Revolutionizing the Marine Spare Parts Supply Chain through Additive Manufacturing: A System Dynamics Simulation Case Study

Abstract

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.

1. Introduction

Maintenance networks encompass a diverse range of stakeholders, including asset owners, systems integrators, original equipment manufacturers (OEMs), service providers, and their respective logistics entities [1]. Effective management of spare parts is pivotal for ensuring operational efficiency and minimizing downtime across various industries. The advent of technology offers transformative potential for optimizing spare parts supply.

Additive manufacturing (AM), often referred to as 3D printing, represents a transformative technology that contrasts traditional subtractive manufacturing methods. While technically distinct processes as defined by ISO/ASTM 52900(en) [2], the terms “additive manufacturing” and “3D printing” are often used interchangeably. For the purposes of this article, the broader term “additive manufacturing” is used, while the term “3D printing” is adopted when referring to the process of making the part, to align with the public understanding of this technology. By enabling decentralized production of small batches, AM offers the potential to optimize spare parts supply chains (SPSCs) through reduced inventory, shorter lead times, and lower costs [3]. As AM facilitates localized production of finished components, a growing body of research advocates for the digitization of spare parts and their decentralized creation [4,5]. The maritime sector is actively embracing technological advancements. Leading global manufacturers of marine propulsion engines recognize the potential of AM and are integrating this innovative process into their operations, extending beyond prototyping to encompass full-scale production. The shipping industry has undergone a digital transformation, emphasizing the strategic importance of seamless information exchange among diverse stakeholders, including maritime personnel, technological systems, and operational procedures [6]. To assess the influence of digital spare parts on operational frameworks, studies have examined supply chain models, spanning from centralized to fully dispersed configurations [5].

AM technologies induce far-reaching and interconnected transformations that impact multiple stages of the supply chain [7]. To assess the potential benefits of AM for the supply chain, executives should conduct a comprehensive evaluation across all operational levels, from initial product conception and design to manufacturing processes and physical facility configurations [8]. AM has shown promise in various industries such as aerospace/aviation [9,10,11], navy/defense [12] offshore oil and gas [13], automotives [14], and mechanical engineering [11].

Demand for spare parts is inherently unpredictable and sporadic, distinguishing it significantly from consumer product demand. This characteristic makes SPSC a distinct area of focus for research and industry [15,16,17] and in many cases, there are relatively limited historical demand data available [18].

Despite its pivotal role in global trade, the maritime industry has lagged behind other sectors in SPSC development due to its smaller scale. Consequently, applying insights from other industries requires a nuanced understanding of the maritime domain’s unique characteristics. These include isolated operating environments, exposure to corrosive conditions, frequent vibrations, reliance on technically skilled personnel, and established information systems [19].

While research on AM implementation in industries with similar characteristics to maritime, such as those involving mobile assets or isolated environments, has emerged, dedicated studies within the maritime sector remain limited.

This study aims to bridge this research gap by investigating the transformative impact of AM on the marine spare parts supply chain. By comparing traditional and digital supply chain models and analyzing cost and delivery time dynamics, this research seeks to demonstrate the feasibility and benefits of integrating AM technology into the maritime sector.

The specific objectives of this study are to

• Assess the current challenges and limitations of the traditional marine spare parts supply chain;
• Develop a digital supply chain model incorporating AM technology;
• Compare the performance of traditional and digital supply chain models in terms of cost and delivery time;
• Identify the potential cost savings and service time improvements offered by AM;
• Evaluate the feasibility of implementing AM technology in the maritime industry.

By addressing these research questions, this study contributes to the existing body of knowledge by providing empirical evidence on the impact of AM on the marine spare parts supply chain. The findings are expected to inform industry practitioners and policymakers in developing effective strategies for the management of spare parts in the maritime sector.

The rest of the paper is structured as follows.

First, our literature review provides an overview of existing research on the topic, identifies gaps in the knowledge, and justifies the current study. Then, our methodology is presented. Next, the locations of the warehouses in the specific supply chain and the choice of spare parts for the study with the most preferable characteristics were examined, and for these reasons, two spare parts—one of high and one of low cost—were selected for further investigation for modeling after a thorough check. These are a semi-open pump impeller (impeller) and a rubber fan gasket. Moreover, the modeling structure of the current and proposed situation is shown. Comparisons of the existing warehouse storage cost of the proposed total 3D printing hub with the existing total warehouse cost of the proposed total 3D printing hub and the existing spare part delivery time with the proposed delivery time are performed for all examined warehouses that have been converted to 3D printing hubs. Our study concludes with a discussion of the findings and their implications.

