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Digital transformation is complicated in International Manufacturing Networks (IMNs), where factories are spread globally, and actions are interdependent. Adapting organizational structures is one way to handle the demands and expectations posed by digital transformation. However, research covering the adaptations to the IT organization is limited, and this paper's purpose is to explore adaptations of IT organizations within IMNs during digital transformation. A multiple case study was performed, studying two manufacturing companies’ adaptations of the IT organization. The result reveals three phases of adaptations of the IT organization: the foundation phase, the mapping phase, and the coordinating phase. The phases are accompanied by the setup of a new operational IT function that works with digital transformation in the IMNs. Also, the interfaces and collaboration between the operational IT function and the factories in the IMNs are identified. Lastly, it highlights remaining challenges with the adaptations of the IT organization that need further research. 

PurposeThe purpose of this paper is to advance the understanding of paradoxes, underlying tensions and potential management strategies when integrating digital technologies into existing lean-based production systems (LPSs), with the aim of achieving synergies and fostering the development of production systems.Design/methodology/approachThis study adopts a collaborative management research (CMR) approach to identify patterns of organisational tensions and paradoxes and explore management strategies to overcome them. The data were collected through interviews and focus group interviews with experts on lean and/or digital technologies from the companies, from documents and from workshops with the in-case researchers.FindingsThe findings of this paper provide insights into the salient organisational paradoxes embraced in the integration of digital technologies in LPS by identifying different aspects of the performing, organising, learning and belonging paradoxes. Furthermore, the findings demonstrate the intricacies and relatedness between different paradoxes and their resolutions, and more specifically, how a resolution strategy adopted to manage one paradox might unintentionally generate new tensions. This, in turn, calls for either re-contextualising actions to counteract the drift or the adoption of new resolution strategies.Originality/valueThis paper adds perspective to operations management (OM) research through the use of paradox theory, and we (1) provide a fine-grained perspective on why integration sometimes "fails" and label the forces of internal drift as mechanisms of imbalances and (2) provide detailed insights into how different management and resolution strategies are adopted, especially by identifying re-contextualising actions as a key to rebalancing organisational paradoxes in favour of the integration of digital technologies in LPSs.

The manufacturing industry contributes to climate change and must take action to reach its high-set target. Implementation of circularity to reach sustainability has shown to be beneficial for products, but there is a lack of knowledge on how to transfer the concept to the design of factories. The purpose of the paper is to identify and systemically analyse areas of importance to enable circularity in production development to better understand what requires attention to achieve a circular factory. The focus of the study is on production development narrowed down to production equipment. A case study approach was used with interviews as the main method for data collection. Four main themes were identified: competence, collaboration, mindset and time. These were considered as areas of importance to enable circularity and to understand what needs further attention they were analysed in a systemic view of macro-, meso- and microlevel. The findings stress the need for investing in circularity in early phases to achieve circularity and that all levels of the industry need to take part in the transition towards circularity. Further, research within areas with similar complexities could benefit and learn from each other.

Digital twins have emerged as a critical technology to enable smart production. Digital twins can enhance the current production system by optimizing the current setup and facilitating decision-making based on facts rather than gut feeling. Despite the numerous benefits explored, digital twins have faced many challenges in developing and implementing production systems. Their complexity is causing a lack of digital twin implementations in the production system. This complexity can be traced back to physical and virtual entities and the digital twin development process. By conducting a case study in a global manufacturing company, this publication explores the sources of complexity when developing digital twins. The findings are organized around the digital twin development steps and their corresponding complexity. The number of different types of entities being modeled, the choice of the modeling approach, modeling low-frequency events, emergent phenomena, and the unpredictability and variability of the manufacturing process are all examples of structural and dynamic complexity that have been found to impede success in digital twin applications. This research has implications for managers who are involved in the development of digital twins in their organizations. It can help with methodological guidance when dealing with an undefined and complicated process of digital twin development.

