Several fields of knowledge have been invited to collaborate on production systems, in order to (a) answer to a growing system complexity, (b) offer organizations holistic solutions, and (c) obtain more resilient results to future changes. Examples of this are the collaborations between simulation, machine learning, and data engineering with multiple domains, for example production system – the focus of this research. Hence, this research aims to provide a holistic view of production systems, characterizing the key processes and concepts of production systems, to offer a clear and integrated understanding for newcomers into this field. The main processes are examined, such as: Production planning and control, Industrial processes, Logistics, Quality management, Maintenance, and Sustainability. The latter is structured around three core dimensions: environmental, social, and governance (ESG), representing an emerging differentiator among organisations. One notable example is green manufacturing, which focuses on minimising waste and promoting sustainable practices throughout the production process. Moreover, different production system models are reviewed, such as: Lean manufacturing, Just-in-time, and Mass production. At the end, a detailed analysis of each of these processes and models is provided, highlighting the relevance of a strategic and sustainable approach to success in contemporary production systems, promoting their optimization.