2. Literature Review

The evolution of supply chain management across various industries has been increasingly influenced by advances in technology, such as the integration of AM, which has had transformative effect on supply chain dynamics by enabling decentralized, on-demand production of parts. The literature underscores the varying degrees to which different industries have embraced AM, with studies predominantly focusing on aerospace, automotives, mechanical engineering, defense, and offshore oil. Each industry presents unique challenges and opportunities for AM adoption, especially in the context of SPSC [16]. The aerospace industry has been at the forefront of adopting AM technology due to its stringent requirements for lightweight, high-performance components. In this sector, AM has been employed for both prototyping and full-scale production of parts, contributing to enhanced operational efficiency and cost savings [9,10,11]. The adoption of AM in aerospace underscores its potential to streamline SPSC, offering valuable insights that can be extended to other sectors, including maritime. The automotive industry has seen widespread adoption of AM, driven by the need for customization, rapid prototyping, and production flexibility. The automotive sector’s experience with AM serves as a useful comparison for maritime applications, particularly in terms of implementing digital supply chains and reducing reliance on large, centralized warehouses [14]. The successful integration of AM in offshore oil can be translated to the maritime SPSC. Within the maritime sector, research on AM has been more limited, though its significance is growing. Studies highlight the potential of AM to address the unique challenges of maritime operations, such as the need for reliable spare parts in remote environments [20]. AM offers a solution to the logistical challenges faced by the industry, enabling decentralized production of critical components closer to the point of need [21]. Although progress has been slower in this sector compared to others, the integration of AM in maritime operations represents a promising direction for enhancing the efficiency of SPSC.

The adoption of AM within the maritime sector remains limited, with most research focusing on industries with similar operational contexts. However, the potential benefits of integrating AM into the maritime SPSC are significant. By producing parts closer to the point of need, AM can mitigate the challenges of long lead times, high transportation costs, and limited storage capacity, thereby enhancing operational efficiency.

While AM’s potential in sectors with mobile or isolated assets has been explored, there is a noticeable gap in dedicated studies within the maritime sector. This research aims to address that gap by evaluating the feasibility and benefits of incorporating AM into the maritime SPSC. By comparing traditional and digital supply chain models, this study will analyze how AM can reduce costs and improve delivery times, offering a novel approach to spare parts management in maritime operations (

Table 1. Highlighting the novelty and contributions of this study compared to the existing literature.

Contribution Area	Existing Literature	This Study’s Novel Contribution
1. Industry Focus	The majority of research is centered on industries like aerospace, automotive, defense, and offshore oil [9,10,11,14,16]. Studies on maritime applications of AM are limited.	This study focuses specifically on the maritime sector’s spare parts supply chain (SPSC), addressing the gap in existing research by evaluating the integration of AM in maritime operations.
2. Adoption of Additive Manufacturing (AM)	Research in sectors like aerospace and automotives highlights extensive use of AM for prototyping and full-scale production [9,10,11,14]. Limited research is available on AM adoption in the maritime sector.	This study examines the specific benefits and challenges of AM adoption within the maritime industry, exploring how it can enhance supply chain efficiency for spare parts.
3. Digital Supply Chain Integration	Previous studies in the aerospace and automotive sectors have explored the transition from traditional to digital supply chains, focusing on reducing lead times and inventory costs [9,11,14].	This research extends digital supply chain concepts to the maritime sector, comparing traditional and AM-based models for spare parts management, including cost and delivery time analysis.
4. Decentralized Production	Decentralized production models using AM have been studied extensively in sectors like aerospace and offshore oil [9,12,13]. Application in the maritime sector remains underexplored.	The study introduces a model for decentralized, on-demand production of maritime spare parts using AM, contributing to knowledge on maritime-specific supply chain solutions.
5. Logistical Challenges in Remote Environments	The literature highlights the logistical benefits of AM in sectors with isolated or mobile operations, such as offshore oil and aerospace [15]. There is limited focus on maritime contexts.	This study directly addresses maritime-specific logistical challenges, analyzing how AM can mitigate issues related to long lead times, transportation costs, and storage limitations.
6. Comparative Analysis of Traditional vs. AM Supply Chains	The existing literature provides comparisons with other industries but rarely focuses on maritime applications [21].	This study provides a detailed comparison between traditional and AM-based maritime supply chains, specifically evaluating cost savings and delivery time improvements for spare parts.

).

3. Methodology

This study employs a comparative analysis and system dynamics simulation to evaluate the impact of AM on the marine spare parts supply chain. The research focuses on the delivery of spare parts from order placement to onboard installation.

