The advent of Industry 4.0 [1] has spurred a surge of interest in digital transformation across various manufacturing sectors and the advancement to Industry 5.0 is going beyond including in the technologies deployment also the impact on people in line with human centric approach [2]. Industry 4.0, characterized by the integration of digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), and cloud computing, is revolutionizing the manufacturing landscape [3,4]. Small and medium-sized enterprises (SMEs) in the construction industry, often constrained by limited resources, are increasingly recognizing the potential of digital transformation to enhance their competitiveness, efficiency, and sustainability [5]. The implementation of digital tools and processes is demonstrating to streamline operations, reduce costs, improve quality, and enable data-driven decision-making [6,7,8]. Also in construction sector the interest in digital technologies is growing every year, but their penetration into the construction industry is currently slow and limited [9]. The reasons are multiple including a lack of awareness and understanding of the technologies, high implementation costs, and concerns about data security. Furthermore, the industry's fragmented nature, traditional practices, and resistance to change often create barriers to digital transformation in the construction industry. However, in the last years, the integration of Industry 4.0 technologies, such as Building Information Modeling (BIM), Internet of Things (IoT), and Artificial Intelligence (AI), has been demonstrating to offer significant opportunities for construction companies. These technologies can streamline processes, enhance collaboration, and enable data-driven decision-making, leading to improved efficiency, reduced waste, and safer working environments. While challenges exist, the potential benefits of embracing digitalization and adapting to a "Construction 4.0" mindset are immense, promising a more sustainable, efficient, and innovative future for the construction industry.

This slow, but inexorable introduction of industry 4.0’s technologies in the construction industry can be particularly relevant for companies focused on manufacturing building components, and for the manufacturing of customized prefabricated building products. These manufacturers challenge the as usual critical aspects [10], but also the complexity due of engineer-to-order (ETO) processes, where customization and rapid response to market demands are paramount. In this context, manufacturing companies realizing customized prefabricated building products within construction industry are challenging the adoption of the enabling technologies due to specificity of their market proposition focused on a by design product delivery, based on specific building project design and specification. The main difference between the ETO model and others in warehouse activities is due to the absence of a preexisting inventory. Indeed, traditional manufacturing companies have on-shell products manufactured based on selected materials: Make-to-Stock (MTS) model is based on forecasts of customer demand and are stored in inventory until ordered; Make-to-Order (MTO) model is based on product manufacturing after an order is received, but based on standard designs; Configure-to-Order (CTO) model is based on pre-defined options selectable by the customers who can choose from a set of to configure a product to their liking. On the opposite an ETO manufacturing is characterized by highly customized products and complex production processes, presenting unique challenges for optimization and efficiency of the inventory being the components and materials with a low replicability and high variability. These challenges are particularly evident in warehouse management, where the constant flux in logistic inbound, internal warehouse operations and logistic outbound of bespoke components and materials demands adaptable solutions. To manage this complexity, Digital Twin (DT) technology, a virtual replica of a physical asset or system, has already emerged as a promising tool for warehouse [11], and research analysis and implementation is addressing towards ETO challenges [12,13]. By integrating real-time data from IoT devices with BIM and AI, recent research has highlighted the potential of DTs in various industrial contexts, including manufacturing, construction, and logistics. Studies have demonstrated the benefits of DTs in streamlining production processes [14,15], improving supply chain visibility [12,16], and enhancing predictive maintenance [17,18]. However, the specific challenges of ETO manufacturing, such as high variability in product manufacturing and demand fluctuations, necessitate tailored DT solutions and open a space for deeper investigation. This is also interesting in the context of providing new software to improve the well-mature Warehouse Management System (WMS). Indeed, the DT development can evolve WMS through the integration of BIM information and IoT data in manufacturing, highlighting the potential for improved information management and collaboration in asset management as well in operations support [19,20]; in the same way, the integration of AI capabilities to analyze complex warehouse data and generate actionable insights remains a nascent area of research which can exploit the data set fusion guaranteed by DT deployment [10,11]. Additionally, the role of DTs in enhancing safety protocols within ETO warehouses has received limited attention. Despite the research conducted, DTs application in ETO environments remains relatively unexplored and this paper aims to contribute in this research field by presenting the activity for the understanding and design the DT implementation conducted within the IRIS project [21], research was funded by the European Union’s Horizon 2020 research and innovation program within the framework of the Change2Twin (C2T) [22] project’s cascade fundings (grant agreement No 951956). The DT for warehouse in ETO model is defined in the warehouse of Focchi S.p.A., an ETO manufacturer of high-technological prefabricated building envelopes. The project aims to develop a DT that leverages IoT, BIM, and AI to optimize warehouse operations and enhance worker safety. By analyzing Focchi's specific production processes and user requirements, this research seeks to uncover the opportunities and challenges associated with DT adoption in ETO manufacturing. The findings will inform the development of tailored DT solutions that can improve efficiency, safety, and ultimately business intelligence in warehouse management. The research evaluates how DTs can offer unprecedented visibility into warehouse operations, facilitating data-driven decision-making, process optimization, and risk mitigation to improve safety measures.