Implementation of VR into NPD processes requires a coordinated effort from within the manufacturing organization. However, the knowledge to carry this out successfully is still quite limited within research as well as within manufacturing organizations, leading to failed pilot projects and a waste of resources. Therefore, the purpose of this paper is to identify barriers that inhibit VR implementation. A multiple case study has been carried out focusing on two VR implementation attempts within a single manufacturing site. The results identify four specific roles and their responsibilities within the VR implementation teams: Key driver, gatekeeper, key user, and general user. The results further identify the barriers experienced within the VR implementation attempts.

Factories within International Manufacturing Networks (IMNs) need coordination to harness globalization’s potential. Simultaneously, adding additional complexity, they seek to coordinate digital transformation across the IMNs, requiring a holistic view encompassing the organizational structure. The purpose of this paper is to identify how manufacturing companies adapt the organizational structures of their IMNs to coordinate digital transformation. Through a multiple case study of four manufacturing companies, the results show new or adapted functional units, roles and interfaces. The findings describe and exemplify global and local functional units, boundary spanner roles, and formal and informal interfaces created for coordinating digital transformation in IMNs.

In order to support manufacturing companies in their digital transformation, challenges and views of the term 'digital transformation' need to be identified since digital transformation is considered a source of competitive advantages. Therefore, this paper aims to explore the challenges and differing views of digital transformation in the manufacturing industry. A case study was conducted in collaboration with four Swedish manufacturing companies. The results were then mapped into categories of three dimensions (people, process and technology), indicating that digital transformation can have different meanings within a company. We conclude that the term 'digitalisation' is more frequently used in the manufacturing industry than 'digital transformation' and identified challenges relate to lack of best practice for digital transformation, degree of standardisation and therefore affects the workload and limits the possibilities of transferring technical solutions between factories. Our findings are relevant to operations managers and other interested in digital transformation. 

With a growing population and increased use of resources, there is an urgent need to transform towards sustainable production in order to stay competitive. Prior studies suggest that circular thinking positively impacts the environmental impact of products. However, few studies have investigated the implications of applying circular thinking to the design of production equipment. We address this research gap by looking at what circularity is and how it can be perceived in the context of production equipment. Our research reveals that different circularity requirements need to be implemented in different phases of the life cycle of the production equipment. However, to succeed the requirements need to be considered already early in the design phase of the production equipment. Further, since the development of production equipment is a co-creation between the equipment with the manufacturing company, i.e. users of the production equipment. The circularity thinking between the two partners needs to be aligned and coordinated. Our findings emphasise the need for a holistic approach with system thinking implemented early in the life cycle of production equipment. 

With the development towards Industry 5.0, manufacturing companies are developing towards Smart Production, i.e., using data as a resource to interconnect the elements in the production system to learn and adapt accordingly for a more resource-efficient and sustainable production. This requires selecting and integrating digital technologies for the entire data lifecycle, also referred to as the data value chain. However, manufacturing companies are facing many challenges related to building data value chains to achieve the desired benefits of Smart Production. Therefore, the purpose of this paper is to identify and analyze the critical factors of selecting and integrating digital technologies for efficiently benefiting data value chains for Smart Production. This paper employed a qualitative-based multiple case study design involving manufacturing companies within different industries and of different sizes. The paper also analyses two Smart Production cases in detail by mapping the data flow using a technology selection and integration framework to propose solutions to the existing challenges. By analyzing the two in-depth studies and additionally two reference cases, 13 themes of critical factors for selecting and integrating digital technologies were identified.

Artificial Intelligence (AI) has proven effective in assisting manufacturing companies to achieve Zero Defect Manufacturing. However, certain products may have quality characteristics that are challenging to verify in a manufacturing facility. This could be due to several factors, including the product’s complexity, a lack of available data or information, or the need for specialized testing or analysis. Prior research on using AI for challenging quality detection is limited. Therefore, the purpose of this article is to identify the enablers that contributed to the development of an AI-based defect detection approach in an industrial setting. A case study was conducted at a transmission axle assembly factory where an end-of-line defect detection test was being developed with the help of vibration sensors. This study demonstrates that it was possible to rapidly acquire domain expertise by experimenting, which contributed to the identification of important features to characterize defects. A regression model simulating the normal vibration behavior of transmission axles was created and could be used to detect anomalies by evaluating the deviation of new products compared to the model. The approach could be validated by creating an axle with a built-in defect. Five enablers were considered key to this development.