## 5 Discussion  
This section is divided into two parts. First, we focus the discussion on the meta-model applied in the simulation prototype and the case study, and later on, we drive the attention to the approaches adopted and the proposed methodology from an industry 4.0 perspective and focus on geometric variability control. Regarding the case study, the instantiated models and simulations to analyze different control logics for geometric variability reduction have shown different positive aspects:  
* Validity of the meta-model. The correct construction, compilation, and simulation of the instances demonstrate the correct structuring and implementation of the meta-model. Moreover, it has been proven that the modular structure of the meta-model allows to build executable simulation models in a few minutes and in a very intuitive way. * Multi-domain simulation approach. It has been proven that a multidomain global assessment is necessary to conduct an adequate analysis in MAS. For instance, according to the results in the best case scenario, the quality improvement increased the number of parts within specifications and the number of parts manufactured decreased with respect to other alternatives. Thus, an analysis to prioritize productivity would have provided a different alternative. * Flexible simulation. The model instantiation supports the simulation of assembly lines with an interesting level of detail, allowing the introduction of various characteristics and behaviors of the process and obtaining realistic and reliable results. Moreover, the flexible and modular structure is aimed to facilitate the extension of the model to incorporate new block types, such as the consideration of new strategies (e.g., selective assembly) and logic control (e.g., based on establishment of optimal number and placement of inspection stations). For this reason, Modelica and the proposed libraries are a great potential resource for the analysis of assembly lines at the design stage. On the other hand, the experience using the proposed methodology has proven that the use of SysML is a key element in the simulation system modelling since its block-based structure may be rewritten quite easily into Modelica formalism. However, recent research works point out the need to advance in some aspects, such as the automatic validation of SysML models, the automatic transformation SysML-Modelica, etc. As these advances are reflected in the new versions of the standards published by the Object Management Group and Modelica groups, the industry will tend to adopt similar approaches to the one proposed in this work. During this work, we have stated the lack of alignment of SysML diagrams to discrete manufacturing systems, as it has been reported [28]. Therefore, the development of normative SysML profiles that consider the modelling of manufacturing systems from different points of view (different types of analysis) and the development of standard libraries for these manufacturing entities is still an open issue. Furthermore, the normative developments on SysML should make some progress and include all aspects required for an integrated modelling process of a product-process-manufacturing system (e.g., MAS). This is pointed out in [29] due to the clear evidence of the strong interdependence that exists between a product and its production system, especially when dealing with geometric variability models during product, process, and manufacturing systems lifecycles. SysML and Modelica have shown their ability to represent simplified product geometries (lightweight models) and tolerances [21; 30; 31]. Another remarkable aspect of the SysML and Modelica languages that makes them suitable for our goals is that they promote the decomposition of complex systems into discrete components and subsystems that are later integrated into a system model, allowing composition of high-scale and low detail (lightweight) models, such as the one proposed in this paper and others of smaller scale and higher detail to form a virtual prototype and a digital twin.