Metal Additive Manufacturing for Industry 4.0 Aerospace: Review and Research Agenda

1. Introduction

While technological advancements are a defining characteristic of each industrial revolution [1], they are not always the sole catalyst force behind these revolutions. Rather, other factors also contribute to their emergence and impact. One such influential factor is the pursuit of lower unit costs through the effective use of emerging technologies [2], resulting occasionally in an oversupply of goods and services. In the context of Industry 4.0 however, which is characterized by the integration of new technologies, an emerging driving force is the effective alignment of supply with demand. This is where Additive Manufacturing (AM), also known as 3D printing, takes centre stage due to its capability for on-demand production [3,4,5,6].

Throughout history, industrial revolutions have witnessed significant breakthroughs in technology that transform industries and reshape economies. From the mechanization of steam power in the First Industrial Revolution [7] to the utilization of electricity and assembly lines in the Second Industrial Revolution [8], and the rise of computers and automation in the Third Industrial Revolution [9,10,11], technology has played a pivotal role in driving change. However, it is crucial to acknowledge that other factors, such as economic, social, and political circumstances, also influence the onset and impact of these revolutions [12,13]. One major economical driver is the pursuit of gaining more market share through price-competitive strategies that focus on lowering unit costs. This pursuit of efficiency and cost reduction has often resulted in an overabundance of supply. Factors like improved production techniques, increased automation, economies of scale, and enhanced productivity contribute to the surplus. Although this excess supply initially fuels growth and expansion, it can eventually lead to inefficiencies, market saturation, and unsustainable practices.

In the context of Industry 4.0, which encompasses technologies like artificial intelligence [14], big data [15], the Internet of Things (IoT) [16], and advanced robotics [17], the focus is not merely to integrate them in one smart factory, but rather on using them effectively to match supply with demand [18], thus eliminating inefficiencies in the form of excess inventories or stockout events. By integrating these technologies, Industry 4.0 enables improved forecasting [19], real-time data analysis [20], demand-driven production [21], and flexible manufacturing systems [22]. The objective is to optimize production processes, reduce waste, minimize inventory, and swiftly adapt to changing market conditions. This approach ensures a more efficient allocation of resources and a synchronized supply chain that matches demand in a timely and customized manner. The aerospace industry particularly has long been at the forefront of technological innovation, consistently pushing the boundaries of what is possible in aviation. In the era of Industry 4.0, the aerospace sector is witnessing a transformative shift.

Among the technologies driving Industry 4.0 in aerospace, Metal Additive Manufacturing (MAM) stands out prominently [23,24,25]. Its capability for on-demand production makes it a key player in this new industrial era [26]. MAM allows for the creation of metal objects layer by layer, based on digital designs [27]. It offers the potential for decentralized production [28], rapid prototyping [29,30,31], customization [32,33], and reduced lead times [34,35]. This paper aims to provide a comprehensive review of the impact of MAM in Industry 4.0 aerospace, while also outlining a research agenda to address the challenges and opportunities that lie ahead.

MAM in the aerospace industry offers two crucial characteristics that contribute to higher performance: i. freedom of geometry [36] and ii. absence of tooling [37,38]. The freedom of geometry feature allows the production of highly complex shapes and structures without incurring additional costs, making it particularly advantageous for achieving lightweight parts in aerospace. Extensive discussions in the literature have emphasized this aspect and its potential benefits [23,26,39,40]. Conversely, the absence of tooling offers increased flexibility and enables just-in-time production, yet it has received limited attention in the literature [41]. However, this aspect holds great relevance to the core objective of Industry 4.0, which aims to prevent overproduction and effectively match demand with supply [18]. Addressing this aspect is crucial in leveraging the potential of MAM to optimize production processes and enhance supply chain management in the aerospace industry.

