Lifetime distributions, such as Weibull and log-logistic distributions, are critical for parametric and semi-parametric analysis in reliability engineering. This article promotes a promising but understated distribution, q-Weibull distribution, to the reliability engineering community by providing new perspectives and demonstrating potential applications. We interpreted the physical meanings of the parameter “q” from multiple perspectives, including internal interactions in nonextensive mechanics, dependence among components in a series system, and the frailty (heterogeneity) in field failure data. Also, we showed that q-Weibull distributions belong to a closed function family under three different operations: minimal ordered statistics, accelerated failure time and proportional hazards for modeling accelerated life test data. Then, q-Weibull distributions are found to be an interpolation between Weibull and log-logistics distributions, and an interpolation between Weibull and Power law distributions. Moreover, this article presented a new approach to estimating parameters more accurately and robustly, by combing maximum likelihood estimation and robust linear regression. Finally, q-Weibull distributions show superior performance for a list of reliability applications, such as modeling lifetime, material strength, accelerated life test, frailty in field failure data, repairable systems, and reliability growth. To promote wider usage of this lifetime distribution, we open source all the codes for parameter estimations and reliability applications and all the datasets collected.

The development of product becomes increasingly collaborative and parallel, which makes the need for design reuse more critical. This paper proposes a framework to enable effective development of complex product by supporting the management of design knowledge, which refers to metadata, structural, functional and behavioral information. The multi-level knowledge represented by Base Object Model can be seen as special cases of web services, as BOMs are fundamentally XML documents. Surrounding the effective management of knowledge, the method for the retrieval of multi-level knowledge is developed including the process of retrieving, matching and assembling. Since the knowledge is stored in the form of a tree structure, the depth-first search (DFS) and breadth-first search (BFS) are applied to the retrieval algorithm and similarity is used to calculate the match degree. The framework is implemented in the development of an example missile, which demonstrates that its useful for the re-use of design knowledge.

In order to improve the efficiency of multi-resolution modeling and simulation, Base Object Model (BOM) based multi-resolution model for federated simulation is proposed in this paper. The whole process includes conceptual modeling design, component design, component assembly and federal simulation. BOM-based conceptual models are divided into two categories: basic BOM and the Resolution Related BOM (RR-BOM). Four-Step Modeling method is applied for those two types of BOMs. The completed BOMs are converted to their corresponding component implementations (BCIs). BOM library and BCI library are set up for model reuse. During the components assembly and federated simulation, Dual Engine Simulation (DES) is designed for multi-resolution simulation. Each federate has an Internal Exchange Service Server (IESS) for the internal component management. IESS provide time management, data management, resolution control and other services. The external supporting environment is Run Time Infrastructure (RTI). This method of modeling and simulation has been applied in industrial projects and greatly improved the efficiency for multi-resolution modeling for federated simulation.

Multidisciplinary collaborative simulation is a new paradigm to enhance the analysis of complex engineering systems more accurately in the systematic level, which enabling the interaction of subsystems models constructed by different CAE software tools in a time-synchronized and high fidelity way. This paper presents a modular method to implement the multidisciplinary collaborative simulation for complex engineering systems in a distributed environment. The modular decomposition is based on the configured subsystems in engineering intuition of corresponding disciplines. The global system is described by inter-connections between subsystems with block representation, thus the different simulation modules are interrelated with the corresponding inputs and outputs. The modular simulation approach allows for independent and parallel modeling of each subsystem and has the advantages of a better modularity. A component-based infrastructure is proposed to integrate the distributed, heterogeneous CAE tools. A modular simulation system which can support the integration of distributed simulation models at run-time is developed, involving the implementation technologies of interrelated modules, disciplinary model transformation and simulation time advancement. Modular modeling and simulation of a rolling stock is demonstrated as a typical case study. Numerical results of the modular simulation demonstrate the effectiveness of this approach to multidisciplinary collaborative simulations for complex engineering systems.