The analysis and design of engineering systems based on only the first law is not adequate [1].
This paper introduces a systematic methodology for life cycle management of complex engineering systems, based on the interaction between dynamic system models and dynamic models of damage propagation.
Especially, during health diagnosis modeling of engineering systems, based on data-driven method, acquired data is expected to contain clusters that can be used to differentiate multiple system health conditions.
The article describes an automated system of support of decision-making structures in the synthesis strategies of industrial engineering systems, based on the method of structural and technological complexity of produced parts.
In this paper, a new risk assessment framework is developed to improve the fidelity and consistency of prioritisation of components of complex offshore engineering systems based on expert judgement.
It is an extension of the paradigm of constrained objects which provides a principled approach to modeling complex engineering systems based upon two main principles: a compositional specification of the structure of the system, using objects, and a declarative specification of its behavior, using constraints.
Engineering systems based on fluidized bed combustion, enhanced oil reservoir recovery, underground spreading of chemical waste, enhanced natural gas combustion in an inert porous matrix and chemical catalytic reactors are just a few examples of the applications of this interdisciplinary field.
To develop an eco-engineering assessment system based on these parameters, we used a matrix of the ratios of comprehensive cost to comprehensive profit (RCC/CP), where the RCC/CP index matrix WCC/CP is defined as the index optimization matrix of CC divided by the index optimization matrix of CP.
The context of our work is the study of the engineering and manufacturing system based on the assembly features.
This study proposes an expert system, which is called hybrid Kansei engineering system (HKES) based on multiple affective responses (MARs), to facilitate the development of product form design. HKES is consists of two sub-systems, namely forward Kansei engineering system (FKES) and backward Kansei engineering system (BKES).
