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Industry 4.0 Readiness Assessment – A Comparative Analysis of Portuguese and Brazilian Companies
Full text linkPurpose: This paper aims to present a comparative analysis of the Industry 4.0 (I4.0) maturity levels between Portuguese and Brazilian industrial companies. This study focuses on identifying signi¯cant di®erences across various evaluation dimensions using a standardized maturity model (MM). Methodology: The same evaluation model, developed by the German Mechanical Engineering Industry Association (VDMA), was applied to Portuguese and Brazilian companies, speci¯cally in the State of Esp {rito Santo (ES). The research encompassed 370 Portuguese industrial companies and 46 Brazilian ones. The VDMA platform was used to process individual results, indicating the levels across six model dimensions and providing an overall score on a scale of 0–5. The data collected were then tabulated to enable a comparative analysis between the two countries. Findings: The study revealed that, on average, Brazilian companies have a lower maturity level (0.95) than Portuguese companies (1.22) on the 0–5 scale for I4.0 readiness. Notably, signi¯cant di®erences were observed in the dimensions of Smart Operations and Employees. Based on these di®erences, this study outlines potential pathways for these companies to enhance their I4.0 maturity levels. Originality/value: This research provides a unique comparative perspective on industrial companies' I4.0 maturity levels in Portugal and Brazil, using a standardized and widely recognized MM. The ¯ndings o®er valuable insights into the speci¯c areas where companies in these countries can focus their e®orts to advance their readiness for I4.0, highlighting the importance of tailored strategies for di®erent national contexts.N/
Overview of the use of data assets in the context of Portuguese companies: Comparison between Micro, SMEs and large companies
No full textIn the digital age, data has become a crucial asset for businesses, serving as a valuable resource for production and decision-making. Effective data management is essential for enhancing companies’ competitiveness and operational efficiency. While big data holds the potential to drive innovation, particularly for small and medium-sized companies (SMEs), many companies struggle to leverage this digital capability effectively. This article examines the nuances of data management practices in Portugal, highlighting the differences between micro, small, medium, and large companies. To achieve this, data were collected from 390 Portuguese companies, and a Kruskal–Wallis Test was conducted to determine if significant differences exist in data utilization across company sizes. The results indicate substantial disparities in the use of data for developing new services and in the application of technologies for Data Storage Security, Security for Data Exchange with Partners, and Cloud Computing Security among micro, small, medium, and large companies. These findings underscore the importance of tailored strategies to improve data management practices and enhance the digital capabilities of companies of all sizes.info:eu-repo/semantics/publishedVersio
The Synergy Between Lean Philosophy and Value Engineering for New Product Development
No full textrganizations worldwide consistently strive to eliminate waste through approaches like Lean and adopting core functions through concepts such as Value Engineering (VE). Several sources affirm that integrating VE with Lean can enhance, streamline, and amplify efforts to implement Lean principles within an organization. Conversely, Lean can improve the effectiveness of VE initiatives. Based on a comprehensive literature review utilizing a natural language processing algorithm, this study focuses on understanding the intersection between these concepts. The review identified eight main sub-topics across three key areas: Lean Healthcare and Performance, Customer Value Improvement, and Process and Product Optimization. The practical implications of integrating Lean and VE in product development include faster time-to-market, enhanced manufacturability, and improved product quality while reducing start-up issues and development costs. This integration fosters a more collaborative environment, aligning teams with customer needs and expectations. The unique contribution of this study lies in demonstrating how Lean and VE, when applied together, form a holistic and robust framework that optimizes efficiency and ensures superior functionality and cost-effectiveness throughout the product development lifecycle.info:eu-repo/semantics/publishedVersio
AI-Powered Data Management to Optimize Data Collection and Processing in a Painting Laboratory
Full text linkIndustrial laboratories often remain under-digitized compared to production lines, creating a gap between data acquisition and analytical intelligence, critical for advanced quality control. This study addresses this gap by proposing and validating a novel framework that combines Low-Code digitalisation tools with Machine Learning (ML) and Causal Inference to optimise data collection and analysis in an automotive painting laboratory. A Microsoft Power Apps-based platform was developed in order to digitalise all measurement records, eliminating manual transcription errors (previously ≈ 40.01%) and reducing data-handling time by up to 34% of an operator’s shift, while enabling centralised, traceable storage and Power BI integration. Four datasets were used to assess predictive capacity with Random Forest, XGBoost and Neural Networks; Random Forest consistently provided the most stable results—Mean Absolute Error (MAE) of 0.972, Mean Absolute Percentage Error (MAPE) of 16.45%, and Root Mean Square Error (RMSE) of 1.307. Causal models (Linear Regression, DoWhy, Causal Forest, Double Machine Learning) consistently identified ultrafiltrate I solid content of the electrodeposition process as a dominant causal factor for defects. This study provides a novel framework that bridges digitalisation and ML-based causal reasoning in laboratory settings, offering a scalable approach that can be extended and replicated in other industrial sectors, aiming to develop smart, data-driven quality control systems.info:eu-repo/semantics/submittedVersio
