(650f) Evaluation of Sustainable Management Strategies for the Plating Industry Using Fuzzy Logic and Sensitivity Analysis

Sustainable development refers to a continuous process of improvements that must be followed in order to achieve a state of sustainability. More practically, sustainable development looks to simultaneously achieve the triple bottom lines of sustainability, a need to: i) to create more value, wealth, and profits in the economically viable dimension, ii) to provide cleaner products with less raw resource consumption and waste generation in the environmentally compatible dimension, and iii) to have more socially benign products, services, and impacts in socially responsible dimension.[1]

Industrial sustainability is a vital issue in pursuing the long-term sustainable development of a given industry, which is closely related to the material efficiency of an industrial zone, region, or beyond. Despite comprehensive concerns and considerable efforts toward sustainability, many industrial activities have profound impacts not only on people's quality of life, but also to the global environment and economy. Industrial sustainability is, therefore, a very important issue in which the improvement of the efficiency of material and energy usage becomes beneficial to the sustainable development of an industrial system. The size and scope of an industrial sustainability problem is large, therefore, sustainable decision-making, which involves decisions at the local, regional, or national levels, often involves complex and ill-defined parameters with a high degree of uncertainty due to incomplete understanding of the underlying issues.[2] In order for such improvements to be successfully implemented within an industrial zone, the industrial leaders must possess accurate decision-making abilities. Thus, in attempting to model the sustainable development of an industrial zone, a methodology for the characterization and management of data uncertainty is necessary to provide more information and is vital for improved decision-making abilities.

Although many methods for the assessment of sustainability have been proposed, this paper will implement the combined use of the Sustainability Assessment by Fuzzy Evaluation (SAFE) model, which uses fuzzy logic reasoning and basic indicators of environmental integrity, economic efficiency, and social welfare to quantify measures of sustainability at the local, regional, or national levels, along with the sensitivity analysis of the SAFE model, which analyzes and identifies the most important factors contributing to sustainable development. This approach can be implemented to appropriately handle the aforementioned data uncertainties and provide a sound basis for rigorous sustainability decisions to be made. Although this approach has been applied to evaluate the sustainability of an entire nation, this work looks to assess the sustainability of an industrial region or zone.

The combined use of fuzzy logic and sensitivity analysis allows for the systematic evaluation of various sustainable management strategies and therefore permits the proposal of various strategies that successfully aid in the sustainable development of the industrial region. In order to do so, it is necessary to have a tool capable of measuring sustainability (i.e. the SAFE model) and another able to determine the effects that a change in a decision parameter will have on system performance (i.e. assess the results of the policy and determine whether or not the region is on a sustainable path), which the sensitivity analysis provides. Sensitivity analysis is critical to successful decision-making abilities since it studies the dependency of industrial sustainability indicators on various industrial policies and regional decisions.

The approach will be applied to an industrial plating case study to quantify and analyze the state of industrial sustainability within an industrial region, whereby recommendations for future policies and actions that would increase the values of the indicators identified as promoting or decrease the values of those identified as impeding sustainability can be made.

[1] Odum, H. T., Environmental accounting: Emergy and Environmental Decision Making, New York: John Wiley & Sons, 1996. [2] Andriantiatsaholiniaina, L. A., V. S. Kouikoglou, and Y. A. Phillis. Evaluating Strategies for Sustainable Development: Fuzzy Logic Reasoning and Sensitivity Analysis. Ecol. Econ. 2004, 48, 149-172.