There is an increasing need for supply chains that can rapidly respond to fluctuating demands and can provide customised products. This supply chain design requires the development of flexibility as a critical capability. To this end, firms are considering Additive Manufacturing (AM) as one strategic option that could enable such a capability. This paper develops a conceptual model that maps AM characteristics relevant to flexibility against key market disruption scenarios. Following the development of this model, a case study is undertaken to indicate the impact of adopting AM on supply chain flexibility from four major flexibility-related aspects: volume, mix, delivery, and new product introduction. An inter-process comparison is implemented in this case study using data collected from a manufacturing company that produces pipe fittings using Injection Moulding (IM). The supply chain employing IM in this case study shows greater volume and delivery flexibility levels (i.e., 65.68% and 92.8% for IM compared to 58.70% and 75.35% for AM, respectively) while the AM supply chain shows greater mix and new product introduction flexibility, indicated by the lower changeover time and cost of new product introduction to the system (i.e., 0.33 h and €0 for AM compared to 4.91 h and €30,000 for IM, respectively). This work will allow decision-makers to take timely decisions by providing useful information on the effect of AM adoption on supply chain flexibility in different sudden disruption scenarios such as demand uncertainty, demand variability, lead-time compression and product variety.

The aerospace industry faces challenges in managing inventory effectively due to long product life cycles and unpredictable demand. Additive Manufacturing (AM) is a promising technology that enables the on-demand production of spare parts, potentially reducing inventory costs and improving supply chain efficiency. This paper proposes a novel conceptual framework for employing AM in the aerospace spare parts industry to isolate demand volatility. A conceptual approach is employed in this study, which involves a comprehensive literature review to identify the factors to consider when employing AM for spare parts and the methods for demand volatility isolation, followed by a structured framework development that outlines the decision-making steps for AM utilization based on the identified factors. The framework outlines a structured approach for using AM to produce spare parts and isolate demand volatility, which can help mitigate the impact of demand uncertainty on inventory management. The proposed approach provides a basis for future research and has the potential to transform how spare parts are produced and managed in the aerospace industry. Overall, this paper contributes to the emerging literature on AM in the aerospace industry by presenting a novel approach to improving inventory management and addressing demand uncertainty.

To err is an intrinsic human trait, which means that human errors, at some point, are inevitable. Business improvement tools and practices neglect to deal with the root causes of human error; hence, they ignore certain design considerations that could possibly prevent or minimise such errors from occurring. Recognising this gap, this paper seeks to conceptualise a model that incorporates cognitive science literature based on a mistake-proofing concept, thereby offering a deeper, more profound level of human error analysis. An exploratory case study involving an aerospace assembly line was conducted to gain insights into the model developed. The findings of the case study revealed four different causes of human errors, as follows: (i) description similarity error, (ii) capture errors, (iii) memory lapse errors, and (iv) interruptions. Based on this analysis, error-proofing measures have been proposed accordingly. This paper lays the foundation for future work on the psychology behind human errors in the aerospace industry and highlights the importance of understanding human errors to avoid quality issues and rework in production settings, where labour input is of paramount importance.

Metal Additive Manufacturing (MAM) has emerged as a promising technology in the aerospace industry, enabling the production of complex components with enhanced design flexibility and reduced lead times. Concurrently, Industry 4.0 has gained significant attention for its potential to revolutionize aerospace manufacturing processes. The 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 for the chief purpose of matching supply with demand. Identified gaps and challenges are analyzed, highlighting the need for further research and outlining research agenda aimed at advancing the integration of MAM for Industry 4.0 in the aerospace sector. By addressing these research areas, the aerospace industry can unlock the value of MAM within an Industry 4.0 framework, leading to improved efficiency, productivity, and competitiveness.