Abstract
In the last years, the paradigm of the Portuguese footwear industry has improved drastically to become one of the main world players. In fact, a lot has changed, from low-cost mass production to serving clients consisting of small retail chains, where orders are small and models are varied. In order to deal with such modifications, the footwear industry started investing in technological solutions. The industrial case presented in this paper fits that purpose. The goal is to contribute to the solution of complex scheduling problems arising in the new mixed-model flexible automatic stitching systems of an important footwear factory. The project starts by building an optimization model. Although the model has its own usefulness, the CPLEX program is only capable of reaching optimal solutions for small problem instances. Therefore, a recent metaheuristic, the Imperialist Competitive Algorithm (ICA), has been chosen to tackle larger problems. The ICA is capable of finding optimal results for smaller instances and achieving adequate solutions for real problems in short periods of time. Moreover, ICA improves the results obtained so far by the method currently used in the factory.

Abstract
Sectorization refers to partitioning a large territory, network, or area into smaller parts or sectors considering one or more objectives. Sectorization problems appear in diverse realities and applications. For instance, political districting, waste collection, maintenance operations, forest planning, health or school districting are only some of the application fields. Commonly, sectorization problems respect a set of features necessary to be preserved to evaluate the solutions. These features change for different sectorization applications. Thus, it is important to conceive the needs and the preferences of the decision-makers about the solutions. In the current paper, we solve sectorization problems using the Genetic Algorithm by considering three objectives: equilibrium, compactness, and contiguity. These objectives are collected within a single composite objective function to evaluate the solutions over generations. Moreover, the Analytical Hierarchy Process, a powerful method to perceive the relative importance of several objectives regarding decision makers' preferences, is used to construct the weights. We observe the changes in the solutions by considering different sectorization problems that prioritize various objectives. The results show that the solutions' progress changed accurately to the given importance of each objective over generations.

Abstract
The manufacturing industry faces a new revolution, grounded on the intense digitalization of assets and industrial processes and the increasing computation capabilities imposed by the new data-driven digital architectures. This reality has been promoting the Digital Twin (DT) concept and its importance on the industrial companies' business models. However, with these new opportunities, also new threads may rise, mainly related to industrial data protection and sovereignty. Therefore, this research paper will demonstrate the International Data Spaces (IDS) reference model's application to overcome these limitations. Following a pilot study with a Portuguese machine manufacturing company, this paper will demonstrate the development of a cutting and bending machines DT, leveraged on an IDS infrastructure for interoperability, for the plastic and metal industry and its importance to introduce this machine manufacturing company in a new B2B marketplace from the EU project Market 4.0.

Abstract
The principles and tools made available by the Industry 4.0, smart factories, or the Internet of Things (IoT), along with the adoption of more comprehensive simulation models, can significantly help the industry to face the current, huge external and internal challenges. This paper presents a new simulation-based approach to support decision making in the design and operational management of manufacturing systems. This approach is used to evaluate different layouts and resources allocation, and help managing operations, by integrating a simulation software with real-time data collected from the production assets through an IoT platform. The developed methodology uses a digital representation of the real production system (that may be viewed as a form of a digital twin) to assess different production scenarios. A set of key performance indicators (e.g. productivity) provided by the simulation can be used by the Manufacturing Execution System (MES) to generate production schedules. The developed approach was implemented and assessed in a real case study, showing its robustness and application potential. Its extension to other industrial contexts and sectors seems, therefore, quite promising. Copyright (C) 2021 The Authors.

Abstract
The Real-Time Monitoring and Performance Management suite tool, known as UIL (User Interface Layer), was developed in the FASTEN project, a R&D initiative financed by the innovation and research program H2020 within a bilateral Europe-Brazil call. UIL was conceived and deployed in the IIoT architecture of the project. The goal was to provide a usercentered assistance to the human operator for both decision-responsibility and control loop, in a continuously updating information fashion, related to system's state. In order to have experimental results, a qualitative assessment was conducted in an industrial environment. The architecture proposed was based on the adoption of a Knowledge Engineering User Interface to support Operator 4.0. Our empirical experiments point out to a successful set of results. Copyright (C) 2021 The Authors.

Abstract
The scarcity of resources is one of the main concerns for the present and the future of the environment and society. The "load factor" in logistic transport has a great potential for improvement, especially in the last-mile deliveries, as the transport of goods is largely fragmented between several small companies using small vehicles. This paper investigates the potential for collaboration to increase efficiency in urban logistics. Based on an overview of the concepts and initiatives regarding vertical and horizontal collaboration, a research agenda is proposed.