Abstract
This paper presents a Cyber Physical System (CPS) laboratory based on Open Design, called Open Science Laboratory for Manufacturing (OSLab4Man), with educational and research purpose and the potential contribute and (direct and indirect) effects regarding the 17 Sustainable Development Goals (SDGs). A short introduction describing the 17 SDG, the education for sustainability role, and the relevance of the framed CPS. A literature review of CPS laboratories that are addressed to sustainability is presented. The OSLab4Man is describe in the educational purpose lens. Then, the contribute of the OSLab4Man as an education tool for sustainability regarding the 17 SDGs is reflected. Finally, the conclusions of this work and future works are highlighted.

Abstract
There are Optimization Problems that are too complex to be solved efficiently by deterministic methods. For these problems, where deterministic methods have proven to be inefficient, if not completely unusable, it is common to use approximate methods, that is, optimization methods that solve the problems quickly, regardless of their size or complexity, even if they do not guarantee optimal solutions. In other words, methods that find acceptable solutions, efficiently. One particular type of approximate method, which is particularly effective in complex problems, are metaheuristics. Particle Swarm Optimization is a population-based metaheuristic, which has been particularly successful. In order to broaden the application and overcome the limitation of Particle Swarm Optimization, a discrete version of the metaheuristics is proposed. The Discrete Particle Swarm Optimization, DPSO, will change the PSO algorithm so it can be applied to discrete optimization problems. This alteration will focus on the velocity update equation. The DPSO was tested in an instance of the Traveling Salesman Problem, att48, 48 points problems proposed by Padberg and Rinaldi, which showed some promising results.

Abstract
Purpose: The study purpose was to analyse the excellence and operational efficiency of Portuguese industrial companies through the measurement of lean practices implementation. Additionally, it intended to propose a new model to assess the lean production system. Design/methodology/approach: The research presents an in-depth lean literature review that served as a basis for the creation of a questionnaire. The survey was addressed to Portuguese industrial companies to obtain data about their lean implementation success. Collected data were analysed, resorting descriptive and exploratory statistics. A principal component analysis was applied to reduce the amount of data and define a new model that characterizes the lean practices adoption level. Some Chi-square tests were used to assess the independence of some variables. Findings: The results indicate that a significant percentage of organizations use lean practices within their activity. Concerning the lean implementation maturity, a plus side revealed by the study concerns the adoption of the teamwork, internal information shared principles, increase of process capability to produce conforming products, and reduction in set up times. On the other hand, responsibilities decentralization, more employees acting as team leaders, implementation of employees' suggestions, and interconnection with suppliers, are some of the principles that need to be given greater attention by the Portuguese industrial organizations. The key contribution consists of a new model for lean determinants based on three dimensions: work method, productive process elements, and work efficiency. Originality/value: The present research provides a new Lean determinants model that allows understanding the importance of the operational efficiency provided by a mature lean production system, being the key to the competitiveness in the global business market.

Abstract
The industry 4.0 revolution provides the machines with a sen-sory and communicational capacity, which allows them to mo-nitor and collect large amounts of information. This kind of data have an impact on planning, maintenance, and management of production, enabling real time reaction, efficiency increase, and the development of predictive and process improvement models. The most recent machines are prepared to communicate with the existing monitoring systems, however, many (around 60%) do not. The objective of this work is to present the proposal of a sys-tem for remote monitoring of equipment in real time that meets the requirements of low cost, simplicity, and flexibility. The system monitors the equipment in a simple and agile way, regardless of its sophistication, installation constraints and company resources. A prototype of a system was developed and tested both labo-ratory conditions and a productive environment. The proposed ar-chitecture of the system comprises of a sensor that transmits the machine's signal wirelessly to a gateway which is responsible of collecting all surrounding signals and send it to the cloud. During the testing and assessment of the tools, the results validated the developed prototype. As main result, the proposed solution offers to the industrial market a new low-cost monitoring system based in mature and tested technology laid upon flexible and scalable solutions.

Abstract
The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, trough the literature review, there were identified five broad suppliers selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. Thereafter, a survey was elaborated and companies were contacted in order to answer which factors have more relevance in their decisions to choose the suppliers. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Simple Multi-Attribute Rating Technique (SMART). The result of the research undertaken by the authors is a reference model that represents a decision making support for the suppliers/partners selection process.

Abstract
The automotive industry is one of the most demanding sectors of the global market. The response capacity and flexibility of companies represent a key factor for their success. Applying Six Sigma, it was carried out an improvement project aiming at reducing the quantity of scrap on the most critical sector of a automotive components’ manufacturer achieving a better comprehension of the flows, process characteristics and different variables associated to the scrap generation, identifying the equipment responsible for that scrap and its type. Brain- storming sessions were performed, as well as the application of 5 Why’s and 5W2H techniques in order to fulfill the Ishikawa diagrams aiming at understanding possible root-causes for the scrap generation. A definition of the improvement actions has been developed. A reduction of 15% was achieve just in the machine identified as the main generator of scrap in these processes. © 2020, Springer Nature Switzerland AG.