Risk And Uncertainty Reduction By Using Algebraic Inequalities
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Risk and Uncertainty Reduction by Using Algebraic Inequalities
This book covers the application of algebraic inequalities for reliability improvement and for uncertainty and risk reduction. It equips readers with powerful domain-independent methods for reducing risk based on algebraic inequalities and demonstrates the significant benefits derived from the application for risk and uncertainty reduction. Algebraic inequalities: • Provide a powerful reliability improvement, risk and uncertainty reduction method that transcends engineering and can be applied in various domains of human activity • Present an effective tool for dealing with deep uncertainty related to key reliability-critical parameters of systems and processes • Permit meaningful interpretations which link abstract inequalities with the real world • Offer a tool for determining tight bounds for the variation of risk-critical parameters and complying the design with these bounds to avoid failure • Allow optimising designs and processes by minimising the deviation of critical output parameters from their specified values and maximising their performance This book is primarily for engineering professionals and academic researchers in virtually all existing engineering disciplines.
Interpretation of Algebraic Inequalities
This book introduces a new method based on algebraic inequalities for optimising engineering systems and processes, with applications in mechanical engineering, materials science, electrical engineering, reliability engineering, risk management and operational research. This book shows that the application potential of algebraic inequalities in engineering and technology is far-reaching and certainly not restricted to specifying design constraints. Algebraic inequalities can handle deep uncertainty associated with design variables and control parameters. With the method presented in this book, powerful new knowledge about systems and processes can be generated through meaningful interpretation of algebraic inequalities. This book demonstrates how the generated knowledge can be put into practice through covering the algebraic inequalities suitable for interpretation in different contexts and describing how to apply this knowledge to enhance system and process performance. Depending on the specific interpretation, knowledge, applicable to different systems from different application domains, can be generated from the same algebraic inequality. Furthermore, an important class of algebraic inequalities has been introduced that can be used for optimising systems and processes in any area of science and technology provided that the variables and the separate terms of the inequalities are additive quantities. With the presented various examples and solutions, this book will be of interest to engineers, students and researchers in the field of optimisation, engineering design, reliability engineering, risk management and operational research.
Reverse Engineering of Algebraic Inequalities
The second edition of Reverse Engineering of Algebraic Inequalities is a comprehensively updated new edition demonstrating the exploration of new physical realities in various unrelated domains of human activity through reverse engineering of algebraic inequalities. This book introduces a groundbreaking method for generating new knowledge in science and technology that relies on reverse engineering of algebraic inequalities. By using this knowledge, the purpose is to optimize systems and processes in diverse fields such as mechanical engineering, structural engineering, physics, electrical engineering, reliability engineering, risk management and economics. This book will provide the reader with methods to enhance the reliability of systems in total absence of knowledge about the reliabilities of the components building the systems; to develop light-weight structures with very big materials savings; to develop structures with very big load-bearing capacity; to enhance process performance and decision-making; to obtain new useful physical properties; and to correct serious flaws in the current practice for predicting system reliability. This book will greatly benefit professionals and mathematical modelling researchers working on optimising processes and systems in diverse disciplines. It will also benefit undergraduate students introduced to mathematical modelling, post-graduate students and post-doctoral researchers working in the area of mathematical modelling, mechanical engineering, reliability engineering, structural engineering, risk management, and engineering design. .