Assessment, simulation, and decision-making under severe uncertainty in industrial sustainability

In order to achieve long-term sustainability in industrial manufacturing, it is required to look beyond the short-term remedial measures and improve the existing methods of product and plant design drastically. Because of the multi-dimensional nature of sustainability, the development and deployment of multi-objective optimization methodologies are in urgent need. Furthermore, because of the existence of uncertainty, sometimes severe uncertainty is inevitable, it is necessary to account for the uncertainties that are affecting the target system. In this dissertation work, algorithms of multi-objective Pareto optimization under severe uncertainty will be developed as a fundamental research on the theoretical development of sustainability science and engineering.;In the design of chemical/energy production systems, how to quantify the sustainability of the systems and how to use the assessment result to guide design remains very challenging because of the multi-dimensional nature of the indices. Concerns on economic return and environmental impacts have been well received by researchers and practitioners. However, the irreversibility of the process has not been taken into consideration yet. Based on the First and Second Laws of Thermodynamics, exergy analysis allows accounting for irreversibility in the process and provides a detailed mechanism for tracking the transformation of energy and chemicals. This dissertation presents a sustainability assessment method incorporating economic, environmental, efficiency, and societal concerns. In conjunction with a multi-criteria decision-analysis method, this methodology provides critical guidance to the designers. The efficacy of this methodology will be demonstrated through a case study on biodiesel production processes.;Continuous quality improvement and cost reduction are necessary for manufacturing. The quality and cost of a manufactured product are determined to a large extent by the engineering design of the product and its manufacturing process. A major quality concern in electroplating and metal finishing is coating deposit thickness and its uniformity. In production, the coating thickness cannot be measured during plating. Therefore, the coating quality can only be inspected after manufacturing, which is a passive way of quality control. In this work, a process of copper gear rack plating will be simulated to illustrate the efficacy of computer-aided process design for product quality improvement.