Search

In this study, we address robust-reliable decision-making approach to select benchmark platforms to develop the automotive family. Activities studied included selecting the appropriate decision-making method, simulating possible scenarios to determine the relative importance of attributes by experts and stakeholders, determining the decision space and valuing attributes based on databases and Knowledge discovery in databases (KDD) techniques, statistical analysis and sensitivity assessment. The robust-reliable decision is made using the Simple Additive Weighting (SAW) method for 6223 unique cases of expert judgments and stakeholder expectations. The database used to determine decision space and attributes values included 546 automobiles designed in 11 different segments based on 34 platforms. This has led to the reliable selection of five benchmark platforms with the highest level of desirability in terms of defined attributes and the greatest robustness to uncertainties in the expert judgments and the level of expectations of stakeholders.

In this paper, a new methodology was proposed for finding optimal robust-reliable parameter values of a space-based earth observation (SEO) mission based on a predefined multi-purpose platform considering influential uncertainties and human judgment. A deterministic optimization was performed using an evolutionary algorithm on the basis of platform capability and mission-required performance, simulated by a dynamic simulation-based model. A set of non-dominated solutions with different behaviors emerged. Then, samples of these solutions were selected and an uncertainty analysis was carried out. After that, a multiple attribute decision-making (MADM) problem was formed with two groups of attributes related to constraints violations and variation of objective function value having unknown weights. Dominant ranking of the non-dominated solutions was obtained by simulating this MADM problem for adequate times with different random weights (human judgment effects). In the next step, given the outputs obtained from solving MADM problem, an optimal robust-reliable solution could be determined utilizing two approaches, response surface methodology (RSM) and forming a new uncertainty-based multidisciplinary design optimization (UMDO) problem. The results showed that utilizing MADM approach not only brings the effects of human judgment into design problem but also accelerates convergence to optimal robust-reliable solution in multimodal problems by bounding the search space without any risk regarding getting stuck in local optimal regions.

With growing interest in low-cost, high performance and short time-to-flight satellites, the idea of using multi-purpose satellite platforms has drawn many attentions. However, under certain conditions in which the required capability of a mission is slightly more than the capabilities of a specified variant of a multi-purpose platform, it must jump to the next higher capability variant. Correspondingly, lots of unnecessary performance or capability might be imposed. In this paper, the main goal is to minimize the wasted performance in the design of an Earth Observation (EO) satellite based on a multi-purpose platform. To this end, a dynamic simulation-based model has been developed with the capability of simulating the satellite performance characteristics, EO mission requirements and supportable performance by the platform under various circumstances and throughout the satellite lifetime. To minimize the wasted performance we face with an optimization problem containing a complicated non-linear, non-convex and multi-modal design space which is enveloped by constraints of the mission requirements and supportable performance of the platform. A novel criterion as an objective function has been introduced aiming at the incompatibility reduction between the capabilities of a certain multi-purpose platform variant and the EO mission requirements. This objective function considers all the performance variations during the entire mission lifetime rather than solely the worst case. Through this, the mission and orbital characteristics have been determined by which there would be no need to jump to the higher performance variant in order to satisfy the EO mission requirements.

In this paper, a sampling-based framework for reliability-based design optimization problems has been developed to provide a comprehensive structure adaptable to MCS methods such as importance sampling strategy. This framework has the capability of adopting any reliability analysis by decoupling two integral parts of a RBDO algorithm: reliability analysis and optimization problem. A shifting vector strategy has been proposed what imposes the constraints to immediately satisfy the reliability requirements. The main advantage of this framework is its independency on the approximation of the constraints since it aims at finding an optimum shifting vector based on the probability density function of the constraints themselves.

One of the most important aspects of a successful space mission is the transition to the correct orbit and maintaining it. As a result, many modern orbit transfer techniques have been developed in space industry in order to accomplish this task in a more reliable and less expensive way. However, when it comes to the design of student satellites, usually there are serious limitations on the financial resources, technical database and satellite industry experts. These limitations may compromise the access to advanced methods and techniques. Therefore, reliability and expenses may no longer be the only criteria to be met in the process of design. As a result, at each step of the design, a decision should be made by the designer (student), which is not exclusively based upon system reliability and cost. The decision should also take into account criteria such as technology accessibility, implementation and integration issues, regarding the available or affordable equipment. Therefore, the process of design of a student satellite could be different from that of a commercial satellite. Furthermore, it is very likely for a team of students who try to follow standards and design criteria of industrial satellites to be disappointed after all. In some cases, students consider outsourcing parts of the design process. In this case, the creativity and innovation of the student team might be compromised by the industrialized routine procedures. Therefore, in order to achieve a genuine student design, a different approach should be adopted in the process of the design and the decision making process. This paper is the result of this approach in choosing an optimal propulsion system for a student satellite.