## 4 Simulation Models and Sustainability: Characterization
### Discrete Event Simulation (DES)
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Criteria** & **DES** & **Effects on Sustainability Assessment** \\ \hline Approach & Process-based & Process-centered sustainability assessment eschews the organizational/systemic view focusing on a given process, e.g., resource flows [92] \\ \hline Object & Entity & Objects in a system are distinct individuals. Limited behavior with the environment, thus does not exhibit emergent behaviors, thus limiting the use in socio-economical contexts. It also cannot capture proactive human centric behavior. Limited ability to adapt the structure at runtime [93]. \\ \hline Space/Time & Discrete & Sequential process models. State changes occur at discrete points of time. Models are simulated in unequal time steps, when ’something happens’ [94]. \\ \hline Feedback & Implicit & Feedback, delays and nonlinearities are not emphasized which in case of sustainability assessment renders strategies as static \\ \hline Randomness & Stochastic & Randomness explicitly modeled with the appropriate statistical analysis, complexity increases exponentially based on the size and requirement [94]. \\ \hline Predictive power & High & High predictive power whereby actual flows are determined, e.g., carbon dioxide emission assessment [95]. The human agents are well-defined decision makers as the output takes form of point predictions. \\ \hline Abstraction level & Meso-Micro & Sustainability assessment at lower individualized functions, e.g., solid waste management [96] \\ \hline Scope & Operational-Tactical & The sustainability assessment for short time range, e.g., integrating human factors in manufacturing with simulation runs of one month [97] \\ \hline Data & Quantitative & Data to be sourced from plant databases which includes energy utilization, emissions, resource utilization, etc. Data from a CNC for energy utilization as an example [98]. \\ \hline Use-case & Optimization, Prediction and bottleneck analysis & Sustainability is conceived within the rubric of optimization. Energy optimization cases are the most common examples [99]. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Major aspects of DES and their efficacy with regards to modeling sustainability. There are 27 articles that deal with simulating sustainability using DES in the industrial context. Some of the studies use DES singly while others make use of the fusion of one or more simulation techniques in addition to DES. Appendix A.1 indicates the recent representative research wherein DES has been used in modeling sustainability in manufacturing and allied SCs. Models using more than one simulation technique are termed hybrid models. The collected articles on DES and sustainability include both pure and hybrid models and can better be characterized by the keyword network of those papers. The keyword network as shown in Figure 11 indicates the thematic constitution of those articles. Most of the articles focused on the operational level with the theme of energy modeling or simulation dominating the aspect taken up by the researchers. In addition to the ones pointed out to in Table A1, one may indicate other studies in contexts including the digital factory concept [100], input data management [101], and water-energy nexus [102], among others. The pre-eminence of energy modeling again points to the fact that DES requires extensive and precise data which are easily available in case of energy use in manufacturing and SCs. Other aspects of sustainability, such as social factors, which show up at higher levels of abstraction do not show up as often in the context of DES. The aspect of sustainability in manufacturing and SC has been studied along various aspects of industrial production in the recent past using DES. Table A1 indicates various case-based studies on different aspects of sustainability that have been undertaken in manufacturing and SCs using DES. The use of software in case of DES has its beginnings in early 1960s when software such as SIMULA, GPSS, and SIMSCRIPT were developed.