A traditional spare parts supply chain model was developed, encompassing ship, port, and regional warehouses. This model was subsequently adapted to incorporate a digital supply chain integrating AM technology. The digital supply chain utilizes encrypted data transmission to suitable 3D printers located near the point of demand.

To analyze the performance of both supply chain models, a system dynamics simulation was conducted using the Vensim PLE tool. This approach allowed for the modeling of complex interactions between system components, including inventory levels, transportation, and production processes.

The Vensim PLE 9.0 software used in this study provided a suitable platform for modeling the supply chain. However, limitations in handling large datasets necessitated data aggregation and simplification. To mitigate the potential impact of these simplifications, sensitivity analysis was conducted to assess the model’s robustness.

Cost and delivery time data were collected for two representative spare parts: a high-cost and a low-cost component. These data were used to parameterize the simulation models and assess the impact of AM on these key performance indicators.

The developed simulation models were validated through sensitivity analysis and comparison with industry data. This process ensured the accuracy and reliability of the simulation results.

Two scenarios were simulated, as follows.

Traditional supply chain: this scenario represents the current state of SPSC, with spare parts stored in physical warehouses.

Digital supply chain with AM: this scenario incorporates AM technology, enabling on-demand production of spare parts at or near the point of use.

The primary performance metrics for evaluating the two supply chain models were total cost (including production, transportation, and inventory costs) and delivery time (from order placement to part installation).

By comparing these metrics across the two scenarios, the study aims to assess the potential benefits of AM technology in the maritime spare parts supply chain.

The visual representation of the methodology below (Figure 1) outlines the sequential steps undertaken in the study, from problem definition to conclusion, encompassing model development, simulation, data analysis, and comparison of supply chain performance.

4. The Spare Part Supply Chain in the Maritime Sector: From Order to the End User

The network connecting the spare part manufacturer to the vessel in the maritime industry is a complex web with several key players, often spread across vast distances. Warehouses with part inventories play a crucial role in the maritime SPSC, acting as strategic hubs to bridge the gap between manufacturers and end user onboard. In the traditional maritime spare parts supply chain, getting a part from the ship’s order to onboard receipt involves several steps. First, the crew identifies the broken part and sends a request with details to the ship owner/manager. The owner then sources the part, considering factors like cost, availability, and how quickly they need it. Depending on urgency, the part might be flown in, shipped by sea, or even pre-positioned at a port the ship will visit next. Warehouses play a role in this process, with parts potentially moving from a manufacturer’s warehouse, a distributor’s stock in a key maritime hub, or even the ship owner’s own centralized warehouse. After international deliveries clear customs, the crew finally receives and inspects the part before updating their inventory system. This traditional approach faces challenges due to the vast distances involved in global shipping, the pressure to perform repairs quickly to avoid downtime, and the complexity of managing inventory to ensure parts are available when needed.

While still evolving, AM has the potential to create certain spare parts on-demand at key locations or even onboard vessels in the future. This would significantly improve responsiveness for emergencies and reduce reliance on traditional supply chains. The decision to manufacture spare parts in-house or source them from external suppliers presents a strategic challenge for maritime companies. In-house manufacturing offers potential cost control and faster lead times for critical parts, but necessitates significant upfront investment and technical expertise [17]. Conversely, external suppliers provide access to a wider range of parts and economies of scale but can lead to dependence on external factors like lead times and minimum order quantities. Companies often navigate this by adopting a hybrid approach, leveraging in-house capabilities for specific parts while partnering with reliable external suppliers for others. This approach allows them to optimize costs, manage lead times, and ensure access to the spare parts needed to keep their vessels operational. The optimal approach to manufacturing spare parts in the maritime industry is a topic of debate, with both centralized and distributed models offering distinct advantages [22]. Centralized manufacturing boasts economies of scale for high-volume parts and facilitates quality control [17]. However, this approach can lead to longer lead times and limited flexibility for geographically distant ships. Conversely, distributed manufacturing offers faster delivery times and increased responsiveness to regional needs but comes at the cost of higher infrastructure expenses and potential quality control challenges across multiple facilities [22]. In practice, many companies utilize a hybrid approach, leveraging centralized production for standardized parts and distributed facilities or even AM for urgent or low-volume items. This allows them to achieve a balance between cost efficiency, responsiveness, and supply chain resilience. Ultimately, the choice between centralized and distributed manufacturing hinges on a careful consideration of factors like part complexity, demand volume, technological advancements, and regulatory requirements.

