Additive manufacturing (AM) is a group of technologies that create objects by adding material layer upon layer, in precise geometric shapes. They are amongst the most disruptive technologies nowadays, potentially changing value chains from the design process to the end-of-life, providing significant advantages over traditional manufacturing processes in terms of flexibility in design and production and waste minimization. Nevertheless, sustainability assessment should also be included in the research agenda as these technologies affect the People, the Planet and the Profit: the three-bottom line (3BL) assessment framework. Moreover, AM sustainability depends on each product and context that strengthens the need for its assessment through the 3BL framework. This paper explores the literature on AM sustainability, and the results are mapped in a framework aiming to support comprehensive assessments of the AM impacts in the 3BL dimensions by companies and researchers. To sustain the coherence of boundaries, three life cycle methods are proposed, each one for a specific dimension of the 3BL analysis, and two illustrative case studies are shown to exemplify the model.

The topic of sustainable business models is growing in literature and in the industry, driving companies to search for opportunities to improve their impact on the three pillars of sustainability—profit, people, and planet (economic, social, and environmental). However, the process of developing sustainable business models is often complex, due to conflicting objectives from the three dimensions of sustainability. This paper presents a procedure model that supports the design and assessment of business models with a sustainable perspective, by integrating a new business model canvas for sustainability (BMCS) and an evaluation method to assess it. A comprehensive assessment is proposed, performed in a life cycle perspective. The proposed model is applied and validated with a real case study, based on a new business model for an aircraft maintenance, repair, and overhaul company. The case is based on shifting from traditional maintenance, repair, and overhaul activities to adopting additive manufacturing as an activity that allows manufacturing optimized spare parts with benefits for the costumer. The results show the application of the procedure model on a specific case study, as well as the potential of additive manufacturing as a driver for more sustainable business models in the aircraft maintenance sector.

Purpose: This paper studies the potential of additive manufacturing (AM) as a strategy for optimizing spare parts supply chains in continuous process industries. It explores how AM impacts traditional supply chain practices, particularly in relation to inventory levels, lead times and purchasing costs. As a secondary objective, it seeks to validate or challenge common assumptions regarding AM’s capacity to eliminate the need for physical spare parts inventory. Design/methodology/approach: The research adopts an inductive single-case study approach, grounded in real-world data from a large-scale paper and pulp manufacturer. Quantitative analysis is conducted using comprehensive stock keeping unit (SKU)-level warehouse and purchasing data, which is processed through an existing AM classification model to identify parts with theoretical potential for AM. In addition, qualitative data from unstructured interviews with maintenance and supply chain personnel are used to contextualize, adjust the model and critically evaluate the results. Findings: The results reveal that while AM shows significant promise for reducing purchasing and inventory costs, its actual applicability is limited to a very small fraction of spare parts (approximately 1% of all SKUs analysed). Despite the limited application range, in large warehouses this may represent high saving potential for companies. The classification model successfully identified these parts with potential gains when produced with AM technologies. From a supply chain perspective, the findings indicate that having local networks of AM suppliers is key to unlock its potential. Practical implications: The paper offers guidance for operations and supply chain managers considering AM adoption in spare parts logistics. Rather than pursuing broad AM integration strategies, companies should focus on conducting structured, data-driven assessments to identify the small percentage of SKUs that can benefit from AM. Originality/value: This study contributes to existing literature by introducing an empirical evaluation of AM’s impact on spare parts logistics in a continuous process industry context, using actual industrial data. It challenges overly optimistic assumptions in existing literature and validates a replicable methodology for part classification and cost analysis based on widely available warehouse and purchasing data. By bridging theory and practice, the paper offers actionable insights into the strategic value of AM in complex, high-asset environments and lays the groundwork for further research on digital supply chains and selective AM implementation.

An overview of the work under development within the EU-funded collaborative project MAESTRI is presented in this chapter. The project provides a framework of new Industrial methodology, integrating several tools and methods, to help industries facing the fourth industrial revolution. This concept, called the MAESTRI Total Efficiency Framework (MTEF), aims to advance the sustainability of manufacturing and process industries by providing a management system in the form of a flexible and scalable platform and methodology. The MTEF is based on four pillars: a) an effective management system targeted at continuous process improvement; b) Efficiency assessment tools to support improvements, optimization strategies and decision-making support; c) Industrial Symbiosis paradigm to gain value from waste and energy exchange; d) an Internet-of-Things infrastructure to support easy integration and data exchange among shop-floor, business systems and MAESTRI tools.