\"in the loop\" in a given economy [2]. There is an increased awareness that industrial production and SC activities are one of the principal components of the total carbon emissions. According to a report by the United States Environmental Protection Agency (EPA) they account for 23% of total carbon emissions [3]. As a consequence, there has been an ever-increasing awareness of the need to mitigate the effects of industrialization. This awareness is well reflected in the research community in the recent past which can be gauged from Figure 1. It depicts the prevalence of research with keywords \"Manufacturing\" AND \"Circular economy\" and \"Simulation\" AND \"Circular economy\" on SCOPUS since 2006. Although there has been an increasing interest in the CE, in the present context, a sustained incongruity between the understanding of CE and its actual realization as social, economical, and, environmental performance in manufacturing-based SCs is greatly lacking [4]. This incongruity can be primarily addressed through use of assessment of sustainability measures that are verifiable, communicable, and widely understood. The use of simulation modeling as a tool for assessing and improving the sustainability performance in manufacturing and SC finds a wide acceptance currently [5]. This can be assessed from the increase in the number of studies in the recent past as shown in Figure 1.  
Modeling sustainability in the industrial context covers various aspects of manufacturing and SCs such as in warehousing, logistics, production planning, and resource allocation while invoking various facets of sustainability such as waste elimination, energy efficiency, resource efficiency in manufacturing and SC [6]. The three major simulation tools used to model manufacturing and their allied SCs include Discrete Event Simulation (DES), Agent-Based Simulation (ABS), and System Dynamics (SD). The locales, contexts, and rationale of their application in manufacturing and SCs, although intersecting to a good degree, are diverse and well cut out. These rationales and contexts have in the recent past been expanded into the realm of sustainability analysis. While taking into account their extensive use, they are beset with a number of limitations vis-a-vis the model magnification, data requirements, model validation, and granularity. Doing away with the limitations and anticipating the benefits of combining two or more simulation techniques (such as DES+ABS, ABS+SD, SD+DES, ABS+DES+SD), hybrid techniques find a prominent use in the realm of sustainable manufacturing and SCs. A number of computer-based Modeling and Simulation (M&S) tools are widely available with some of them paid and licensed while others free and open source. This article catalogs some of the free-to-use software in the case of each M&S technique. The literature is rife with numerous techniques that are employed in formulating the simulation models and they are quite diverse unlike the application of  
Figure 1: Articles published within CE framework in contexts of manufacturing and simulation. The figure presents the evolution of research in the fields of CE in manufacturing and simulation and CE. The field of sustainability simulation is a fairly new aspect but there has been a steady increase in research in the past few years. the models themselves. However, a framework wherein these techniques are characterized and brought together with respect to their actual application is severely lacking. The industry is on the cusp of a new revolution termed as Supply Chain 5.0 (SC 5.0). SC 5.0 seeks to realign the goals of industry from formerly technology-driven growth to value-driven sustainable growth [7]. The SC 5.0 is less of a new technological paradigm and more of an assimilatory philosophy wherein the current technologies are redirected in service of sustainable production and consumption.