In the maritime industry, efficient management of spare parts is critical to minimize vessel downtime and ensure operational profitability. A key element is knowing the optimal storage location for each spare part type. Manufacturers’ warehouses offer the widest range of parts at potentially lower costs, but lead times can be long. Strategically located regional warehouses provide faster access for critical parts within a specific region. Local warehouses near ports offer the fastest response times but have limited space, necessitating careful selection of frequently needed or long-lead-time parts [23]. Understanding these storage level advantages and disadvantages allows companies to optimize spare part availability. This translates to minimized downtime when repairs are needed, reduced costs associated with emergency deliveries, and efficient utilization of limited storage space, ultimately contributing to a more robust and cost-effective maritime supply chain.

By understanding the network connecting spare part manufacturers to vessels, stakeholders can make informed decisions to optimize the supply chain, ensuring efficient and timely repairs to keep vessels operational.

5. Modeling of the SPSC

5.1. Locations of the Warehouses in the Specific Supply Chain

The geographical locations of the spare part warehouses identified and examined in this research are

• The ship’s spare parts warehouse;
• The local (port’s) warehouse;
• The regional facility warehouse.

Research by [20] indicates that survey participants predominantly favored shipboard inventory as the most convenient location for spare parts, primarily due to the immediate availability for replacement and uninterrupted vessel operations. Local warehouses situated near ship routes were the second preference, relying on local distributors for part distribution. Regional warehouses operated by regional distributors followed, with central manufacturer warehouses as the least preferred option.

Therefore, based on stakeholders preferences [20], it was considered appropriate for research to simulate the two most preferred warehouses, that is, the ship’s warehouse and the local warehouse, as well as the one immediately preceding them in order of preference (the regional warehouse).

5.2. Choice of Spare Parts for the Study

When assessing suitable spare parts for 3D printing, respondents considered factors such as small size compatible with the printing process, low order quantities, infrequent demand, high value, complex design, and high supply risk, as identified by [20,24]. In addition, respondents showed interest in low-cost spare parts that again met the specified characteristics. They were also given the opportunity to themselves suggest the spare parts that they thought met the specified conditions.

Taking into account all of the above, two spare parts, one of high and one of low cost, were selected for further investigation for modeling after a thorough check. These are

• A semi-open pump impeller (impeller), and
• rubber fan gasket.

5.3. Modeling Assumptions

The model was constructed to simulate the movement of spare parts through the supply chain stages—onboard, in the port, and at regional facilities—for two specific components: a semi-open pump impeller and a rubber fan gasket. The primary objective was to contrast traditional inventory-based supply chains with a proposed 3D printing hub model utilizing AM. The system dynamics model incorporates inventory levels, production rates, lead times, and cost factors for both scenarios.

Key decision variables within the model include

Inventory levels: the quantity of spare parts stored at various warehouse locations (ship, port, regional warehouse).

Delivery time: the duration required to transport spare parts from different warehouses to the end user (ship) using the existing supply chain and AM methods.

AM production costs: expenses associated with producing spare parts using AM technology at the proposed 3D printing hubs.

AM production time: the difference between the times taken to manufacture the semi-open impeller (owing to unique AM processes) and the rubber fan gasket (which exhibited a shorter production time).

The model’s primary goal was to minimize total supply chain costs while optimizing delivery time. The objective function considers the following factors.

Total supply chain costs: In the traditional supply chain, the end user’s expense for a replacement part encompasses acquisition and shipping costs from the supplier and trader. Storage costs—including interest on invested capital, insurance, and potential depreciation—accumulate over time, elevating the overall cost. Conversely, in the proposed supply chain, the end user’s cost is determined by the AM spare part cost per 3D printing hub.

Delivery time: Reducing delays in delivering spare parts to the end user maintains operational efficiency.

6. Modeling the Current and Proposed Situation

The need for a replacement part may occur either because the predetermined stock has become too low before a scheduled maintenance or because of extraordinary wear and tear. The entire SPSC process is the responsibility of the respective manufacturer of the part, while the ordering process (Figure 2) is mostly based on the use of ERP (enterprise resource planning) of the respective information system. First, if a part needs replacement, the end user (ship) checks the ship’s warehouse inventory to locate it. In the event that the spare part is unavailable, a request is sent to the shore office so that the local distributor at the nearest port is notified to collect the required spare part from the respective (next) port warehouse to deliver it to the ship. Additionally, if this is also not possible, the request is sent to the regional distributor to be located in this case by the regional distributor from the regional warehouse. It is then shipped and delivered to the ship. Otherwise, if even this attempt to locate a spare part is not successful, the request is sent to the central warehouse so that the requested spare part can be located by the ship’s manufacturer, then shipped and delivered to the ship. From all the above, it is clear that in any case, the spare part is delivered back to the ship. If it is still out of stock in the central warehouse, it will be manufactured if there is an economic lot.

