Abstract
AbstractDigital technologies have gained ground among companies, researchers and policy makers in recent years due to their growing relevance to current and future supply chains. Technologies such as robotics, artificial intelligence, autonomous transport systems, data science, and additive manufacturing are gradually becoming part of people’s and companies’ daily lives and are changing the manufacturing, process industry and logistics sectors. Although recent attempts have been made to understand the implications of these technologies on supply chain management, the relevance of the different technologies in future scenarios is still unknown. Using a technology scouting approach, the most important enabling technologies for supply chains until 2030 are identified and selected and their implications on future supply chains are evaluated using an assessment methodology with different evaluation criteria.

Abstract
AbstractDriven by the current digital transformation, European companies rely on accurate forecasting of future trends and prediction of most useful technologies in order to maintain their competitive edge. For this purpose, the mapping of enabling technologies to future scenarios becomes a valuable tool for practitioners and researchers alike, especially when considering the disruptive events that surround SCs design, implementation and management. This research sets forth to fill this gap by presenting a technology mapping of enabling technologies based on technology portfolio approach, expert elicitation and literature. The final outcome is the mapping of the enabling technologies to the characteristics of the future European SC scenarios.

Abstract
The need of lockdown, due to COVID-19, led many manufacturing companies to accelerate the adoption of digital technologies. Manufacturing companies were strongly affected by workforce shortages associated with the spread of COVID-19 and the lockdown, as well by connectivity losses among business partners. Therefore, these companies are reviewing their strategies to increase productivity, mainly embracing digital manufacturing technologies. Here the adoption of digital technologies aims to improve efficiency and flexibility in their processes, also improving connectivity among business partners. This study investigates how collaborative academia-industry R&D cases accelerated the adoption of digital technologies by manufacturing companies, given the current COVID-19 pandemic situation. Based on multiple case studies, this article reports the challenges and the strategies of three ongoing collaborative industry-academia R&D projects developed during the COVID pandemic situation. The results are presented in four different perspectives derived from industry 4.0 readiness maturity models: interpersonal communication, personal competencies and skills, systems integration, and technological strategy. It highlights the importance of manufacturing companies to have a well-designed digitalization strategy, need of continuous training and development of their workforce, and the support of Research & Technology Organizations (RTO) to bring more maturity to the efforts required during a turbulent situation. The results of this paper can provide relevant decision support for manufacturing companies, and its stakeholders, in face of challenges of the actual pandemic and post-pandemic scenario.

Abstract
Zero Defects is one of the ultimate targets for manufacturing quality control and assurance. Such systems are becoming common in advanced manufacturing industries but are at an initial stage in more traditional industrial sectors, such as wood panels, laminates production, pulp and paper processing and composite panels production. This paper proposes the PREFAB framework, applied to the wood based panels industry, to minimize rejected products using AI, machine learning and IoT devices. The framework was built through action research with a Portuguese wood-based panel manufacturing. This framework delivered an innovative decision support system that provides relevant and timely recommendations for shopfloor decision making and to support process/product engineering. Copyright (C) 2021 The Authors.

Abstract
While Industry 4.0 promises large technological improvements, firms face multiple challenges in its adoption. Current literature has made significant efforts to identify the barriers which are common to most companies but fails to identify their interrelationships and their implications for practitioners. We use interpretive structural modelling (ISM) methodology to identify these barriers and their interrelationships, combined with matrix impact of cross multiplication applied to classification (MICMAC) analysis to identify the root barriers, in the context of the Portuguese manufacturing industry. We categorize these barriers using the Technology -Organization-Environment framework. We conclude that barriers related to standardization and lack of off -the-shelf solutions are considered root barriers. Our results differ from other studies that regard barriers related to legal and contractual uncertainty with the highest driving power and lowest dependence power. Also, we find that organizational barriers have the highest dependency and lowest driving power, contradicting studies on the topic. We provide recommendations for managers and policymakers in three areas: Standardization Dissemination, Infrastructure Development, and Digital Strategy.

Abstract