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Generalized Industrial Sustainability Analysis and Decision-Making Framework: A Discrete Event Control Based Approach

Cristina Piluso, Wayne State University, 5050 Anthony Wayne Dr., Detroit, MI 48202 and Yinlun Huang, Department of Chemical Engineering and Materials Science, Wayne State University, 5050 Anthony Wayne Dr., Detroit, MI 48202.

The study of industrial sustainability is highly complex. It is quite difficult to evaluate how an individual facility, industry, or industrial zone ranks on the issue of sustainable development, how to determine where these entities should be in the future, and most importantly, how to achieve this future goal of sustainable development. Additionally, the idea of industrial sustainability is highly uncertain, where the required knowledge, models, and data necessary for a meaningful sustainability evaluation are often uncertain, incomplete, and imprecise. As a result, the question of how to approach a sustainable development problem and possessing the ability to make an effective sustainability-focused analysis is extremely difficult.

As such, there is a great need for a generalized methodology that is capable of describing and characterizing a large-scale sustainable development problem and providing best estimates and scenario-based decision-support based on the available data, under the above-mentioned complexities and uncertainties. The methodology should also be capable of modeling from a systems view, i.e., create a cause/effect relationship among the member entities of a large scale problem, to identify methods of making the system more sustainable.

This paper provides a systematic approach to the study a sustainable development problem by introducing a generalized industrial sustainability analysis and decision-making framework. The general format of the proposed methodology is by resorting to the concept of discrete-event system control. Note that sustainability cannot be controlled. On the contrary, sustainability can be guided through educated and well-informed decision-making, which is the focus of the proposed framework. The framework begins by categorizing various system disturbances, which could include market demand fluctuations, the introduction or modifications of governmental policies or regulations, etc. These disturbances must be taken into account during the systems-based modeling and simulation stage of the framework. The flow of information gained through this process is then passed along to an assessment stage of sustainable development, where the indicators of industrial sustainability are measured. Lastly, as the quantitative assessment is completed, the information flows to the final block, the sustainable development decision-making step. Here, the indicator values are compared to the goals or targets set by the industrial leaders for each indicator. Based on the deviation from the target value, specific techniques can be applied, which present the industrial decision-makers the abilities and security in making sound and reliable decisions that will further guide the industrial region to a state of improved sustainable development.

Overall, the industrial sustainability analysis and decision-making methodology provides industrial decision makers with the necessary decision-making abilities, which in turn provides the necessary adjustments to the system and ultimately affects the zone's industrial sustainability in a positive manner. It also provides the decision-makers with the abilities and security in making sound and reliable decisions that will further guide the industrial region to a state of improved sustainable development. Using this methodology, one is capable of improving the industry's environmental, economic, and societal performance through management decisions. To display the efficacy of the methodology, it will be applied to a large-scale, multi-industry case study. The case study will utilize the systematic approach to model, quantify, analyze, and provide decision-support to the decision-makers within the industrial zone.