This section resumes the methods and materials adopted for the implementation of the research activities presented in this paper.

The methods are focused on the approach adopted for the DT definition with the following methodologies adopted:

The materials used for the IRIS digital twin design are:

The methodology presented above has been implemented with the following activities Interviews and Workshops: Gathered information from warehouse personnel to understand their daily tasks, challenges, and requirements for the digital twin.

The insights gained from these results can inform the development of tailored DT solutions for other ETO manufacturers, paving the way for a more agile, responsive, and competitive manufacturing landscape. The research conducted within the IRIS project focus on addressing the distinct challenges of engineer-to-order manufacturing in the context of warehouse management through a digital twin approach reveals several key findings with broader implications for the field. The implications of the research are methodological to define a common approach to support DT implementation in ETO business model as well as architectural to define a comprehensive vision of DT opportunities in this specific use case.

The initial analysis of Focchi's warehouse processes underscored the complexities inherent in ETO environments. The high degree of product customization and frequent changes in components lead to unique challenges in inventory management, communication, and overall efficiency. The role of ERP and production scheduling tool adopted is a key component for the warehouse optimization. Indeed, these softwares already have key data which can be integrated in DT to boost the collaboration among users as well as support the warehouse task organization and optimization in line with material and product in-house, order to be delivery and production time slot.

An analysis of the result and methodology replicable in similar use cases, reveals clearly some key steps for the design of the DT for ETO process. By tracking the implementation and evaluation of features based on user stories, this study contributes to the body of knowledge on the effectiveness of UCD methodologies in industrial settings supporting the adoption of I4.0 and I5.0 based on bottom-up approach. The development of user stories through a collaborative process with diverse stakeholders proved crucial for aligning the DT with the specific needs of the workforce in the ETO environment. This user-centric approach, advocated for in DT research, not only fosters acceptance of new technologies in early stage as demonstrated by the interactive process, but also ensures that the system delivers tangible benefits to those who interact with it daily. This is particularly relevant also for the collaborative approach to define with the users measurable and verifiable performance metrics. The KPIs identified in the user stories such as truck turnaround time, picking time, NCR due to loss, helps users to understand what they would like to achieve while providing a basis for quantitative assessment of the digital twin's impact on warehouse performance and to implement specific business intelligence active with the data interoperated within the DT.

Another result is that analyzing the user stories by user group can reveal patterns in requirements and priorities, highlighting the unique needs of different stakeholders. It appears that for all the users groups the KPIs are more oriented to optimization and efficiency (19 of 26 user stories, 73%) to avoid time consuming activities and inefficiency while safety KPIs for measure prevention and control have a minor relevance for the current organization (7 of 26 user stories, 27%).