A proposed case explores (Figure 3) the impact of the application of the new AM technology on the shipping industry’s spare parts supply chain in terms of ship spare parts delivery. For this reason, a comparison of the existing state of the parts supply chain with the proposed digital chain was made using the necessary files to be sent encrypted to a suitable 3D printer located close to the point of demand of the AM end user.

A system dynamics simulation was used for the shipping network of the ship spare parts supply chain in order to model the problem under consideration, both for the existing situation and for the future with the introduction of the proposed technology. The software used for the simulation was the Vensim PLE tool, which is suitable for complex system dynamics algorithms. For this reason, after identifying the locations of the warehouses in the specific supply chain, the two most preferred by the parties involved were selected for further investigation, as presented in the previous section; these were the warehouse on the ship and at the port as well as the one immediately preceding them, i.e., the regional warehouse. In all these positions, the cost and delivery time of the distribution of the selected spare parts were studied.

In Figure 4 and Figure 5, simulations with the existing procedure of the regional warehouse are shown alongside the proposed procedure of the regional 3D printing hub. It is clear that the proposed procedure is far simpler than the existing one.

7. Simulation Results and Analysis

7.1. Assumptions of the Existing Procedure Simulation

Regarding the number of spare parts in the simulation, the supply chain was studied separately for two different and unique components: a semi-open impeller pump and an elastic fan gasket. The simulation model used for both examined components in the supply chain under existing conditions is the same. The case of a specific route is considered, where the demand components in both cases were assumed to be the same because the return to the end user (ship) followed the same route. The cost components were adjusted according to the costs of the respective parts that resulted from researching the relevant market prices. As for the simulation’s duration, the unit of time chosen was days. The initial time (initial time) was set to day 0, while the final time for all warehouses was 180 days (final time). The duration of time in the ship’s warehouse was set to 180 days until needed. For the case of the local (port) warehouse, the delay time was 72 days until needed. Finally, for the regional warehouse, the total delay time was 126 days until needed. The interest rate for spare parts in each warehouse was separately set at 2%. The total costs result from the exponential accumulation over time for each service.

7.2. Assumptions of the Proposed Procedure Simulation

In relation to the number of spare parts in the simulation for the proposed condition, the supply chain was studied, focusing on two components: a semi-open impeller pump and an elastic fan gasket.

The simulation model used for both examined components in the supply chain under the proposed condition is the same, with only the cost parameters changed. The duration was measured in days. The initial time (day 0) and the final time (5 days) were set for all warehouses. The construction time differs for the semi-open impeller due to a different AM method used in the port (local) and regional 3D printing hubs compared to the ship’s 3D printing hub.

The delivery time for both components was the same, except for the elastic fan gasket, which takes only 24 min for AM. The interest rate for spare parts in each 3D printing hub was separately set at 2%. The simulation did not include the costs of purchasing 3D printers and raw materials used for constructing the 3D-printed parts. The total cost results from the exponential accumulation over time for each service.

7.3. Comparison of Storage Cost between Existing and Proposed Procedures for the SPSC

Overproduction and an outdated inventory provoke drawbacks in the SPSC of the maritime sector. The usage of a 3D printing hub, which represents a digital inventory in parallel with the real-time production strategy, has a tremendous impact by significantly reducing storage requirements and related expenses. We conducted a comparison of storage costs between the existing and proposed procedures of the two examined objects from the maritime sector SPSC: the semi-open pump impeller and the rubber fan gasket; for this, we used the Vensim simulation formula. We then examined the cost of the final spare part to be delivered from the 3D printing hub in the examined case.

7.3.1. Comparison of Storage Costs between Existing and Proposed SPSC Procedures for the Semi-Open Pump Impeller

As far as the cost of the semi-open pump impeller from existing spare part storage warehouses versus the proposed 3D printing hubs is concerned, the analysis reveals the following. Transitioning from ship storage to ship 3D printing hub storage resulted in savings of EUR 660 per spare part. Transitioning from storage at a regional facility to storage at a regional 3D printing hub saved EUR -2294 per spare part. Last but not least, changing from port facility storage to port 3D printing hub storage saved EUR -2083 per spare part.