It is crucial to briefly discuss the relevance of MAM to the aerospace industry in comparison to conventional methods. Figure 1 presents a comparison between MAM and conventional manufacturing, focusing on unit cost optimality [23]. This comparison is based on two crucial factors: production volume and product complexity. In terms of production volume, it is well-established that AM exhibit cost-effectiveness for the production of small batches [42,43,44]. On the other hand, an inherent advantage of AM lies in its ability to handle complexity during the manufacturing process [45]. This unique capability allows for the creation of innovative designs, resulting in improved performance while reducing overall system mass. Such achievements are beyond the reach of conventional manufacturing methods. Moreover, the design approach of AM facilitates weight lightning through both component consolidation and enhanced technical efficiency [46]. Part consolidation is yet another area where AM stands out [47,48]. This process involves redesigning multiple interacting components into a single integrated system, resulting in substantial improvements in technical performance. The optimality of AM in terms of unit cost is evident when considering production volume and product complexity. Its ability to handle complexity, coupled with the absence of tooling enabling it to economically produce small batches, make AM a valuable technology with vast potential for various industries.

When examining its alignment with the typical product life cycle [49], see Figure 1, the impact of MAM on the aerospace industry can be classified into four major domains. Firstly, MAM has the potential to reduce the risk of failure during new product introductions by enabling faster and more efficient iterations without the need for costly moulds [29]. Secondly, MAM effectively isolates personalization from the market during the growth stage, either through series combination [50] or in parallel with conventional manufacturing methods [51,52]. The third domain involves the strategic utilization of MAM during the maturity stage to prevent stockout events by complementing conventional production planning and inventory control techniques [53]. Lastly, MAM can be effectively employed to manage variability in demand, particularly in the spare parts industry of aerospace [51]. Throughout the entire aerospace product life cycle, MAM can be distinctly applied to optimize supply and demand, thereby paving the way for the next industrial revolution in the aerospace sector. This paper adopts this categorization while examining the impact of MAM on the aerospace industry to enable the realization of Industry 4.0.

Figure 2. Alignment of MAM to the product life cycle in relation to Industry 4.0 (figure constructed based on [49]).

Figure 2. Alignment of MAM to the product life cycle in relation to Industry 4.0 (figure constructed based on [49]).

This paper aims to cluster and review the literature on MAM in the aerospace industry, specifically focusing on its relevance to Industry 4.0 and its applicability throughout the various stages of the product life cycle. To achieve this, the paper adheres to a structured organization as follows: Section 1 provides an introduction to the topic of MAM in aerospace, emphasizing its significance in the context of Industry 4.0. In Section 2, a review is conducted, exploring the intersection of MAM and Industry 4.0 within the aerospace domain. This section is further divided into four subsections, each dedicated to reviewing distinct streams of relevant literature based on the described product life cycle stages. The subsections aim to identify gaps in the existing research, thereby paving the way for further investigation by outlining the research agenda for each reviewed area. Finally, Section 4 concludes the paper with a summary of key findings and concluding remarks, summarizing the significance of MAM in aerospace and its implications for Industry 4.0.

2. Review of Rollout Scenarios

Before embarking on reviewing the impact of MAM on Industry 4.0 aerospace, it is imperative to briefly discuss the MAM technologies that have been adopted in the aerospace industry and have significant potential. Laser Powder Bed Fusion (L-PBF) [54,55], Electron Beam Powder Bed Fusion (EB-PBF) [56] and Directed Energy Deposition (DED) [57] are MAM processes primarily utilized in the aerospace industry. These technologies have gained significant prominence in aerospace manufacturing due to their ability to produce complex, lightweight metal components with high precision and mechanical properties suitable for aerospace applications. L-PBF utilizes high-power lasers to selectively melt and solidify metal powder layers, offering design flexibility and high precision for producing complex, lightweight components. EB-PBF employs a high-energy electron beam in a vacuum environment to melt metal powder layers, resulting in components with properties similar to cast materials. DED processes, on the other hand, deposit material locally using powder or wire feedstock. DED techniques provide geometric freedom and are suitable for manufacturing large components, commonly used in repairing high-value components such as turbine blades. DED has lower resolution compared to powder bed processes and is suitable for larger components or when post-processing machining is feasible. LP-DED and LW-DED are specific forms of DED that use lasers and wire feedstock, respectively, with their advantages and limitations. The next subsections review the literature on the use of these technologies in relation to a product life cycle, as shown in Figure 1.