Mapping PRNP Polymorphisms in Portuguese Serra da Estrela Ovine Populations: Insights into Scrapie Susceptibility and Farm Animal Improvement
Full text linkScrapie (classical and atypical) susceptibility in sheep is strongly influenced by PRNP gene polymorphisms. In Portugal, limited data exist for native breeds such as Serra da Estrela, despite their relevance to animal conservation and food production. The full coding region of PRNP gene of 92 Serra da Estrela sheep was sequenced and SNP frequencies were analysed. The predicted functional impact of nonsynonymous SNPs was assessed using PolyPhen-2 and AMYCO. A total of 27 SNPs were identified, including 20 nonsynonymous variants. Thirteen major haplotypes were observed. The ARR allele, which provides resistance to classical scrapie, was present in 58.7% of the population, with 18.5% of animals being homozygous. Several previously unreported SNPs were identified, and their impact on prion protein aggregation propensity and structure was explored. The high frequency of the ARR allele without full ARR fixation suggests that no selective breeding for scrapie resistance has been applied. These results support the adoption of gradual selection strategies that preserve genetic variability and promote farmer compliance, while increasing classical and atypical scrapie resistance.info:eu-repo/semantics/publishedVersio
Digital maturity and business performance in industry 4.0: evidence from industrial firms in Portugal's Dão Lafões region
No full textPurpose – Digital maturity in the context of Industry 4.0 has become a key driverfor enhancing industrialization and overall business performance in the manufacturing sector. However, limited understanding remains regarding how the different pillars of digital maturity affect organizational and financial outcomes. This study investigates the influence of these pillars on key business performance indicators. Design/methodology/approach – A conceptual framework was developed to support the primary research hypotheses. A survey was conducted with 140 manufacturing companies in the D~ao Laf~oes region (Portugal), assessing subdimensions of digital maturity. Business performance data (ROA, debt, interest rate, productivity and Internationalization) were retrieved from the Iberian Balance Sheet Analysis System. Responses were collected through face-to-face interviews with managers, ensuring high-quality and context-rich data. Multiple linear regression models and robust statistical tests ensured the reliability of the results. Findings – Digital maturity has significant but heterogeneous effects on performance. Strategy and data analytics negatively affect ROA and productivity, while existing competencies positively influence internationalization. Strategy is also associated with higher debt. Other subdimensions show marginal effects on internationalization, debt, and interest rate. Practical implications – This study advances both the Industry 4.0 and performance management literature by demonstrating how distinct digital maturity pillars exert heterogeneous effects on operational and financial indicators. The findings refine existing maturity frameworks by showing that early-stage I4.0 adoption may generate negative short-termimpacts, underscoring the need for phased, capability-driven digital transformation strategies in SME-dominated regions. Originality/value – This study contributes to the literature on Industry 4.0 by providing empirical evidence on the differentiated effects of digital maturity subdimensions on business performance. It offers practical insights for policymakers and businessleadersseeking to optimize digital transformation strategies, particularly in SMEdominated industrial regionsinfo:eu-repo/semantics/publishedVersio
Influence of Injection Conditions on Adhesion Interface in Sandwich Panels
No full textComposites are materiais combining a strong reinforcement with a lighter matrix for enhanced mechanical and thermal properties. A typical example is the sandwich panei, comprising sturdy outer layers and a lightweight core, such as rock wool, enclosed between them. The outer layers can be metal, wood, or plastic. In paneis with polyurethane (PUR) cores, the bond between the PUR and metal sheets can weaken over time due to stress and fatigue, potentially causing structural failure. Researchers are actively exploring methods to enhance PUR and metal sheet adhesion. Their studies encompass surface treatments, optimizing injection conditions, refining PUR composition, and computer modeling of the material interface [1, 2]. Studies by Pereira et al. [ I ] highlighted that primers significantly enhance adhesion, whereas Naik et al. [2] explored optimizing the production process through tests to ensure robust and long-lasting adhesion. This study investigated the adhesion of PUR adhesives to metal sheets under real-world production conditions. The paneis were produced in a factory environment using ali the parameters and procedures to create a fundamental part. The study aimed to identify and categorize common adhesion defects (e.g., voids, weak adhesion) that may occur during production, additionally, it aimed to develop corrective actions to prevent these defects. The study involved performing pull-out tests on specimens taken from different positions on a large board and comparing the results with reference specimens without defects.info:eu-repo/semantics/publishedVersio
A transformação Digital do Marketing no Setor Vitivinícola: O Impacto da Inteligência Artificial e Automação na Região do Dão
No full textA transformação digital está a redefinir a forma como as empresas vitivinícolas comunicam, promovem e gerem a sua relação com os consumidores. O presente estudo
analisa o impacto da Inteligência Artificial (IA), da automação e do Big Data nas práticas de marketing digital das quintas e cooperativas da Região Demarcada do Dão, procurando
compreender até que ponto estas tecnologias já se encontram implementadas e contribuem para melhorar o desempenho e a competitividade do setor.
