Digitalization is rushing throughout the world, namely, in industrial and societal infrastructures. Hence, digital transformation becomes a pillar of industrial policy, known in Europe as “Industry 4.0,” in China as “made in China 2025,” in Asia as “Smart Cities,” in Japan as “Society 5.0,” and in North America as “Industrial Internet.” These transformations will change the industrial landscape, toward Quality 4.0 and therefore, our lives. The presented research was conducted on quality management employees in Portugal and it aims to analyze if such employees have the perception of the impact of Industry 4.0 in the quality management profession and the required and needed skills. After analyzing the answered questionnaires, 90 results were considered valid. This is the sample of our study. Simultaneously, the goal of this research is also to review and analyze the main topics in progress related to quality management for the fourth industrial revolution and how quality emerges of this change. The professionals that work on quality management must have creative thinking, be leaders, know how to communicate and work as a team, as well as, to have knowledge and understanding of ICT (Information and Communications Technology), and main pillars of Industry 4.0. These are the main findings. Besides that, they must know how to motivate their work teams, be open to change, know how to use Big Data to make decisions and above all, they must know how to manage conflicts. In addition, quality professionals must promote the design and production of first class products, be the defenders of their customers within the organization, and finally, they must create value for the stakeholders.

In the last decade, researchers have focused on digital technologies within Industry 4.0. However, it seems the Industry 4.0 hype did not fulfil industry expectations due to many implementation challenges. Today, Industry 5.0 proposes a human-centric approach to implement digital sustainable technologies for smart quality improvement. One important aspect of digital sustainability is reducing the energy consumption of digital technologies. This can be achieved through a variety of means, such as optimizing energy efficiency, and data centres power consumption. Complementing and extending features of Industry 4.0, this research develops a conceptual model to promote Industry 5.0. The aim of the model is to optimize data without losing significant information contained in big data. The model is empowered by edge computing, as the Industry 5.0 enabler, which provides timely, meaningful insights into the system, and the achievement of real-time decision-making. In this way, we aim to optimize data storage and create conditions for further power and processing resource rationalization. Additionally, the proposed model contributes to Industry 5.0 from a social aspect by considering the knowledge, not only of experienced engineers, but also of workers who work on machines. Finally, the industrial application was done through a proof-of-concept using manufacturing data from the process industry, where the amount of data was reduced by 99.73% without losing significant information contained in big data.

There is no defined methodological approach that would rank the quality goals of a process in uncertain environments, which is one of the basic problems in process management. In this paper, the considered problem is stated as a multi-criteria decision problem. The criteria present performances which are defined by the knowledge and experience of the decision makers. The fuzzy rating weights of each pair of the considered criteria and uncertain criteria values for the defined quality goals are described by linguistic expressions which are modeled by triangular fuzzy numbers. The weights vector of criteria is calculated by the fuzzy Analytic Hierarchical Process (AHP). The extension of the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank quality goals. The proposed model is illustrated by an example.