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The purpose of this paper is to present propositions for facilitating the integration of additive manufacturing (AM) for manufacturing companies in the heavy vehicle sectors based on identified success factors and lessons learned in use cases with different operational purposes. A case study was conducted that identified 42 retrospective use cases from three main sources highlighting seven different use case types with contributions from seven sectors representing 14 countries on four continents. Six success factors (technology infrastructure, relative advantage, organizational readiness, competitive pressure, expectations of market trends, and trading partner) and 20 lessons learned sorted into five dimensions (additive thinking, management aspects, practice makes perfect, AM acceptance, and AM experts) were identified in the use cases based on the analysis. Three propositions covering the three stages of integration were derived based on the identified success factors and lessons learned. These propositions should provide guidance on what managers need to be prepared for when integrating AM step-by-step. Integrating AM is no simple feat, and the propositions only scratch the surface since the complexity of AM runs deep both technically and managerially. Future research should investigate in-depth operational capabilities and, if applicable, dynamic capabilities to further enhance facilitating the integration of AM step-by-step.

The purpose of this paper is to explore changes in operational capabilities and their impact when integrating additive manufacturing into a traditional manufacturing company. This was exemplified based on a sub-system component (gears and shafts in a gearbox) for automotive applications that are developed and manufactured at a manufacturing company in the commercial vehicle sector. The research was set up based on a case study consisting of semi-structured interviews, informal meetings, observations, company documents, reports, presentations, and field notes. The literature and findings from empirical data converged into 57 themes of operational capabilities that were categorized into six aggregated dimensions. The results suggest two emerging dimensions, namely stakeholders and strategy, building upon an existing theoretical framework. Integrating AM into traditional industrial settings requires several changes in operational capabilities. It is essential to consider the following priorities, 1) gain understanding and knowledge in design for AM, 2) build robust AM infrastructure as an integral part of existing infrastructure, 3) evaluate AM process changes in product development and production, 4) establish an internal AM team with at least one person working full time with AM, 5) establish collaborations with suitable AM research partners, and 6) conduct AM management and evaluate the business impact not only short-term but also long-term. Future research should investigate operational capabilities from other use cases, dynamic capabilities in the same or similar contexts, and transform the required operational capabilities into guidelines and best practices for managers and other decision-makers in the manufacturing industry.

The purpose of this paper is to identify the challenges in the integration of additive manufacturing (AM) that management faces in large manufacturing companies. Based on a case study consisting of a focus group, interview, informal meetings, direct and participant observations, company documents, reports, presentations, and field notes, seven dimensions containing 20 challenges were identified. The challenges were mentioned by 10 participants from four functional organizations. Thereafter, the 20 challenges were sorted into the three stages of integration. The results suggest a newly emerging theme that builds upon an existing framework. Organizational change was a unanimous concern by all functional organizations when contemplating integrating AM into the whole organization. Most of the challenges appear in the pre-integration stage and the post-integration stage compared to the integration stage which only highlighted two challenges. Future research should investigate solutions that contain proper actions and capabilities to overcome the identified challenges to enhance facilitating the integration of AM step-by-step.