## 1 Introduction  
There is beauty in how complex the human body is, yet seemingly how naturally and effortlessly it operates day-to-day. For the untrained eyes, a manufacturing plant can seem such a complicated, yet well-functioning entity. Both have a system which connects faculties of sensing, decision-making, and acting, which is essential for their proper functioning [1]. For the human body, this is obviously the nervous system. For a production facility, this is the _Manufacturing Execution System_, or MES in short. Many definitions and approaches of MES appeared, yet somehow all of them tried to modularize and incorporate every aspect of manufacturing and to combine them into one monolithic system [2]. Thus far, there has not been a minimalist, core concept of MES. One which only has the most basic, _core functionalities_ to execute a manufacturing plan. The aim was to take out every intelligent and decision-making aspects of MES to create a _nervous system for manufacturing_, which connects both low-level resources and their operations together, in addition to linking them to the high-level orchestrators, like a scheduler or an Enterprise Resource Planner (ERP). This approach operates with the expectation that both low- and high-level components have built-in intelligence to enable smart production through the digitalization of their environment. The basis for this expectation is the raising phenomena of Cyber-Physical Systems (CPSs) in the manufacturing shop-floor and the spread of generally accepted distributed decision-making supporting the _Cyber-Physical Production System_ (CPPS) concept [3; 4]. Manufacturing digitalization prevails more and more, and industrialized countries now have their own initiatives to support it [5]. Industry 4.0 (I4.0) is all about integration and digitalization [6; 7], and, given the crucial role of data and Industrial Internet of Things (IIoT) in its technological scenarios, there is a common view that integrated MES are still crucial, although moving toward the broader Manufacturing Operations Management (MOM) and service-oriented approach [8]. Next to this, robotics is expanding in magnitude around the developed world, also in executing manufacturing processes, and is expected to rise from a 15 billion US dollar sector now to 67 billion by 2025 [9]. Overall, I4.0 is demanding a gradual but continuous evolution towards interoperable standards and systems, distributed and self-learning MES services [10]. In this view, modular (not monolithic) MES, with functions becoming services, acquires a central role. Customers in manufacturing require support to multi-plant enterprise orchestration, easy scalability, optimal interplay with modern technologies, and process innovation support through the integration with additive manufacturing, robotics, and Plant Lifecycle Management (PLM) systems. In order to digitally transform industrial automation, significant efforts have to be dedicated to the isolated systems [11]. As I4.0 grows, MES need to grow alongside it [12]. Global networking of production resources and processes, as well as the use of globally interconnected applications, crucially require the adoption of unified standards. _Standardization_ in manufacturing architectures evolved from ISA95 to Manufacturing Enterprise Solutions Association International (MESA) [13] in the past decades and, more recently, to service-oriented industrial reference architectures, such as RAMI 4.0 (Reference Architecture Model for Industry 4.0) [14] and IIRA (Industrial Internet Reference Architecture) [15]. All these have proved their applicability also to MES and CPPS, with the intention to organize, define, and integrate automated functions (services) that can be connected to the _core_. These two major standardization proposals are _de-facto_ considered reference guidelines for conceiving future business organizations, even though a final consensus or agreement in the scientific and industrial communities has not been reached yet.