for sustainable building operations while highlighting critical research priorities for systematic FM sector deployment. Full article

The purpose of this study is to examine the spare parts supply chain when introducing new computer technology products to the market. Background: Despite the growing importance of after-sales service, the supply chain for spare parts for ICT (information and communications technology) products often receives insufficient attention. Materials and Methods: The data was obtained from an analysis of operational service logs encompassing 149,937 warranty service requests and associated Service Level Agreements, augmented by feedback from 1572 surveyed computer equipment customers regarding their after-sales service experience. The data refers to a period of one year (1 January 2023 to 1 January 2024) and takes into account all new products launched in the computer category during this period (116 new products), primarily focusing on equipment such as servers, and the product tree for each of these products. Results: The results are related to increasing requirements for after-sales service, in particular, the supply chain for spare parts, which is of great importance for the development and success of companies producing computing equipment. Conclusions: The study contains original results obtained during scientific research conducted by the authors in the field of logistics and supply chain for spare parts. Full article

As electric multiple unit (EMU) operations and maintenance demands have expanded, spare parts supply chain management has become increasingly crucial. This study emphasizes the supply challenges of EMU spare parts, including inadequate minimum inventory levels and prolonged response times. Redesigning the OEM–railway bureau vendor-managed inventory (VMI) model contract incentive and penalty system is the key goal. Connecting the spare parts supply system with its characteristics yields a game theory model. This study analyzes and compares the equilibrium strategies and profits of supply chain members under different mechanisms for managing critical spare parts. The findings demonstrate that mechanism contracts can enhance supply chain performance in a Pareto-improving manner. An in-depth analysis of downtime loss costs, procurement challenges, and order losses reveals their effects on supply chain coordination and profit allocation, providing railway bureaus and OEMs with a theoretical framework for supply chain decision-making. This study offers theoretical justification and a framework for decision-making on cooperation between OEMs and railroad bureaus in the management of spare parts supply chains, particularly for extensive EMU operations. Full article

In recent years, as an important alternative to traditional gasoline-powered vehicles, new electric vehicles (NEVs) have gained widespread attention and rapid development globally. In the traditional automotive industry chain, downstream vehicle manufacturers need to master core technologies, such as engines, chassis, and transmissions. In contrast to the traditional automotive industry chain, where downstream vehicle manufacturers must master core technologies, like engines, chassis, and transmissions, the electric vehicle industry chain has evolved in a way that the development of core components is gradually separated from the vehicle manufacturers. Downstream vehicle manufacturers can now outsource key components, such as batteries, electric controls, and motors. Additionally, in terms of sales models, the electric vehicle industry chain can adopt either the traditional 4S dealership model or a direct-sales model. As the research and development of core components are increasingly separated from vehicle manufacturers, the downstream vehicle manufacturers can source components, like batteries, electric controls, and motors, externally. At the same time, they can choose to use either the traditional 4S dealership model or the direct-sales model. The underlying mechanisms and channel selection in this context require further exploration. Based on this, a mathematical model is established by incorporating terminal marketing input, product competitiveness, and after-sales service levels from the literature to solve for the optimal pricing under centralized and decentralized pricing strategies. Using numerical examples, the pricing and profit performance under different market structures are analyzed to systematically examine the impact of the electric vehicle supply chain on business operations, as well as the changes in various elements across different channels. We will focus on how after-sales services (including the spare part supply) influence the pricing strategy and profit distribution in the supply chain, aiming to provide insights into advanced manufacturing system management for manufacturing enterprises and improve the efficiency of intelligent logistics management. The research indicates that (1) The direct-sales model helps to improve the terminal marketing input, after-sales service quality, and product competitiveness for supply chain stakeholders; (2) It is noteworthy that the manufacturer’s direct-sales model also significantly contributes to lowering prices, highlighting that the direct-sales model has substantial impacts on both supply chain stakeholders and, importantly, consumers. Full article

This research aims to identify patterns and root causes of aircraft downtimes by comparing various forecasting models used in the aviation industry to prevent AOG events effectively. At its heart, this study explores innovative forecasting models using time series analysis, time series modeling and binary classification to predict spare part usage, reduce downtime, and tackle the complexities of managing inventory for diverse aircraft fleets. By analyzing both data and insights shared by aviation industry experts, the research offers a practical roadmap for enhancing supply chain efficiency and reducing Mean Time Between Failures (MTBF). The thesis emphasizes how real-time data integration and hybrid forecasting approaches can transform operations, helping airlines keep spare parts available when and where they are needed most. It also shows how precise forecasting is not just about saving costs, it is about boosting customer satisfaction and staying competitive in an ever-demanding industry. In addition to data-driven insights, this research provides actionable recommendations, such as embracing predictive maintenance strategies and streamlining logistics. These steps aim to ensure smoother operations, fewer disruptions, and more reliable service for passengers and operators alike. Full article