A further interesting analysis, not conducted out of the scope of the research, is related to the prioritization of user requirements and consequently the technical ones. The user stories can be used to prioritize the development of specific technical features within the digital twin based on their potential impact on user satisfaction and overall warehouse performance. To this activity the involvement also of middle and top management to have an alignment between DT and business strategy based on performance productivity or certification acquisition or other strategic parameters is a key step. Indeed, this KPIs monitoring in DT helps also to be aligned with the company activities along the project delivery such as quality control – goal is to ensures that all prefabricated building envelopes meet the highest quality standard – and the company project management for the production activities – goal is to deliver on time prefabricated façade in line with projects milestones. Additionally, the adoption of KPIs has emerged to be aligned with opportunities of certification improvement to guarantee quality control and track improvement year by year in the already achieved certifications as ISO 9001 to assess and improve the quality management system, ISO 14001 to assess and improve the environmental management system, ISO 45001 to assess and improve the safety management system.

Processes and user identification presented in the results will help also to address further platform implementation at the differ stage, defining User Interfaces (UI) and User Experience (UX) related to specific tasks and requirement defined by the users. The implementation of this UI is not in the scope of the present paper, and it will be analyzed during platform implementation.

The integration of BIM, IoT, and AI within the DT architecture confirms the novelty of the approach to warehouse management to support the integration of BIM and IoT in manufacturing with the incorporation of AI algorithms for real-time analysis and decision-making is a distinct advancement. The potential for AI to optimize warehouse layouts, predict production line needs, and enhance safety protocols aligns with the broader vision of Industry 4.0.

Although preliminary testing results are not yet available, the findings suggest that DT technology can effectively address the unique challenges of ETO manufacturing by providing a comprehensive, data-driven platform for warehouse management. The ability to visualize complex processes, track assets in real time, and generate actionable insights has the potential to transform the efficiency and safety of ETO warehouses.

The IRIS project offers a compelling framework for leveraging DT technology to address the complex challenges inherent in Engineer-to-Order manufacturing. By integrating IoT, BIM, and AI capabilities, the DT architecture can support warehouse management in customized prefabricated building product manufacturers as in the case of Focchi S.p.A., creating a more efficient, safe, and data-driven environment. The DT architecture design serves as a practical blueprint for the implementation of digital twin technology in ETO manufacturing environments. By integrating IoT, BIM, and AI, the DT appears to offer a comprehensive solution for optimizing warehouse operations, enhancing worker safety, and streamlining complex workflows. The project's findings can be directly applied to similar manufacturing contexts where customization and rapid response to construction site demands are comparable. The developed framework, encompassing data collection, analysis, and visualization, can be adapted to various warehouse layouts and production processes. The focus on user-centric design ensures that the resulting DT is intuitive and user-friendly, promoting widespread adoption and maximizing the benefits of digital transformation. Moreover, the research’s emphasis on safety protocols and risk mitigation strategies can serve as a model for other industries seeking to improve workplace safety with digital technologies. A key remark is that this research underscores the importance of a user-centric approach in DT design, as exemplified by the meticulous collection of user stories and requirements. By tailoring the DT to the specific needs of warehouse personnel, the research demonstrates the potential for technology to empower workers and improve their daily experiences.

While implementation of DT architecture is ongoing and consequently testing activities, the design and development phases of DT for ETO manufacturers have highlighted the transformative potential of digital twin. The integration of real-time data, 3D visualization, and AI-powered analytics can unlock new levels of efficiency, optimize resource utilization, and enhance safety protocols. However, the design validation should be confirmed with DT implementation focusing on rigorously quantifying its impact on key warehouse KPIs defined with the users. This will provide concrete evidence of the DT's efficacy in ETO environments. This demonstration will serve to demonstrate design methodology effectiveness for DT implementation in specific ETO context. Further research should investigate the scalability and adaptability of this approach to other industries and manufacturing models, potentially leading to standardized DT frameworks for broader adoption. This validation is even more interesting considering the understanding of the impact of the DT on worker behavior and decision-making, crucial for long-term success. Future studies should investigate the human-machine interaction aspects of DT implementation, ensuring that the technology complements and empowers the workforce.

Overall, the DT integrating AI and IoT in ETO environment can represent a significant step forward in the application of digital technologies. By addressing the unique challenges of this market segment, the research offers some insights for both researchers and industry practitioners seeking to leverage digital transformation for increased competitiveness and improved operational outcomes.