2.1. MAM to Reduce Failure Risk during the Introduction Stage

MAM has brought about a revolutionary shift in the aerospace industry, particularly in the realm of prototyping [58]. Its capability to rapidly produce complex and custom parts at reduced costs has garnered significant attention [59,60]. Prototyping is a critical stage in aerospace product development, allowing engineers to validate designs and address potential issues before full-scale production [26]. However, the selection of the appropriate product introduction strategy, whether stage gate [61], market-based [62] or learning-based [63], is vital to effectively leverage AM in prototyping, particularly in the face of uncertainties in both market and technology.

The learning-based strategy is centred around iterative learning and adaptation through continuous experimentation and feedback [64]. This approach is well-suited for aerospace prototyping where high levels of uncertainty exist in both the market and technology. AM-driven prototyping in aerospace can greatly benefit from this approach, primarily due to the absence of tooling requirements and the potential for on-demand production. These features enable faster iterations at minimum costs, allowing engineers to swiftly fabricate and test multiple iterations of components like airfoils, fuselage parts, and engine components. As a result, the learning-based strategy facilitates rapid learning, enabling engineers to identify optimal designs and material combinations that enhance performance and safety.

On the other hand, the stage gate strategy involves dividing the product development process into distinct stages or gates, each marked by specific deliverables and milestones [65]. This approach proves advantageous when the market is relatively known, but certain technological uncertainties remain [66]. Aerospace innovation projects with clear market requirements but unproven technologies can benefit from a stage gate approach when employing AM in prototyping. The freedom of geometry feature offered by MAM and the ability to consolidate parts prove invaluable in this strategy. Manufacturers can utilize AM to rapidly prototype aircraft interior components, engine parts, and other critical elements. By subjecting these prototypes to rigorous testing at different stages, the stage gate model ensures that each design iteration progresses through predefined gateways, verifying its performance and safety.

MAM has significantly enhanced prototyping in the aerospace industry, offering rapid iteration and cost-effective development of complex components. The choice between a learning-based and stage-gate strategy depends on the level of uncertainty in both the market and technology. Figure 3 below maps the introduction strategies to the corresponding market and technological uncertainty levels. Koen, et al. [67] proposed a comprehensive three-dimensional innovation typology that categorizes innovations into incremental, architectural, and radical types. Incremental innovation pertains to refining and enhancing existing technologies, aiming for gradual improvements. On the other hand, architectural innovation involves novel ways of integrating existing components into a system, without introducing new technology. Lastly, radical innovation revolves around introducing entirely new core technologies or tools, pushing the boundaries of what was previously impossible. This paper synthesizes this dimension, the technology dimension, with the market dimension based on the work of [68,69] where the market uncertainty level can be categorized with its corresponding customer service level. At the lower end of the spectrum, some customers are provided with more features than they require, while at the other end, certain customers are overlooked and underserved, with the possibility of not being served at all.

The learning-based strategy harnesses the absence of tooling and on-demand production features in MAM to allow for faster iterations with minimum costs, making it ideal for high-uncertainty environments. On the other hand, the stage gate approach capitalizes on the freedom of geometry and parts consolidation features in MAM to enhance performance aspects, such as lightweight and other related performance aspects, in situations with known market requirements but technological uncertainties. By aligning the right strategy with the prevailing uncertainties, aerospace companies can leverage the potential of MAM in prototyping to accelerate innovation and maintain a competitive edge in the ever-evolving industry. Based on the surveyed literature, MAM is mainly employed in the Evolutionary Innovation domain shown in Figure 3. Within this domain, MAM serves distinct subdomains, the least of which is the Radical Innovation field. In this field of innovation and prototyping, new and novel materials are utilized with MAM that cannot be otherwise utilized [70,71,72,73,74,75]. On the other hand, a literature review reveals that AM can be utilized for Incremental Innovation in the tooling and fabrication of moulds [76,77,78,79,80,81]. in this area of research, AM is utilized for the aspect of cost only; hence does not necessarily induce Architectural or Radical Innovation. Most of MAM applications however have been clustered to serve the Architectural Innovation type. In this innovation type, MAM is employed with the redesign needed to reduce part counts (i.e. parts consolidation) [82,83,84,85], reduce the overall mass (i.e. lightweight products) [46,86,87,88,89,90], enhance the internal cooling [91,92], or to avoid certain defective/limitation aspects in traditionally made products and enhance certain functional performance aspects [93,94,95,96,97,98,99]. Table 1 summarizes the relevant literature and categorizes them based on Figure 3.