The pursuit of energy security has become one of the most important challenges facing modern societies worldwide. The increase in energy consumption and the need to promote sustainability puts pressure on power generation systems. In this context, renewable energy sources have become a favorable option to improve both energy security and sustainability while promoting the use of domestic energy sources. The supply chain is an optimized methodology that includes all necessary activities to bring a product to the final consumer. Traditionally applied in the manufacturing industry, recent evidence shows its successful implementation in various renewable energy sectors. In this work, a novel methodology based on a supply chain was designed to evaluate the feasibility of mini wind power systems in urban areas in an integrated and measurable manner. The main contribution lies in the integration of several different approaches, currently recognized as the most relevant factors for determining the viability of wind energy projects. A five-link supply chain model was proposed, which includes an evaluation of wind potential, supplier network, project technical assessment, customer distribution, and equipment final disposal. Specific metric indicators for each link were developed to evaluate technical, legislative, and social considerations. The methodology was applied in a case study in the city of Mexicali, Mexico. The findings show that although wind as a resource remains the most important factor, local government policies that promote the use of renewable energy, the supplier’s availability, qualified human resources, and spare parts are also of equivalent significance for the successful implementation of mini wind power systems. Full article

Manufacturing supply chains are becoming increasingly complex due to geopolitical issues, globalization, and market demand uncertainties. These challenges lead to logistics disruptions, inventory shortages, and interruptions in raw materials and spare parts production, resulting in delayed delivery, reduced market share, and lower customer satisfaction. Effective supply chain management is critical for improving operational efficiency and competitiveness. This paper proposes a supply chain digital twin methodology to enhance operational efficiency through real-time monitoring, analysis, and response to disruptions. This methodology defines a supply chain digital twin system architecture and outlines the operational process of digital twin applications. It introduces two key modules: a digital twin module for prediction and monitoring and an optimization module for determining the optimal movement of products. These modules are integrated to align digital simulations with real-world supply chain operations. The proposed approach is validated through a case study of an automobile body production company’s supply chain, demonstrating its effectiveness in reducing inventory and logistics costs while providing countermeasures for abnormal situations. Full article

Spare parts search and retrieval processes are of paramount importance in manufacturing and supply chains. Image recognition using 2D and 3D image properties plays an important part in the success of such processes, as it facilitates the identification of the types and components associated with spare parts, a step that is crucial for their success. In this article, a novel Deep Learning-based object recognition model based on a convolutional neural network architecture is proposed and constructed using stacked convolutional layers to extract and learn features of the spare parts efficiently with the goal of improving the effectiveness of the spare part image recognition process. The proposed model is assessed using industrial spare parts datasets, and its performance is compared against different transfer learning models using precision, accuracy, recall, and F1 score. The proposed model demonstrated efficiency in spare parts recognition and achieved the highest accuracy compared to state-of-the-art image recognition models. Full article

This research investigates the potential of additive manufacturing (AM) to revolutionize the marine spare parts supply chain (SPSC). While AM has been widely explored in other industries, its application in the maritime sector remains limited. This study addresses this gap by comparing traditional and AM-integrated SPSC models using system dynamics simulation. By focusing on high- and low-value spare parts, this research highlights significant cost reductions and improved delivery times through strategic AM integration. Our findings demonstrate the potential of AM to enhance the efficiency and resilience of the maritime supply chain, particularly in remote environments. Full article

Proper supply chain management helps to ensure business continuity considering the increased importance of globalization. Logistics processes play an important role in keeping the supply chain running smoothly, and warehouse management is one of the most important logistics activities. The movement of freight flows in the supply chain poses many challenges to the arrangement of sustainable processes at the international level. The stopping of these flows at warehouses and/or terminals temporarily and/or for longer periods of time is yet another challenge. In this respect, a number of analyses and studies have been conducted in the scientific literature to identify the most serious and frequent problems: lack of planning of work activities, partial accounting of the work performed, lack of timely accounting of the internal movement of goods within the warehouse, absence of a spare-parts management system, etc. On the other hand, warehousing processes have been analysed to identify certain efficiency gaps in freight flows within warehouses; thus, this article addresses this problem by applying guanxi principles. Using guanxi theory and practice to test various assumptions for efficient freight flow movement in warehouses, a study was conducted using quantitative and qualitative methods and expert judgment. Based on the results of the conducted empirical studies, guanxi philosophy can be concluded to have an impact on the efficient management of warehouse processes when goods are removed from a warehouse over 365 days with an annual daily loading flow rate of 103,490 t/m and a loading density of 280 kg/m³. This indicates that the application of guanxi principles is important, which reflects the intensity of the logistics processes of cargo flows and transport dynamics between guanxi and warehouse optimization. Full article

