... an optimization framework for disassembly sequence planning under uncertainty considering human–robot collaboration. The proposed framework combines three attributes: disassembly cost, safety, and complexity of disassembly, namely disassembleability, to identify the optimal disassembly path and allocate...

... with EMD, an angle metric is developed as an alternative of the area metric to reduce the misjudgment rate of model validation. In order to quantify the uncertainty due to insufficient experimental and simulation data, the angle metric is further extended to a new interval angle metric, namely the interval...

... reliability system Bayesian method uncertainty optimization reliability in design simulation-based design systems design uncertainty analysis For many system design problems, it is crucial to predict the reliability of the system under design. The reliability prediction can help not only...

... a system’s total lifetime value by reducing sensitivity to requirement changes and truncating change propagation. Quantitatively studying excess margin beyond what is required for known uncertainties has been particularly challenging as information is needed about how requirements change, how system...

...Yixuan Liu; Chen Jiang; Zissimos P. Mourelatos; David Gorsich; Paramsothy Jayakumar; Yan Fu; Monica Majcher; Zhen Hu This paper develops a simulation-based mission mobility reliability (MMR) analysis framework to account for uncertainty in mobility prediction of off-road ground vehicles in mission...

... and experiments). New samples are often selected based on the estimated uncertainty in the design space. While some surrogates such as kriging have readily available uncertainty models for their predictions, other surrogates do not. Consequently, there have been studies of using the process of leaving-samples-out...

... want to supplement point forecasts with prediction intervals to assess future uncertainty and make contingency plans accordingly. However, prediction intervals generation for technology evolution has received scant attention in the literature. In this paper, we develop a generic method that uses...

...Young Kap Son; Gordon J. Savage This paper presents a novel approach to determine the stability space of nonlinear, uncertain dynamic systems that obviates the traditional eigenvalue approach and the accompanying linearizing approximations. In the new method, any long-term dynamic uncertainty...

... June 11, 2014. Assoc. Editor: Qi Fan. 04 10 2013 05 04 2014 In operation, wind turbine gearboxes (WTGs) are subjected to variable torsional and nontorsional loads. In addition, the manufacturing and assembly process of these devices results in uncertainty in the design parameters...

... ] . The uncertainty domain can be expressed as a convex model (20) [ R - 6 , S - 5 . 25 ] [ 1 . 042 - 0 . 2778 - 0 . 2778 1 . 852 ] [ R - 6 S - 5 . 25 ] ≤ 1 It is known that the reliability domain of the structure under...

.... References [1] Haldar , A. , and Mahadevan , S. , 2000 , Probability, Reliability, and Statistical Methods in Engineering Design , Wiley , New York . [2] Picheny , V. , 2009 , “ Improving Accuracy and Compensating for Uncertainty in Surrogate Modeling ,” Ph.D. thesis, Aerospace...

.... The resulting uncertainty must be accounted for in the decision-making process. This paper proposes a method for estimating the environmental impact of a product’s life cycle and the associated degree of uncertainty of that impact using information generated during the design process. Total impact is estimated...

... . 10.1016/j.cma.2006.12.008 Missoum , S. , 2007 , “ Controlling Structural Failure Modes During an Impact in the Presence of Uncertainties ,” Struct. Multidiscip. Optim. 1615-147X , 34 ( 6 ), pp. 463 – 472 . 10.1007/s00158-007-0100-z Basudhar , A. , Missoum , S...

...Subroto Gunawan; Panos Y. Papalambros In engineering design, information regarding the uncertain variables or parameters is usually in the form of finite samples. Existing methods in optimal design under uncertainty cannot handle this form of incomplete information; they have to either discard some...

... is proposed that matches the first two moments of interrelated responses and linking variables. Several implementation issues are addressed, including representation of probabilistic design targets, matching responses and linking variables under uncertainty, and coordination strategies. Analytical...

...Raphael T. Haftka; Raluca I. Rosca; Efstratios Nikolaidis To address the need for efficient and unbiased experimental testing of methods for modeling uncertainty that are used for decision making, we devise an approach for probing weaknesses of these methods by running numerical experiments...

... uncertainty is presented. First, Bayes’ formula is used in conjunction with information extracted from the Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), component reliability, and prior system knowledge to construct the Component-Indication Joint Probability Matrix (CIJPM). The CIJPM...

.... This application is a preliminary study, and focuses on the collaborative optimization feature of the DBCO framework. The issues of propagated uncertainty are neglected in this study. The utility of profit is assumed to be the profit itself. Hence the objective of the resulting deterministic optimization...