The adoption of MAM for prototyping across industries, including aerospace, has been a significant driving force. However, the existing literature falls short in discussing how this cutting-edge technology can be effectively utilized within the context of product introduction strategies, particularly within the learning-based strategy. One especially promising approach gaining traction in learning-based strategies is the concept of the Minimum Viable Product (MVP). The MVP approach emphasizes the development of products that may not be perfect but can serve as valuable tools for market feedback [100]. While this concept has been embraced extensively in the information technology industry [101], its implementation in the manufacturing sector, especially within aerospace, remains limited. Therefore, this paper aims to address the gaps in the literature by exploring the applicability of MAM in aerospace for launching MVPs effectively, while ensuring critical aspects of quality and certification are not compromised. By addressing the gaps in the literature and exploring the potential of MAM for aerospace prototyping, the following research agenda aims to pave the way for more effective utilization of MVPs within the aerospace industry.

Table 2. Research agenda for the application of MAM in aerospace during the product introduction stage to reduce the risk of failure.

Research agenda	Research objectives
Assessing the Viability of MAM-Enabled Minimum Viable Products (MVPs) in Aerospace	Conduct case studies and empirical research to investigate successful implementations of MAM in aerospace for prototyping and product launch. Analyze the factors influencing the effectiveness of MVPs produced using MAM in gathering market feedback and facilitating product improvement.
Developing a Framework for Balancing Quality and Certification Requirements	Investigate the challenges associated with achieving the necessary quality standards and certification in aerospace when utilizing MAM for MVP development. Propose a framework that ensures MVPs meet regulatory requirements while embracing the inherent iterative nature of MAM-based prototyping.
Identifying Barriers to Widespread Adoption of MVPs in Aerospace	Conduct surveys and interviews with industry experts and stakeholders to understand the reasons behind the limited acceptance of MVPs in aerospace. Explore the cultural and organizational factors that hinder the adoption of MVPs and MAM technologies, seeking strategies to overcome resistance.
Characterizing Uncertainty Levels in MAM Prototyping	Develop a comprehensive model to assess uncertainty levels in different prototyping areas within aerospace based on market dynamics and technological advancements. Establish guidelines to assist decision-making regarding the most suitable prototyping
Evaluating Cost-Benefit Analysis of MAM-Based MVP Launch	Quantify the potential cost savings and time-to-market advantages of introducing MVPs in aerospace through MAM technology. Compare the financial implications of iterative MAM-based prototyping against traditional prototyping methods to showcase its economic viability.
Integrating MAM in Existing Aerospace Product Introduction Strategies	Explore how MAM can complement or enhance traditional product introduction strategies in aerospace, taking into account the diverse manufacturing requirements and regulations. Develop practical guidelines for incorporating MAM in existing strategies to ensure seamless integration and optimized results.

Table 2. Research agenda for the application of MAM in aerospace during the product introduction stage to reduce the risk of failure.

