Entity

Time filter

Source Type

Needham, MA, United States

PTC, Inc. is a U.S.-based computer software company specializing in 2D & 3D design software, product lifecycle management , and service management solutions. Its core product lines are PTC Creo , PTC Windchill , PTC Mathcad , PTC Integrity , PTC Servigistics, and PTC Arbortext . Wikipedia.


Mo Y.,Zhejiang Normal University | Xing L.,University of Massachusetts Dartmouth | Amari S.V.,Parametric Technology (PTC)
IEEE Transactions on Reliability | Year: 2014

Many practical systems are phased-mission systems (PMSs), where the mission consists of multiple, consecutive, and non-overlapping phases of operation. An accurate reliability analysis of a PMS must consider statistical dependence of component states across phases, as well as dynamics in system configurations, success criteria, and component behavior. This paper proposes a new method based on multiple-valued decision diagrams (MDDs) for the reliability analysis of a non-repairable binary-state PMS. Due to its multi-valued logic nature, the MDD model has recently been applied to the reliability analysis of multistate systems. In this work, we present a novel way to adapt MDDs for the reliability analysis of systems with multiple phases. Examples show how the MDD models are generated and evaluated to obtain the mission reliability measures. Performance of the MDD-based method is compared with an existing binary decision diagram (BDD)-based method for PMS analysis. Empirical results show that the MDD-based method can offer lower computational complexity as well as a simpler model construction and improved evaluation algorithms over those used in the BDD-based method. © 2014 IEEE. Source


Amari S.V.,Parametric Technology (PTC)
International Journal of Performability Engineering | Year: 2012

Many fielded systems use cold standby redundancy as an effective system design strategy. However, methods for analyzing the reliability of k-out-of-n cold standby systems, particularly with components having age-dependent hazard rates, are limited. In this paper, using the concepts of counting processes, we propose an efficient method to evaluate the reliability of k-out-of-n cold standby systems. This proposed method considers Erlang distributions for component lives and the effects of switch failures on system reliability. The main advantage of this counting process-based method is that it reduces a complex problem involving multiple integrals into an equivalent simple problem involving one-dimensional convolution integrals. We consider the Erlang distribution for three reasons: (1) it can be used to model either constant or increasing hazard rates, (2) it can be used to approximate several component failure time distributions, and (3) it has well established closed-form expressions for calculating the convolutions that are used in the counting process-based method. We show that all steps involved in finding the reliability of k-out-of-n cold standby system using the proposed method are simple. We demonstrate the proposed method and its computational efficiency using a numerical example. © RAMS Consultants. Source


Amari S.V.,Parametric Technology (PTC) | Pham H.,Rutgers University | Misra R.B.,Secure Meters Ltd.
IEEE Transactions on Reliability | Year: 2012

We study reliability characteristics of the k-out-of-n warm standby system with identical components subject to exponential lifetime distributions. We derive state probabilities of the warm standby system in a form that is similar to the state probabilities of the active redundancy system. Subsequently, the system reliability is expressed in several forms that can provide new insights into the system reliability characteristics. We also show that all properties and computational procedures that are applicable for active redundancy are also applicable for the warm standby redundancy. As a result, it is shown that the system reliability can be evaluated using robust algorithms within {\cal O}(n-k+1) computational time. In addition, we provide closed-form expressions for the hazard rate, probability density function, and mean residual life function. We show that the time-to-failure distribution of the k-out-of-n warm standby system is equal to the beta exponential distribution. Subsequently, we derive closed-form expressions for the higher order moments of the system failure time. Further, we show that the reliability of the warm standby system can be calculated using well-established numerical procedures that are available for the beta distribution. We prove that the improvement in system reliability with an additional redundant component follows a negative binomial (Pólya) distribution, and it is log-concave in n. Similarly, we prove that the system reliability function is log-concave in n. Because the k-out-of-n system with active redundancy can be considered as a special case of the k-out-of-n warm standby system, we indirectly provide some new results for the active redundancy case as well. © 1963-2012 IEEE. Source


Amari S.V.,Parametric Technology (PTC)
Proceedings - Annual Reliability and Maintainability Symposium | Year: 2011

Many practical systems are phased-mission systems where the mission consists of multiple, consecutive, non-overlapping phases. For the mission to be a success, the system must operate successfully during each of the phases. In each phase, the system has to accomplish a specific task and may be subject to different stresses. Thus, the system configuration, success criteria, and component failure behavior may change from phase to phase. An accurate reliability analysis of these systems must consider the statistical dependencies of component states across the phases. The consideration of these dynamic dependencies poses unique challenges to existing reliability analysis methods. In this paper, we propose an efficient method for exact reliability evaluation of a special class of phased-mission systems containing multiple subsystems where all components within a subsystem are identical. The configuration of each subsystem can change with the phases, including their active and inactive status, redundancy type, and minimum required working components. If any one of the required (active) subsystems is failed in a phase, the system is considered to be failed in that phase. We also consider the time-varying and phase-dependent failure rates and associated cumulative damage effects. From the published examples, it can be shown that the mild restrictions imposed on the system configuration are applicable for a wide range of practical systems. The proposed method, which can be applied to very large-scale systems, is based on conditional probabilities and an efficient recursive formula to compute these probabilities. The main advantage of this method is that both the computational time and memory requirements of the method are linear in terms of the system size. We demonstrate the efficiency of the proposed method using medium-scale to large-scale systems. The proposed method provides a simple, efficient, and accurate reliability analysis of practical and large-scale phased-mission systems. © 2011 IEEE. Source


In modeling environments, a user typically interacts with a feature-based model by manipulating a feature of the model using a tool that is capable of achieving a number of different results with respect to the feature. An interface may be displayed that allows for manipulations to be made based on a result to be achieved, rather than by providing a generalized tool to achieve the result. Accordingly, the number of options that are presented on the interface may be reduced by eliminating extraneous options that are associated with the tool but not directly applicable to the desired result. A dynamic help system may be provided that provides targeted, dynamically-generated information relating to the result to be achieved. Furthermore, warnings may be displayed on the interface in real time during the model design process.

Discover hidden collaborations