In evaluating all the storage cost comparisons across the examined cases for the semi-open pump impeller (

Table 2. Cost of storing a semi-open pump impeller in a warehouse versus in an AM hub.

Existing Warehouse Storage Cost	Total Proposed 3D Printing Hub Cost
Ship Warehouse	Total Ship
Storage Cost: EUR 1380/spare part	3D Printing Hub Cost: EUR
	720/spare part
Port Warehouse	Total Port
Storage Cost: EUR 732/spare part	3D Printing Hub Cost: EUR
	2815/spare part
Regional Warehouse	Total Regional Warehouse
Storage Cost: EUR 1056/spare part	3D Printing Hub Cost:
	EUR 3350/spare part

), the proposed ship’s 3D printing hub emerged as the preferable option (Figure 6). This conclusion arises from the difference in delivery times, assuming that the specific spare part will not be required by the ship for 180 days. Judging by the results of the research for the examined spare part, it is thought that the more the days a spare part stays as an unsold stock on warehouse shelves, the more the storage cost goes up.

7.3.2. Storage Cost Comparison between Existing and Proposed SPSC Procedure for the Rubber Fan Gasket

On the contrary, when comparing the cost of the rubber fan gasket between the existing spare part storage warehouses and proposed 3D printing hubs (

Table 3. Cost of storing a rubber fan gasket in a warehouse versus in an AM hub.

Existing Warehouse Storage Cost	Total Proposed 3D Printing Hub Cost
Ship Warehouse	Total Ship
Storage Cost: EUR 72/spare part	3D Printing Hub Cost:
	EUR 0.10/spare part
Port Warehouse	Total Port
Storage Cost: EUR 48.8/spare part	3D Printing Hub Cost:
	EUR 4/spare part
Regional Warehouse	Total Regional
Storage Cost: EUR 70.4/spare part	3D Printing Hub Cost:
	EUR 4.2/spare part

), our analysis revealed the following (Figure 7). Transitioning from ship storage to storage in a ship’s 3D printing hub resulted in cost savings of EUR 71.90 per spare part. Transitioning from storage at a regional warehouse to storage at a regional 3D printing hub resulted in cost savings of EUR 66 per spare part. Transitioning from storage at a port facility to storage at a port 3D printing hub resulted in cost savings amounting to EUR 45 per spare part.

Overall, across all examined cases, the selected 3D printing hubs consistently yielded savings on the storage of the rubber fan gasket. This conclusion arises from the AM speed for the specific spare part and the improved delivery time for all scenarios.

7.4. Comparison of Total Costs between Existing and SPSC Comparison Procedures

The existing total cost for both spare parts is affected by parameters other than warehouse storage cost in every examined case, such as trader’s cost, supplier’s cost, etc., as shown by the Vensim PLE tool’s simulation formula. The total proposed 3D printing hub cost in every examined case is the same as that used in the comparison with warehouse storage cost, because the cost of the final spare part to be delivered is examined.

7.4.1. Comparison of Total Costs between Existing and Proposed SPSC Procedures for the Semi-Open Pump Impeller

In comparing the total cost of the semi-open pump impeller between existing spare part warehouses and the proposed 3D printing hubs (

Table 4. Comparison of total costs for the semi-open pump impeller between the warehouse and AM hub.

Total Existing Cost	Total Proposed 3D Printing Hub Cost
Total Ship	Total Ship
Warehouse Cost: EUR 1680/spare part	3D Printing Hub Cost: EUR 720/spare part
Total Port	Total Port
Warehouse Cost: EUR 2982/spare part	3D Printing Hub Cost: EUR 2815/spare part
Total Regional	Total Regional
Warehouse Cost: EUR 3985/spare part	3D Printing Hub Cost: EUR 3350/spare part

), we can make the following conclusions. To begin with, the greatest cost savings were observed in the transition from the ship’s warehouse to the ship’s 3D printing hub, which resulted in savings of EUR 960/spare part. Following this, the transition from the regional warehouse facility to the regional 3D printing hub achieved savings of EUR 635/spare part. Lastly, the Port’s Warehouse, transitioning to the Port’s 3D Printing Hub, shows a cost savings of 167 EUR/spare part.

Evaluating all the total cost comparisons across the examined cases for the semi-open pump impeller, the proposed 3D printing hubs are the preferable option (Figure 8).

7.4.2. Comparison of Total Costs between Existing and Proposed SPSC Procedures for the Rubber Fan Gasket

Comparing the total costs of a rubber fan gasket in an existing spare part warehouse with the cost of one in a proposed 3D printing hub (

Table 5. Comparison of total costs for the rubber fan gasket between the warehouse and AM hub.