Research agenda	Research objectives
Assessing the Viability of MAM-Enabled Minimum Viable Products (MVPs) in Aerospace	Conduct case studies and empirical research to investigate successful implementations of MAM in aerospace for prototyping and product launch. Analyze the factors influencing the effectiveness of MVPs produced using MAM in gathering market feedback and facilitating product improvement.
Developing a Framework for Balancing Quality and Certification Requirements	Investigate the challenges associated with achieving the necessary quality standards and certification in aerospace when utilizing MAM for MVP development. Propose a framework that ensures MVPs meet regulatory requirements while embracing the inherent iterative nature of MAM-based prototyping.
Identifying Barriers to Widespread Adoption of MVPs in Aerospace	Conduct surveys and interviews with industry experts and stakeholders to understand the reasons behind the limited acceptance of MVPs in aerospace. Explore the cultural and organizational factors that hinder the adoption of MVPs and MAM technologies, seeking strategies to overcome resistance.
Characterizing Uncertainty Levels in MAM Prototyping	Develop a comprehensive model to assess uncertainty levels in different prototyping areas within aerospace based on market dynamics and technological advancements. Establish guidelines to assist decision-making regarding the most suitable prototyping
Evaluating Cost-Benefit Analysis of MAM-Based MVP Launch	Quantify the potential cost savings and time-to-market advantages of introducing MVPs in aerospace through MAM technology. Compare the financial implications of iterative MAM-based prototyping against traditional prototyping methods to showcase its economic viability.
Integrating MAM in Existing Aerospace Product Introduction Strategies	Explore how MAM can complement or enhance traditional product introduction strategies in aerospace, taking into account the diverse manufacturing requirements and regulations. Develop practical guidelines for incorporating MAM in existing strategies to ensure seamless integration and optimized results.

2.2. MAM to Isolate Personalization in Demand

The aerospace industry often requires a balance between standardization and customization to meet diverse customer needs and enhance operational efficiency [102,103]. MAM has emerged as a transformative technology that offers unique advantages in producing personalized products. This section explores how MAM can effectively isolate personalized products in aerospace, enabling customization while maintaining the benefits of conventional manufacturing for standardized components.

One approach to isolating personalized products in aerospace is through a parallel combination of MAM and conventional manufacturing methods [97]. MAM excels in producing complex geometries and intricate designs that are challenging or impossible to achieve using traditional manufacturing techniques [45]. This flexibility allows engineers and designers to optimize the performance of aerospace components and structures, enhancing their reliability and reducing the risk of failure. By utilizing MAM, personalized components, such as aircraft interior elements, can be produced separately while standardized parts are manufactured using conventional methods. For instance, MAM can be employed to create customized seat brackets, armrests, and overhead storage compartments that cater to specific aircraft configurations or individual passenger preferences. At the same time, conventional manufacturing methods can be utilized for standardized components like overhead bins, floor panels, or door frames, ensuring efficiency and uniformity. Chiu and Lin [52] suggested employing MAM as a complementary capacity for the conventional manufacturing method.

Another approach to isolating personalized products is through a series combination of AM and conventional manufacturing methods. This does not relate to the combination under one functional unit, as discussed in [104,105,106,107,108], but as separate units that complement each other [50,52]. This approach involves utilizing AM for design optimization, followed by the transition to conventional manufacturing for large-scale production. In the aerospace industry, this series combination is particularly useful during engine prototype development [86]. AM allows for the production of rapid prototypes of complex engine components, such as turbine blades or combustor geometries. As discussed in Section 2.1, the flexibility of MAM enables quick iterations and testing of various designs, facilitating the optimization of performance and efficiency. Once the design is finalized, conventional manufacturing methods, such as casting or precision machining, can be employed for mass production of standardized engine components. A prominent illustration of this scenario can be found in the work by Froes [109], where AM was utilized for the development of the passenger seat mould followed by conventional casting. By leveraging AM in the prototyping phase and transitioning to conventional methods for mass production, the development process can be streamlined, reducing costs and ensuring consistent quality.

The following research agenda listed in Table 2 highlights the potential of MAM in isolating personalized products in the aerospace industry. By exploring parallel and series combinations and complementary capacity, aerospace manufacturers can efficiently leverage the MAM capabilities for customization while ensuring the benefits of conventional manufacturing for standardized parts. The insights gained from this research will contribute to enhancing aerospace product development, improving supply chain management, and driving innovation in the aerospace industry.

Table 3. Research agenda for the application of MAM in aerospace during the product's growth stage to isolate personalization and achieve mass customization with MAM.

