## 2 Results of Literature Analysis
### Content Analysis
#### 2.2.2 Process
[PERSON] [62] compared the manufacturing of components with conventional manufacturing and AM using a lifecycle cost model. The author found that AM is more beneficial in after-sales service logistics. Break-even characteristics allow the OEM to decide which design option to adopt in the early design process. [PERSON] et al. [10] suggested a scoring methodology that identifies eligible spare parts for AM. The authors' methodology helps to increase the effectiveness and efficiency of selecting promising facilities for after-sales service logistics. Similarly, [PERSON] et al. [51] designed a web-based software tool to select a suitable 3D printer service provider. The tool provides an AM feasibility assessment to identify the components that can be manufactured through AM. Supporting the decision-making process in aerospace MRO activities, [PERSON] [59] developed a decision tool that calculates the expected cost of AM, conventional technology, and the procurement of a new part from the original equipment manufacturer. The tool can support decision-making when adopting a manufacturing strategy. The proposed multi-attribute decision analysis model considered the cost, time, and quality of the technology. Another decision support tool was proposed to assist decision makers in the selection of the right AM technology class and material in a remote manufacturing environment [60]. Each of the processes, machines, parts, material, environment, and logistics objectives and constraints were identified and used in decision support. The review shows that researchers considered analytical tools to help the industry select conventional manufacturing and AM. Additionally, for AM, decisions on capacity, allocation of AM facilities, and demand-based manufacturing strategies were also considered. * _Maintenance Strategy_ [PERSON] [3] suggested a process-based model to study the viability of AM in maintenance activities. The developed model and costing approaches included three stages: design, manufacturing, and warehouse management. The author highlighted the importance of the potential of AM in reducing maintenance costs and extending machine lifetimes. [PERSON] [56] applied a sustainable procedure model for aircraft maintenance. The authors studied the impact of shifting from traditional maintenance, repair, and overhaul activities to AM. The authors showed that from the point of view of maintenance, the adoption of distributed manufacturing of spare parts unlocks the opportunity for spare weight optimization. Moreover, it reduces the transportation of parts, raw material consumption, and fuel savings during aircraft operation. [PERSON] et al. [37] used a hybrid simulation model to compare SC configurations to assess the effect of additive manufacturing capabilities on improvements in operational efficiency and maintenance effectiveness. However, they did not take into consideration the resource management aspect of maintenance operations, such as maintenance equipment and maintenance technicians, which will allow more rational decision-making in manufacturing resource deployment. [PERSON] et al. [54] demonstrated that the use of AM in maintenance supports both preventive maintenance and corrective maintenance strategies. The adoption of AM would provide agility and positively affect lead times associated with the replenishment of spare parts. The review shows that researchers have shown that the choice of AM can also be based on the maintenance strategy and that lead time, service effectiveness, and agility can be some of the aspects that can favor AM. However, one must remember that if the company adopts a safety-stock-based policy, lead time, service effectiveness, and agility in maintenance could be much better. Therefore, a maintenance strategy should be considered along with the total system cost of adopting AM or adopting conventional manufacturing with an inventory. * _Analysis Methods_ The following section presents the analysis methods and available quantitative models for analyzing AM in SC.