| dc.description.abstract | Spare parts are strategic assets to ensure the execution of maintenance activities in industrial plants. They are exchangeable parts that can be used to replace damaged components, facilitating the restoration of the functioning of plants and equipment (Huiskonen, 2001; Tapia-Ubeda et al., 2020). Due to the significant role of spare parts, the scientific literature (Frazzon et al., 2016) has emphasized how crucial it is for spare parts retailers to ensure efficient supply chains (SCs), where the right spare parts are stored and delivered in the right place (close to the damaged plant or equipment) at the right time (breakdown time). Aligning spare parts deployment and delivery activities with customer needs leads to customer satisfaction, increased sales profits, greater sustainability, and efficient company performance (Giannikas et al., 2019). Based on this, a well-configured spare parts SC has been recognised as an ever-growing crucial aspect for the success and competitiveness of spare parts retailers (Esmaeili et al., 2021).
Among the decisions that impact the configuration of spare parts SCs, stock deployment is of primary importance (Gregersen and Hansen, 2018). Antithetical stock deployment policies can be selected, such as inventory centralisation, decentralisation, or hybrid stock deployment policies, which imply countervailing advantages in terms of SC flexibility and responsiveness, delivery time, inventory levels, mitigation of demand uncertainty, facility management efforts, and number of supply orders to replenish distribution centres (DCs). Due to the opposite advantages of inventory centralisation and decentralisation and the typical volatility of spare parts demand, determining optimal stock deployment policies has been recognised as a challenging task worldwide (Basto et al., 2019; Vlajic et al., 2012), where the main issue is to minimise inventory costs while guaranteeing high service levels (Jiang et al., 2019). In the case of spare parts, the optimisation of stock deployment policies and the consequent configuration of SCs are further hampered by two main issues. First, the optimal stock deployment policies of spare parts should not be defined only once (when the business is founded) but should be regularly reviewed during the business lifetime, adapting to fluctuations in customer needs and spare parts criticality and, consequently, reviewing the SC configuration (Alfieri et al., 2017; Del Prete and Primo, 2021). Second, the optimal manufacturing technology should be selected for each stock keeping unit (SKU), opting for conventional (CM) or additive manufacturing (AM), where AM is considered the next revolution in the field of spare parts, allowing to disrupt the choice between inventory centralisation and decentralisation (Xu et al., 2021).
Despite the achievable benefits of optimising the configuration of spare parts SCs, the choice between inventory centralisation and decentralisation is not the subject of much scientific research. It is also unclear what the optimal manufacturing technology is for spare parts (CM or AM) and how different manufacturing technologies impact the choice of optimal stock deployment policies (Frandsen et al., 2020; Trancoso et al., 2018). Moreover, the scientific literature has recently underlined the lack of structured methodologies (especially heuristic ones) to review the configuration of spare parts SCs, aligning stock deployment policies and spare parts manufacturing technology to demand fluctuations (Eldem et al., 2022). In this context, the present research aims to fill this gap by supporting and creating new knowledge for researchers and practitioners (spare parts retailers) on how to review the configuration of spare parts SCs, focusing on optimising the stock deployment policies and manufacturing technology of spare parts. To this end, we began the current research by developing a systematic literature network analysis (SLNA) on the topic of spare parts deployment in SC configuration and the choice between inventory centralisation and decentralisation. The SLNA combines a typical systematic literature review (SLR) with an analysis of quantitative information emerging from bibliographic networks. Therefore, the SLNA allowed us to understand the extant body of knowledge in the analysed domain, confirming the aforementioned literature gaps, laying the foundation for future research investigations, and providing an answer to the following research question.
• RQ1: What are the extant literature and driving research streams on the topic of stock deployment in spare parts SCs?
Based on the identified literature gap and future research opportunities, two additional research questions were derived:
• RQ2: What viable heuristic methodologies can be proposed to review stock deployment policies in spare parts SCs?
• RQ3: What is the optimal manufacturing technology for spare parts in SCs with different stock deployment policies?
To answer the above research questions, the following research methods were applied:
• RQ1: SLNA
• RQ2: mathematical modelling, case study research, and experimental research
• RQ3: mathematical modelling and experimental research By answering each research question, the following outcomes were achieved:
• RQ1: An SLNA of the scientific literature on the topic of inventory centralisation/decentralisation and stock deployment in spare parts SCs:
- Identification of the extant literature on the analysed topic;
- Investigation of past and current research themes related to the considered topic, determining the driving research streams, which mainly concur in developing the literature on this field.
• RQ2 and RQ3: Three novel heuristic methodologies for reviewing the configuration of spare parts SCs:
- Proposal of a data-driven heuristic methodology (based on a multicriteria ABC criticality classification) to review the stock deployment policies in spare parts SCs without considering the spare parts manufacturing technology (answers RQ2);
- Proposal of a DSS to compare the cost-effectiveness of centralised and decentralised SCs, where spare parts can be purchased from suppliers as AM or CM parts and the optimal manufacturing technology is selected (answers both RQ2 and RQ3);
- Proposal of a DSS to compare the cost-effectiveness of centralised and decentralised SCs, where spare parts can be purchased from suppliers as CM parts or produced inhouse as AM parts and the optimal manufacturing technology is selected (answers both RQ2 and RQ3);
Overall, the main goal of this research work was achieved by providing support and new knowledge to researchers and practitioners (spare parts retailers) on how to review the configuration of spare parts SCs, focusing on optimising stock deployment policies and spare parts manufacturing technologies. Specifically, the answer to RQ1 highlights the current body of knowledge in the analysed domain, remarking on possible research opportunities. Then, the answers to RQ2 and RQ3 provide spare parts retailers with heuristic methodologies and DSSs to recurrently review the configuration of spare parts SCs, defining the optimal stock deployment policies with AM or CM spare parts. | en_US |
