Abstract
The Industry 4.0 (i4.0) paradigm was conceived bearing smart machines enabling capabilities, mostly through real-time communication both between smart equipment on a shop floor and decision-aiding software at the business level. This interoperability is achieved mostly through a reference architecture specifically designed for i4.0, which is aimed at devising the information architecture with real-time capabilities. From such architectures, the Reference Architectural Model for Industrie 4.0 (RAMI 4.0) is considered the preferred approach for implementation purposes, especially within Small and Medium Enterprises (SMEs). Nevertheless, the implementation of RAMI 4.0 is surrounded with great challenges when considering the current industrial landscape, which requires retrofitting of existing equipment and the various communication needs. Through three different case studies conducted within footwear and cork industries, this research proposes a RAMI 4.0 SME implementation methodology that considers the initial stages of equipment preparation to enable smart communications and capabilities. The result is a methodological route aimed for SMEs’ implementation of smart machines, based on RAMI 4.0, which considers both the technological aspects as well as the business requirements. © 2020, Springer Nature Switzerland AG.

Abstract
Sensors are susceptible to failure when exposed to extreme conditions over long periods of time. Besides they can be affected by noise or electrical interference. Models (Machine Learning or others) obtained from these faulty and noisy sensors may be less reliable. In this paper, we propose a data augmentation approach for making neural networks more robust to missing and faulty sensor data. This approach is shown to be effective in a real life industrial application that uses data of various sensors to predict the wear of an automotive fuel-system component. Empirical results show that the proposed approach leads to more robust neural network in this particular application than existing methods.

Abstract
New opportunities for lifelong learning, alternative curricula in pre-university education and fairly "open" policies on access to Higher Education (HE) have boosted, in recent decades, the problem of the lack of homogenization of knowledge and skills of "freshmen" students in Higher Education Institutions (HEI). This problem becomes overwhelming when it comes to "constructive" basic curricular units, such as Mathematics or Statistics, in non-mathematical degrees, in areas as Administration, Accounting or Management. This is a daily "struggle" faced by teachers of these curricular units as they try to talk about more advanced subjects to a very heterogeneous audience, with significant differences in Math background, promoting the participation of all students and avoiding the early drop out of some. In this sense, other didactic strategies, which include a set of activities that combine higher order thinking skills with math subjects and technology, for students of HE, appear as remedial but important, proactive and innovative measures in order to face and try to level up Math competences without risking the "repetition process", that unfortunately promotes other kind dropout behaviors. In this paper some of these strategies, developed in the Polytechnic of Porto (P.PORTO) and based on the creation and usefulness of the interactive teaching and learning materials, will be presented. The actual need for innovating in the teaching-learning process was felt and the search for a good support software, that enables to develop all the materials and implement real interactions, culminated with the choice of iSpring Suite 9. This software is a powerful eLearning toolkit for PowerPoint that allows to develop quality courses, video lectures, and assessments that will work on any desktop, laptop and mobile platform. Therefore, the use of the iSpring Suite 9 will be described, with a special focus on core objective when teaching statistics to students from the Management and Business degree in a HEI and facing the abovementioned issues - to improve students' basic statistics skills and enhance their motivation in learning Statistics.

Abstract
The European Union has been making efforts to increase energy efficiency within its member states, in line with most of the industrialized countries. In these efforts, the energy consumed by public lighting networks is a key target as it represents approximately 50% of the electricity consumption of European cities. In this paper we propose an approach for the autonomous management of public lighting networks in which each luminary is managed individually and that takes into account both their individual characteristics as well as ambient data. The approach is compared against a traditional management scheme, leading to a reduction in energy consumption of 28%.

Abstract
Many domestic enterprises in emerging economies are concerned with the question of how to better utilize the portfolio of technology sourcing channels to achieve rapid economic growth by technological innovation. This paper looks at this issue by exploring the impacts of knowledge acquisition diversity (KAD) on innovation performance of domestic enterprises in China and the technological contexts (in terms of technology gap and technology development speed) under which KAD is most likely to contribute. Using panel data of the manufacturing industry in China over the 2001-2009 period, the results show that KAD has an inverse U-shaped relationship with innovation performance in terms of both product-related innovation performance (NPS) and knowledge-related innovation performance (PAT). Specifically, it reveals that the capability to generate technological innovation over time is dependent on how domestic enterprises manage their portfolio of knowledge sourcing channels to learn from foreign enterprises. Moreover, it is shown that the technology gap significantly moderates the inverted U-shaped relationship between KAD and both NPS and PAT. Technology development speed has a moderating effect on the inverted U-shaped relationship between KAD and innovation only in terms of NPS. The results of this study can help us to understand the relationships among technological contexts, KAD and innovation performance of domestic enterprises in emerging countries.

Abstract
Purpose This paper aims to investigate supply chain (SC) strategies, analyzing the adoption of lean, agile, leagile and traditional SC strategies with respect to product characteristics, environmental uncertainty, business performance and innovation performance. Design/methodology/approach The paper presents an empirical analysis carried out on a sample of 329 companies. Cluster analysis was applied, based on lean and agile SC characteristics, to identify patterns among different SC strategies. One-way analysis of variance of different constructs by types of SC clusters was conducted to test the research hypotheses. Findings Cluster analysis indicates that the companies studied adopt four types of SC strategies - lean, agile, leagile and traditional. The differences between the clusters are identified and discussed, highlighting that companies adopting a leagile SC strategy present the highest performance, while those that adopt a traditional SC present the lowest; companies adopting an agile SC compete in the most complex and dynamic environments, while companies with a lean SC present a clear predominance of functional rather than innovative products. Originality/value Based on the analysis of the relationship between constructs that have not been addressed previously, the paper adds to the knowledge regarding the role of SC strategies, as well as the antecedents and consequences of their adoption. The results may support managers in the difficult task of choosing the "right" SC strategy.