Constant advancements in biomanufacturing require operational frameworks that enable accurate comparisons between similar production processes for performance and cost optimization purposes. However, the extensive and heterogeneous nature of available data which is often presented in different formats, characterized in different ways, and reported in disparate units - poses a significant challenge to an efficient and effective comparative analysis. In this paper, the potential benefits of applying the biomanufacturing production process ontology to provide a common ground for addressing data heterogeneity issues are investigated in the context of process design optimization with respect to key performance indicators (KPIs). Using acetic acid fermentation as a case study, three semi-continuous processes involving different bacterial species and feedstock sources were analyzed. Existing industrial ontologies were utilized, and additional ontologies were developed to facilitate the normalization of notions and link data from multiple domains, including life cycle analysis, process, production, and materials. Following ontology development best practices, competency questions and respective queries were formulated to validate the ontology, with the aim to evaluate KPIs, including the material intensity and the number of fermentation cycles each microorganism can sustain. Results demonstrate that the ontology effectively resolved data inconsistencies, enabling more accurate comparisons and providing deeper insights into the differences in processes across various strains and conditions.
To remain competitive in the long term and sustain or expand market share, companies rely on continuous innovation. In practice, investment decisions are typically based on expected economic value, although such evaluations are challenging in early innovation phases due to limited data availability. In particular, the future economic potential of the results from fundamental research is difficult to predict. The Collaborative Research Center 1368 investigates the influence of an oxygen-free atmosphere on the active zones in production processes as an innovation to develop future-proof production technologies. One example is the compound casting of oxide-free aluminum-copper composites with fullsurface metallurgical bonds, which significantly improves thermal conductivity compared to conventional joining methods. A relevant application lies in computer components such as graphical processing units, where power electronics generate substantial heat loss and demand efficient, sustainable cooling solutions. These require improved material performance to reduce thermal resistance and enable more effective heat dissipation, potentially extending the product use phase. While the innovation introduces additional manufacturing effort, it also offers potential long-term economic benefits during the use phase. This paper proposes an approach to integrate use phase benefits into early-stage innovation evaluation, capturing economic effects that extend beyond the production stage. This study supports a more holistic and forward-looking assessment of innovation potential by focusing on functional performance improvements and their relevance for customer value, particularly through the extended product use phase. The findings can be fed back into the development process, helping identify and improve key value drivers early on.
This study examines how inherent contradictions affect supply chain planning (SCP) practices in engineer-to-order (ETO) settings through a multi-case study of five companies. The research identifies sixteen contradictions across four paradox categories: performing, organizing, belonging, and learning paradoxes. The findings reveal that contradictions shape SCP practices while SCP practices simultaneously influence how contradictions are managed. Companies employ four management strategies: acceptance, spatial separation, temporal separation, and synthesis to handle contradictions. One of the approaches acknowledge contradictions as inherent features of ETO settings rather than a problem to eliminate. Companies with structured SCP processes demonstrate better contradiction management capabilities, creating virtuous cycles of continuous improvement. The research contributes to paradox theory by validating the dynamic equilibrium model in SCP contexts and identifying organizational capabilities that enable effective paradox management. For practitioners, the study suggests that explicitly acknowledging contradictions, aligning organizational structures, and developing balanced performance metrics can transform competing demands into sources of competitive advantage rather than operational constraints.
Norwegian yards face difficulties in operational coordination and the adoption of effective technical solutions, reducing their overall productivity. To remain competitive and fully leverage the vast amount of data, it is essential to adopt innovative technologies and methods, such as digital twins and artificial intelligence. This study aims to map the current applications of digital twin technology in yards, exploring its potential, challenges, and needs. A comprehensive literature review and a case study from a Norwegian yard are conducted. Research reveals that applications are often limited to small or specific parts of the yard, rather than full-scale operations. While the use of 3D visualization tools and artificial intelligence optimization methods is widespread, the findings highlight the need to implement digital twins and artificial intelligence technologies more extensively in production and across entire yard operations to enhance overall efficiency and productivity.
Digital transformation (DT) has revolutionized manufacturing by enhancing efficiency, productivity, and competitiveness. However, adoption remains concentrated among large corporations, while microenterprises (MEs) often lag due to limited resources, which hinders their growth. Conventional DT strategies focused on SMEs are ill-suited for MEs, which face distinct challenges such as informal structures, minimal capital, low digital literacy, and reliance on analog machinery-risking a widening digital divide. This study investigates DT in the context of manufacturing MEs, focusing on migrant-run enterprises in Oman operating under severe constraints. Based on a qualitative methodologyincluding interviews, field observations, and participatory work-it proposes a frugal, two-layer DT framework tailored to the socio-technical realities of MEs. The digital layer emphasizes immediate digitalization of business processes using accessible tools like spreadsheet dashboards and pricing templates, co-designed with ME stakeholders to ensure relevance and usability. The physical layer enables access to digitally capable production infrastructure through low-cost, DIY opensource machine tools (OSMT). This is demonstrated through the local replication of an open-source 3D printer design. By prioritizing affordability and leveraging open-source technologies, the proposed approach reduces dependency on proprietary systems and offers a practical path toward inclusive digital transformation. This research contributes to emerging discussions on DT for MEs, offering actionable strategies to enhance their competitiveness in an increasingly digital manufacturing landscape.
