Despite the plethora of literature in sustainability and supply chain management in the recent years, a quantitative tool that measures the sustainability performance of an industrial supply network, considering the uncertainties of existing data, is hard to find. This conceptual paper is aimed at establishing a quantitative measure for the sustainability performance of industrial supply networks that considers aleatory and epistemic uncertainties in its environmental performance evaluation. The measure is built upon economic, environmental and social performance evaluation models. These models address a number of shortcomings in the literature, such as incomplete and inaccurate calculation of environmental impacts, as well as the disregard for aleatory and epistemic uncertainties in the input data and, more importantly, the scarce number of quantitative social sustainability measures. Dyadic interactions are chosen for the network, while the network members have a revenue-sharing relationship. This relationship promotes sharing of the required information for the use of the proposed model. This measure provides an approach to quantify the environmental, social and economic sustainability performances of a supply network. Moreover, as this measure is not specifically designed for an industrial sector, it can be employed over an evolving and diverse industrial network.

FMEA (Failure Modes and Effects Analysis) is a method to analyze potential reliability problems in the development cycle of the project, making it easier to take actions to overcome such issues, thus enhancing the reliability through design. FMEA is used to identify actions to mitigate the analyzed potential failure modes and their effect on the operations. Anticipating these failure modes, being the central step in the analysis, needs to be carried on extensively, in order to prepare a list of maximum potential failure modes. However, the information stored in risk assessment tools is in the form of textual natural language descriptions that limit computer-based extraction of knowledge for the reuse of the FMEA analyses in other designs or during plant operation. To overcome the limitations of text-based descriptions, FMEA ontology has been proposed that provides a basic set of standard concepts and terms. The development of the ontology uses an upper ontology based on ISO-15926, which defines general-purpose terms and act as a foundation for more specific domains. The ontology is developed so that engineers can build new concepts from the basic set of concepts. This paper evaluates the proposed ontology by means of use cases that measure the performance in finding relevant information used and produced during the safety analyses. In particular, the extraction of knowledge is performed using JTP (an object oriented modular reasoning system) that is used for querying the ontology.

Agent structure has been proposed and used in a multiagent system with the logic and aim of safety engineering by the means of faulty diagnosis diagram to enhance the risk assessment method disadvantages such as shortcoming of FMEA in complex systems or with a process with numerous components. However there are several new concepts to improve the multi agent system engineering based on one or more risk assessment method, the presented research is only in a dawn and for instance as a proposition, employing ZEUS to design the multi agent system is one option for more efficient, and agile way of designing and creating multi agent system to shift the focus on safety aspect instead of information technology.