Research agenda	Research objectives
Parallel Combination of AM and Conventional Manufacturing	Investigate the optimal implementation of a parallel combination of MAM and conventional manufacturing methods for personalized aerospace components. Examine scenarios where MAM is used for customized seat brackets, armrests, and overhead storage compartments, while traditional methods are employed for standardized components like overhead bins, floor panels, and door frames.
Series Combination of AM and Conventional Manufacturing	Explore the benefits of a series combination of MAM and conventional manufacturing techniques in aerospace product development. Investigate cases where MAM is utilized for rapid iterations and design testing, leading to final designs transferred to conventional methods for large-scale production, such as casting or precision machining. Examine cases of successful transitions from AM-based prototyping to conventional mass production in the aerospace industry.
Complementary Capacity of MAM in Conventional Manufacturing	Investigate how MAM can serve as a complementary capacity to conventional manufacturing methods in aerospace production. Examine scenarios where MAM is utilized alongside traditional techniques to enhance production efficiency and product performance.

Table 3. Research agenda for the application of MAM in aerospace during the product's growth stage to isolate personalization and achieve mass customization with MAM.

Research agenda	Research objectives
Parallel Combination of AM and Conventional Manufacturing	Investigate the optimal implementation of a parallel combination of MAM and conventional manufacturing methods for personalized aerospace components. Examine scenarios where MAM is used for customized seat brackets, armrests, and overhead storage compartments, while traditional methods are employed for standardized components like overhead bins, floor panels, and door frames.
Series Combination of AM and Conventional Manufacturing	Explore the benefits of a series combination of MAM and conventional manufacturing techniques in aerospace product development. Investigate cases where MAM is utilized for rapid iterations and design testing, leading to final designs transferred to conventional methods for large-scale production, such as casting or precision machining. Examine cases of successful transitions from AM-based prototyping to conventional mass production in the aerospace industry.
Complementary Capacity of MAM in Conventional Manufacturing	Investigate how MAM can serve as a complementary capacity to conventional manufacturing methods in aerospace production. Examine scenarios where MAM is utilized alongside traditional techniques to enhance production efficiency and product performance.

2.3. MAM to Prevent Stockout Events

The previous section discussed the utilization of MAM in aerospace to address personalization, typically during the product's growth stage. This section focuses on the application of MAM in the product maturity stage, where customer preferences are known, and the product is ordered in high volumes. However, due to demand variability, stockouts occur, resulting in penalties [110]. In certain instances, MAM is adopted as a preventive measure to avoid stockout events [53,111]. A stockout event occurs when a customer places an order for a particular item, but the item is not available in the inventory [112]. In such cases, MAM can be leveraged to produce the item on-demand, ensuring that the customer order is fulfilled promptly and preventing the occurrence of stockouts. Traditional manufacturing methods typically rely on mass production and inventory management to meet customer demand [113]. However, maintaining large inventories of every possible product variant can be expensive and inefficient [114]. Moreover, predicting the exact quantity and variety of products that customers will demand is a complex task, often leading to stockouts for specific items [115].

MAM provides a solution to this challenge by enabling on-demand production of items as per customer orders. When an order is received for a specific item that is not currently in stock, the manufacturer can utilize MAM technology to produce the item quickly and efficiently. This eliminates the need to rely solely on pre-manufactured inventory and ensures that customers receive their desired products without delays or stockouts. By adopting MAM in such cases, greater responsiveness to buyer demands is achieved, as items can be produced as soon as the orders are received. This flexibility helps to meet customer expectations and enhances customer satisfaction. Furthermore, MAM enables manufacturers to reduce inventory holding costs. Instead of maintaining a large inventory of every possible item, they can rely on a smaller stock of raw materials and produce items as needed through MAM. This reduces the risk of overstocking or obsolete inventory, leading to cost savings and improved inventory management.

The following research agenda outlined in Table 3 addresses the gap in the literature by exploring the application of MAM in the aerospace industry during the product's maturity stage to prevent stockout events. By evaluating the effectiveness of MAM, optimizing on-demand production, developing responsive inventory management strategies, assessing customer satisfaction, and conducting cost-benefit analyses, this research aims to provide valuable insights for aerospace manufacturers seeking to enhance their supply chain efficiency, customer service, and overall competitiveness.

Table 4. Research agenda for the application of MAM in aerospace during the product's maturity stage to prevent stockout events and enhance supply chain efficiency.