Remanufacturing is one of the ways forward for product recovery initiatives and for maintaining sufficient production flow to satisfy customer demand by providing high-quality goods with a combination of new and return parts through a circular economy. Recently, manufacturers have been progressively incorporating remanufacturing processes, making their supply chains vulnerable to disruptions. One of the main disruptions that occurs in remanufacturing systems is the shortage of spare parts supply, which results in unexpected delays in the remanufacturing process and could eventually result in a possible loss of sales. In the event of such potential disruptions, remanufacturing facilities must manage their supply chains in an effective and optimal manner such that the negative impact of disruptions to their business can be minimised. In this study, a two-stage production–inventory system was analysed by developing a cost-minimisation model that focuses on the recovery schedule after the occurrence of a disruption in sourcing spare parts for a remanufacturer’s production cycle. The developed model was solved using the branch-and-bound algorithm, where the experimental results demonstrated that the model provides effective solutions. Through numerical experiments, results indicated that the optimal recovery schedule and the number of recovery cycles are considerably dependent on the disruption time, lost sales and backorder costs. A sensitivity analysis showed that the lost sales option seems to be more effective than the backorder sales option in optimising the system’s overall cost due to unmet demand, which becomes lost sales when serviceable items are reduced, thereby shortening recovery time. Furthermore, a case study revealed that a manufacturer’s response to disruption is highly influenced by the spare part costs and overall recovery costs as well as the supplier’s readiness level. The proposed model could assist managers in deciding the optimal production strategy whilst providing interesting managerial insights into vital spare parts recovery issues when disruption strikes. Full article

This paper presents a declarative model of maintenance logistics for offshore wind farms. Its implementation in decision-making tools supporting wind turbine maintenance enables online prototyping of alternative scenarios and variants of wind turbine servicing, including weather-related operation vessel movement and routing of unmanned aerial vehicle (UAV) fleets carrying out maintenance on these wind turbines during monitoring or component-delivery missions. The possibility of implementing the model was verified via two case studies focusing, separately, on the issues of routing and scheduling of a UAV fleet used for the inspection of wind turbines and the distribution of ordered spare parts. The open structure of the model allows for its easy generalization, expanding the range of supported functions, including vessel fleet routing in an offshore wind farm, staff and competence planning of service teams, and supply chain management, enabling the planning of tool sets distributed to serviced wind turbines. Computer experiments conducted for various weather conditions confirm the competitiveness of the proposed approach. Full article

Once on Mars, maintenance and repair will be crucial for humans as supply chains including Earth and Mars will be very complex. Consequently, the raw material available on Mars must be processed and used. Factors such as the energy available for material production play just as important a role as the quality of the material that can be produced and the quality of its surface. To develop and technically implement a process chain that meets the challenge of producing spare parts from oxygen-reduced Mars regolith, this paper addresses the issue of low-energy handling. Expected statistically distributed high roughnesses of sintered regolith analogs are approximated in this work by parameter variation in the PBF-LB/M process. For low-energy handling, a dry-adhesive microstructure is used. Investigations are carried out to determine the extent to which the rough surface resulting from the manufacturing process can be smoothed by deep-rolling in such a way that the microstructure adheres and enables samples to be transported. For the investigated AlSi10Mg samples (12 mm × 12 mm × 10 mm), the surface roughness varies in a wide range from Sa 7.7 µm to Sa 64 µm after the additive manufacturing process, and pull-off stresses of up to 6.99 N/cm² could be realized after deep-rolling. This represents an increase in pull-off stresses by a factor of 392.94 compared to the pull-off stresses before deep-rolling, enabling the handling of even larger specimens. It is noteworthy that specimens with roughness values that were previously difficult to handle can be treated post-deep-rolling, indicating a potential influence of additional variables that describe roughness or ripples and are associated with the adhesion effect of the microstructure of the dry adhesive. Full article

The aerospace industry faces challenges in managing inventory effectively due to long product life cycles and unpredictable demand. Additive Manufacturing (AM) is a promising technology that enables the on-demand production of spare parts, potentially reducing inventory costs and improving supply chain efficiency. This paper proposes a novel conceptual framework for employing AM in the aerospace spare parts industry to isolate demand volatility. A conceptual approach is employed in this study, which involves a comprehensive literature review to identify the factors to consider when employing AM for spare parts and the methods for demand volatility isolation, followed by a structured framework development that outlines the decision-making steps for AM utilization based on the identified factors. The framework outlines a structured approach for using AM to produce spare parts and isolate demand volatility, which can help mitigate the impact of demand uncertainty on inventory management. The proposed approach provides a basis for future research and has the potential to transform how spare parts are produced and managed in the aerospace industry. Overall, this paper contributes to the emerging literature on AM in the aerospace industry by presenting a novel approach to improving inventory management and addressing demand uncertainty. Full article