000			02663nam a2200217Ia 4500
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020			_a9780471284963
041			_aeng
082			_a620.0042 _bJON-D
100			_aJones, John Chris _960519
245			_aDesign methods/ _cby John Chris Jones
250			_a2nd ed.
260			_aNew York: _bJohn Wiley, _c1992.
300			_alxiv, 407 p.
490			_aStructures and infrastructures series, v. 7.
505			_a1. Design decision under uncertainty -- 2. Overview of theories of uncertainty and tools for modeling uncertainty -- 3. Objective probability -- 4. Statistical inference : constructing probabilistic models from observations -- 5. Probabilistic analysis of dynamic systems -- 6. Subjective (Bayesian) probability -- 7. Decision analysis -- 8. Multiattribute considerations in design.
520			_a"Reliability methods are becoming increasingly popular in engineering design because they help build safer and more efficient products than traditional deterministic methods. A principal challenge in using these methods in practical design problems is to model uncertainty when little data is available and the underlying mechanism of uncertain events is unknown. There is a need for an integrated presentation of tools for modeling uncertainty and making design decisions under severe uncertainty, which bridges the gap between theory and practice for methods for design under uncertainty. This work presents and compare the most important theories for modeling uncertainty and explains what tools are most suitable for a given design problem. It illustrates how to solve practical design problems in the aerospace and automotive engineering industries with a balanced approach explaining both the theoretical foundations of methods and their application to engineering design. The numerous examples in each section will help to appreciate the importance of design under uncertainty and the theoretical developments of the methods. Readers will learn a structured, risk-based approach for design under uncertainty when limited information is available, which tools are available and which to select and apply given a design decision problem. They will further understand how to improve their overall performance using a structured, risk-based approach for design under uncertainty. Intended for mechanical and civil engineers working in aerospace, automotive, civil, shipbuilding and power engineering, and for graduate level courses and students in reliability analysis and design and decision-making under uncertainty"--
650			_aAR _959235
942			_cBK
999			_c1535 _d1535