Research agenda	Research objectives
Assessing the effectiveness of MAM in preventing stockout events in the aerospace	Conduct empirical studies to evaluate how MAM can effectively prevent stockout events in the aerospace industry. Analyze real-world case studies and industry data to quantify the impact of MAM implementation on reducing stockout occurrences and the associated penalties. Compare the performance of MAM-based on-demand production with traditional mass production and inventory management strategies in terms of cost-effectiveness and customer satisfaction.
Development of responsive inventory management strategies	Propose inventory management strategies that integrate MAM with traditional manufacturing methods to achieve greater responsiveness to customer demands. Design frameworks to dynamically adjust inventory levels based on demand forecasts and real-time order data. Compare the cost-effectiveness and inventory turnover rates of MAM-based on-demand production with traditional inventory management approaches.
Cost-benefit analysis of MAM adoption in aerospace	Evaluate the financial implications of reducing inventory holding costs, avoiding stockout penalties, and meeting customer demand with timely delivery through MAM. Consider the initial investment in MAM technology, operating costs, and long-term financial benefits to determine the overall economic viability and return on investment.

Table 4. Research agenda for the application of MAM in aerospace during the product's maturity stage to prevent stockout events and enhance supply chain efficiency.

Research agenda	Research objectives
Assessing the effectiveness of MAM in preventing stockout events in the aerospace	Conduct empirical studies to evaluate how MAM can effectively prevent stockout events in the aerospace industry. Analyze real-world case studies and industry data to quantify the impact of MAM implementation on reducing stockout occurrences and the associated penalties. Compare the performance of MAM-based on-demand production with traditional mass production and inventory management strategies in terms of cost-effectiveness and customer satisfaction.
Development of responsive inventory management strategies	Propose inventory management strategies that integrate MAM with traditional manufacturing methods to achieve greater responsiveness to customer demands. Design frameworks to dynamically adjust inventory levels based on demand forecasts and real-time order data. Compare the cost-effectiveness and inventory turnover rates of MAM-based on-demand production with traditional inventory management approaches.
Cost-benefit analysis of MAM adoption in aerospace	Evaluate the financial implications of reducing inventory holding costs, avoiding stockout penalties, and meeting customer demand with timely delivery through MAM. Consider the initial investment in MAM technology, operating costs, and long-term financial benefits to determine the overall economic viability and return on investment.

2.4. MAM to Isolate Demand Variability

During the transition of a product from maturity to the decline stage in its life cycle, demand becomes more variable than what was anticipated during the maturity stage. This phenomenon is especially relevant in the spare parts industry [116,117,118]. In the spare parts industry, demand variability can pose significant challenges. Manufacturers often face fluctuations in the demand for specific parts, leading to inefficiencies in traditional mass-production processes and sometimes causing a reliance on the flexibility offered by skilled labour [119]. MAM presents a viable solution by allowing the on-demand production of spare parts, thereby minimizing the impact of demand variability. Sasson and Johnson [51] investigated the potential of AM to mitigate manufacturing variability related to low-volume parts. In comparison to existing research, they proposed a distinct AM implementation strategy, adoption by different industry players, and a reconfiguration of the supply chain. The authors highlight mass manufacturing variability reduction as the key driver for AM adoption, a factor that holds significant relevance, especially in the aerospace spare parts industry.

One of the key advantages of AM in this context is its ability to isolate and manage the variability associated with low-volume part production. By utilizing AM for producing spare parts, aerospace manufacturers can overcome the limitations of traditional mass production, which typically involves producing parts in large quantities and storing them in inventory [120]. AM enables the production of spare parts in response to specific demand, reducing the risk of excess inventory or shortages. Despite being more expensive than mass production methods [43], the ability of MAM to address demand variability makes it a preferred choice for spare parts manufacturers. The cost of maintaining inventory and managing unpredictable demand patterns can often outweigh the higher per-unit cost of MAM [121]. By leveraging MAM for spare parts, manufacturers can achieve greater flexibility and responsiveness in meeting customer needs while minimizing the risks associated with demand fluctuations.

