A Fuzzy-Logic-Based Triple-A Template for Industrial Sustainability Enhancement

Industrial sustainability is pursued to achieve the long-term sustainable development (SD) of a given industrial system that could be defined as a network of industrial sectors, each composed by a number of entities. Industrial sustainability problems are always difficult to be thoroughly investigated and further optimized, because of the problem size and scope that carry highly complexity and inherent uncertainty that are associated with data, information, and knowledge. Therefore, current industrial practices on industrial sustainability enhancement are mostly scenario based, where the enhancement strategies are heuristically generated and improved until the degree of sustainability of the system has been increased based on the criteria selected by the involved parties.

One of the major challenges in industrial sustainability research is how to effectively handle uncertainty. In this paper, a fuzzy-logic-based Triple-A Template that can be used to conduct more effective sustainability studies in three consecutive steps: Assessment, Analysis, and Action. First, a fuzzy-logic-based multilayer sustainability assessment is applied to a given industrial zone system problem. With carefully defined fuzzy sets for the triple bottom lines (i.e., economic, environmental, and social sustainability), the sustainability status of the zone can be appropriate determined under uncertainties of various types. The assessment gives the classified sustainability status of not only at the industrial zone level, but also its subsystems. Then, the industrial zone's sustainability problem is analyzed by the approach of design of experiments in order to determine systematically the causes of those poor aspects of sustainability and the relationships among them. In the last step, potential actions will be proposed on the identified causes. Instead of proposing limited numbers of strategies heuristically and comparing their associated scenarios, general action strategies are taken in the proposed methodology and fuzzy logic based optimization is further applied based on the relationships derived before to obtain enhancement strategies under given constraints and uncertainties.

The main advantage of the introduced methodology is its capability of effectively and systematically identifying the optimal enhancement strategies for a given industrial system problem under uncertainties. The methodological efficacy will be illustrated through analyzing the sustainability issues and developing strategies for enhancing the sustainability of an automotive manufacturing centered industrial zone.