Total Existing Cost	Total Proposed 3D Printing Hub Cost
Total Ship	Total Ship
Warehouse Cost: EUR 92/spare part	3D Printing Hub Cost: EUR 0.1/spare part
Total Port	Total Port
Warehouse Cost: EUR 173.2/spare part	3D Printing Hub Cost: EUR 4/spare part
Total Regional	Total Regional
Warehouse Cost: EUR 293.6/spare part	3D Printing Hub Cost: EUR 4.2/spare part

), we found significant cost savings. The transition to the ship’s 3D printing hub resulted in a substantial savings of EUR 92 per spare part.

Converting to the regional 3D printing hub yielded even greater savings of EUR 28,4 per spare part. Transitioning to the port’s 3D printing hub led to savings of EUR 169 per spare part.

Evaluating all the total cost comparisons across the examined cases for the rubber fan gasket, it is evident that the proposed 3D printing hubs are the preferable option in all cases (Figure 9).

7.5. Delivery Time Comparison between Existing and Proposed Procedure SPSC

In comparison delivery times between the existing spare part warehouse and the proposed 3D printing hub, delivery time savings were judged from the time from which the two examined spare parts were required by the end user (i.e., the ship) until they were delivered to the ship, as determined by the Vensim PLE tool’s simulation formula. To find the total end user delivery time using AM, the total end user’s delivery time—not the 3D printing production time—was used. Only the total ship end user delivery time using AM was differentiated, because 3D printing production time was used in this case.

7.5.1. Comparison of Delivery Time between Existing and Proposed SPSC Procedures for the Semi-Open Pump Impeller

In comparing delivery times between the existing spare part warehouse and the proposed 3D printing hub for the semi-open pump impeller, we found the following results (

Table 6. Comparison of delivery times for the semi-open pump impeller between the warehouse and AM hub.

Warehouse Delivery Time	AM Delivery Time
Total Ship Delivery Time	Total Ship End User Delivery Time
of the End User: 180 days	using AM: 0.3 days
Total Port Delivery Time	Total Port End User Delivery Time
of the End User: 72 days	using AM: 3.5 days
Total Regional Delivery Time	Total Regional Delivery Time
of the End User: 126 days	using AM: 5 days

). The greatest delivery time savings were achieved with the transition from the ship warehouse to the ship 3D printing hub, resulting in a reduction of almost 180 days in delivery time. This was followed by the transition from the regional warehouse facility to the regional 3D printing hub, which saved 68.5 days. Lastly, the transition from the port warehouse to the port 3D printing hub resulted in a saving of 121 days of delivery time (Figure 10).

Considering the tremendous savings made on total end user delivery time, which resulted from the proposed 3D printing hubs using AM, across all examined cases, such hubs are indisputably the preferable option. A semi-open pump impeller made by AM could be ready for use after only a few hours on the same day that it is requested.

7.5.2. Comparison of Delivery Time between Existing and Proposed SPSC Procedures for the Rubber Fan Gasket

As for the Delivery time Comparison between the Existing and Proposed Spare Part Warehouse and 3D Printing Hub for the Rubber Fan Gasket, the findings are as follows: The greatest delivery time savings are achieved with the transition from the Ship’s Warehouse to the Ship’s 3D Printing Hub, resulting in a reduction of almost 180 days in delivery time. This is followed by the Regional warehouse facility transitioning to the regional facility 3D printing hub, which saves 68.5 days. Lastly, the Port’s Warehouse transitioning to the Port’s 3D Printing Hub shows a delivery time saving of 121 days. (

Table 7. Comparison between warehouse delivery times and AM delivery times for the rubber fan gasket.

Warehouse Delivery Time	AM Delivery Time
Total Ship Delivery Time	Total Ship End User Delivery Time
of the End User: 180 days	using AM: 0.02 days
Total Port Delivery Time	Total Port End User Delivery Time
of the End User: 72 days	using AM: 3.5 days
Total Regional Delivery Time	Total Regional Delivery Time
of the End User: 126 days	using AM: 5 days

).

Once again, the proposed 3D printing hubs using AM resulted in tremendous savings on total end user delivery time across all examined cases, so they are indisputably the preferable option. A rubber fan gasket made by AM could be ready for use after only a few minutes on the same day that it is requested (Figure 11).