One relevant application in the after-sales service is the isolation of demand variability caused by legacy aircraft. Legacy aircraft, which are no longer in production, pose difficulties in sourcing replacement components. Specialized MRO companies are working to address this supply issue, particularly when the original component suppliers have ceased operations, taking their intellectual property with them. The absence of tooling in MAM makes it an appealing option in such cases, where legacy aircraft require unique, one-of-a-kind products [97,122]. In the same vein, Froes and Boyer [123] showed how MAM can be applied to repair existing bladed rotors (i.e. Blisks).

Based on the premise that MAM can effectively prevent stockout events (as discussed in the previous section) and isolate demand variability, Figure 4 below presents a flowchart that distinguishes between these two drivers. The flowchart begins by scanning the spare parts to identify components with high demand volatility. Subsequently, each part's historical records are analyzed to determine whether it was previously ordered in small batch sizes or high volumes. If the part was previously ordered in high volumes, the conventional Economic Production Quantity (EPQ) method is applied, and the optimal quantity is produced using traditional manufacturing methods. However, there remains a risk of stockout occurrences in this approach, and MAM can be employed to proactively prevent such stockouts. On the other hand, if the expected batch size is small or even consists of a single order (e.g. legacy aircraft repair), MAM is leveraged as an on-demand production solution that responds to orders that may disrupt production schedule due to unexpected low volumes. This flowchart provides a systematic approach for determining whether to use conventional manufacturing or MAM based on the demand characteristics of spare parts, thereby enhancing supply chain efficiency and responsiveness.

The following research agenda outlined in Table 4 seeks to bridge the gap in the literature by exploring the application of MAM in managing demand variability during the transition from the maturity to the decline stage of a product's life cycle, specifically in the aerospace spare parts industry. Through the analysis of demand variability, cost-benefit assessments, exploration of unique applications for legacy aircraft, supply chain integration strategies, and case studies, this research aims to provide valuable insights for aerospace manufacturers and MRO companies seeking to enhance supply chain efficiency, reduce costs, and improve customer satisfaction in the spare parts industry.

Table 5. Research agenda for the application of MAM in aerospace during the product's decline stage to isolate demand variability and avoid disruption to the spare parts management.

Research agenda	Research objectives
Assessing the feasibility and cost-benefit of mam for spare parts production	Perform a cost-benefit analysis of implementing MAM for producing spare parts in response to demand variability. Evaluate the economic implications of MAM adoption, considering factors such as inventory holding costs, excess inventory, stockout penalties, and the overall efficiency of the supply chain.
Supply chain integration and implementation strategies	Develop frameworks and strategies for integrating MAM into the spare parts industry supply chain to effectively manage demand variability. Propose guidelines for optimizing the production process, lead times, and inventory levels through MAM adoption. Address potential challenges and constraints in transitioning from traditional mass production to MAM-based on-demand production.
Case studies and industry best practices	Conduct in-depth case studies on successful implementations of MAM for managing demand variability in the aerospace spare parts industry. Analyze best practices and lessons learned from aerospace manufacturers and MRO companies that have effectively leveraged MAM to improve supply chain responsiveness and spare parts availability.

Table 5. Research agenda for the application of MAM in aerospace during the product's decline stage to isolate demand variability and avoid disruption to the spare parts management.

Research agenda	Research objectives
Assessing the feasibility and cost-benefit of mam for spare parts production	Perform a cost-benefit analysis of implementing MAM for producing spare parts in response to demand variability. Evaluate the economic implications of MAM adoption, considering factors such as inventory holding costs, excess inventory, stockout penalties, and the overall efficiency of the supply chain.
Supply chain integration and implementation strategies	Develop frameworks and strategies for integrating MAM into the spare parts industry supply chain to effectively manage demand variability. Propose guidelines for optimizing the production process, lead times, and inventory levels through MAM adoption. Address potential challenges and constraints in transitioning from traditional mass production to MAM-based on-demand production.
Case studies and industry best practices	Conduct in-depth case studies on successful implementations of MAM for managing demand variability in the aerospace spare parts industry. Analyze best practices and lessons learned from aerospace manufacturers and MRO companies that have effectively leveraged MAM to improve supply chain responsiveness and spare parts availability.