A investigação recorreu a uma abordagem quantitativa de natureza descritiva e exploratória, baseada na aplicação de um questionário digital a dez organizações
vitivinícolas da região. O instrumento, validado e aplicado através da plataforma Microsoft Forms, permitiu recolher dados sobre níveis de adoção tecnológica, perceções
de impacto e barreiras à transformação digital. A análise estatística foi conduzida com recurso ao software Jamovi, utilizando testes não paramétricos como Kruskal–Wallis,
Mann–Whitney e o Teste Exato de Fisher.
Os resultados evidenciam que a transformação digital no setor vitivinícola do Dão é uma realidade em desenvolvimento, ainda com níveis desiguais de maturidade tecnológica. A
Inteligência Artificial e a automação de marketing revelaram associações positivas com o aumento do alcance e da fidelização dos clientes, enquanto o uso de Big Data
demonstrou impacto significativo no desempenho comercial, particularmente nas vendas.
Identificaram-se também barreiras de natureza cultural e organizacional, como a resistência à mudança e a falta de apoio da gestão, que condicionam a adoção tecnológica.
O estudo contribui para o conhecimento científico sobre a digitalização do marketing vitivinícola em contexto regional, oferecendo uma perspetiva empírica sobre o estado
atual do setor e propondo pistas para futuras investigações e estratégias de modernização digital.Digital transformation is redefining how wine companies communicate, promote, and manage their relationships with consumers. This study analyses the impact of Artificial
Intelligence (AI), marketing automation, and Big Data on the digital marketing practices of wineries and cooperatives in Portugal’s Dão Demarcated Region, seeking to
understand how these technologies enhance performance and competitiveness within the sector.
A quantitative, descriptive, and exploratory approach was adopted, based on an online survey conducted with ten wine organizations in the region. The questionnaire, validated and distributed via Microsoft Forms, collected data on technology adoption, perceived impact, and barriers to digital transformation. Data analysis was performed using Jamovisoftware through non-parametric tests such as Kruskal–Wallis, Mann–Whitney, and
Fisher’s Exact Test.
Results show that digital transformation in the Dão wine sector is progressing but remains at uneven levels of technological maturity. Artificial Intelligence and marketing
automation were positively associated with increased audience reach and customer loyalty, while the use of Big Data showed a significant impact on commercial performance, particularly sales. Cultural and organizational barriers, including resistance to change and lack of management support, were also identified as limiting factors.
This study contributes to the scientific understanding of digital transformation in the wine industry by providing an empirical view of the Dão region’s current situation and offering insights for future research and strategies to foster digital modernization
Molecular Screening of Sarcocystis spp. in Grazing Sheep (Ovis aries) and Shepherd Dogs (Canis lupus familiaris) from Central Portugal
Full text linkSarcocystis spp. are cyst-forming protozoan parasites with a global distribution that infect a wide range of domestic and wild animals, impacting both animal health and livestock productivity. In sheep, infections can cause clinical disease, reproductive losses, and economic damage, articularly when pathogenic species such as Sarcocystis tenella are involved. Grazing sheep, including breeds such as the Serra da Estrela from central Portugal, are at increased risk due to frequent contact with shepherd dogs, which serve as definitive hosts. Despite their significance, data on the occurrence and distribution of Sarcocystis spp. in Portuguese sheep remain limited. This study analyzed 179 samples collected in central Portugal during 2024, including 41 brain tissues and 88 blood samples from sheep, and 50 stool samples from shepherd dogs, using conventional PCR and bidirectional Sanger sequencing. Sarcocystis sp. closely related to S. tenella was detected exclusively in sheep brain tissue, with a prevalence of 4.9% (2/41; 95% CI: 0.60–16.53), while no parasite DNA was found in blood or dog samples. These results provide the first molecular confirmation of Sarcocystis spp. closely related to S. tenella in Portuguese sheep raised for human consumption and establish baseline data for future epidemiological surveillance and control strategies.N/