8. Discussion

The system dynamics simulation using Vensim PLE successfully compared traditional and digital supply chains for ship spare parts, shedding light on significant operational improvements that are achievable through the integration of AM. By evaluating two distinct spare parts—a high-cost semi-open pump impeller and a low-cost rubber fan gasket—the study provides robust insights into the cost-effectiveness and time efficiency of transitioning from conventional storage systems to AM-based solutions.

The simulation’s results indicate that incorporating 3D printing hubs leads to a substantial reduction in total costs. For the semi-open pump impeller, the ship’s 3D printing hub demonstrated the greatest savings compared to traditional storage warehouses, reducing costs by approximately EUR 960 per spare part. The regional facility and Port 3D printing hubs also led to cost reductions, although these savings were less pronounced compared to the ship hub. This study highlights that the cost advantages of AM are most evident in scenarios in which the spare part remains unsold or unused for extended periods, which significantly drives up traditional storage costs.

Conversely, for the rubber fan gasket, while the cost savings were smaller due to its lower value, AM still proved beneficial. The cost savings were consistent across all hub types, driven primarily by reduced storage costs and the rapid production capabilities of AM. The transition to AM offers a clear economic advantage, particularly for parts with shorter storage periods, where traditional storage costs would otherwise remain relatively low.

The study’s findings underscore the dramatic improvements in delivery times with AM. For both spare parts, the transition from traditional storage to AM-based production offers time savings of up to 180 days. This is particularly significant in the maritime sector, where delays in the availability of parts can result in costly operational downtime. The ship’s 3D printing hub emerged as the optimal solution, enabling same-day production and delivery, ensuring that critical spare parts can be ready within hours or even minutes.

The regional and port hubs also exhibited significant improvements in delivery time, albeit to a lesser extent than the ship hub. This time advantage not only minimizes downtime but also enhances operational agility, a key benefit in the dynamic maritime environment. The ability to produce parts on demand using AM eliminates the need for extensive pre-emptive stocking, hereby reducing the risk of holding obsolete or overproduced inventory.

The integration of AM technology into the maritime spare parts supply chain offers more than just cost and time efficiencies; it represents a strategic shift towards more flexible, resilient, and sustainable operations. By localizing production through 3D printing hubs, the industry can significantly reduce its reliance on complex, multi-tiered supply chains, thereby mitigating risks associated with long lead times, supply chain disruptions, and inventory mismanagement.

Moreover, the study’s findings indicate that AM’s advantages are not limited to high-value components like the semi-open pump impeller but extend to lower-cost parts such as the rubber fan gasket. This suggests that the maritime industry can achieve widespread benefits from adopting AM, regardless of a given part’s economic value. As such, AM offers a scalable solution capable of transforming both high-volume and niche component supply chains.

9. Conclusions

This study effectively demonstrates the substantial benefits of integrating AM technology into the maritime SPSC through the use of system dynamics simulation with Vensim PLE. By comparing traditional and digital supply chain models, focusing on a high-value spare part like a semi-open pump impeller and a low-value one like a rubber fan gasket, the analysis revealed significant advantages in terms of financial savings, reduced inventory, and faster delivery when using the proposed AM hubs.

The results clearly indicate that the introduction of 3D printing hubs at various locations (onboard, in the port, and in regional facilities) significantly improves conventional warehouse-based supply chains. The ship’s 3D printing hub emerged as the most advantageous option, consistently offering substantial cost reductions by minimizing storage costs associated with overproduction and obsolete inventory. Moreover, the proposed AM model ensured remarkable time savings, allowing spare parts to be produced and delivered within hours of being needed, thereby reducing operational downtime.

The research emphasizes the transformative potential of AM in the maritime sector. For both high-cost and low-cost components, the proposed digital supply chain model provides a scalable solution for optimizing logistics, reducing expenses, and enhancing the overall efficiency of spare parts’ management. The study underscores the viability of shifting towards AM-driven supply chains, particularly in scenarios in which time-critical delivery and flexibility are crucial.

However, it is essential to acknowledge the limitations of this study. Our focus on two specific spare parts may not fully represent the complexity of the entire spare parts portfolio. Additionally, this study did not delve into the environmental impact of AM, which is a growing concern in the maritime industry. Future research should explore these areas to gain a more comprehensive understanding of AM’s potential and challenges in the maritime context.

In conclusion, adopting 3D printing hubs in maritime supply chains presents a forward-looking strategy that can drive substantial improvements in operational efficiency, cost-effectiveness, and delivery in the industry. While this study provides compelling evidence of the benefits of AM, further research is necessary to fully realize its potential and address potential challenges. By building upon the findings of this study, the maritime industry can embark on a path towards a more sustainable, efficient, and resilient spare parts supply chain.