The use of warranty claims data to determine the failure characteristics of a product is well documented. Typically, existing techniques assume that the product ages at the times of failure are known or can be derived based on product manufacturing data for each month of production and the corresponding monthly failure counts derived from the warranty claims. However, our experience shows that, in many cases, it may not be possible to know the failure ages of components. The information available from each month might be limited to the volume of shipments and total claims or product returns. In these cases, the data hides the component age at the time of failure. In this paper, we show that when the failure history information is incomplete, the failure distribution of the product can be determined using Bayesian analysis techniques applicable for handling incomplete data. The popular Expectation-Maximization (EM) algorithm is applied to find the Maximum Likelihood Estimates (MLE) of the failure distribution parameters using incomplete data. The effectiveness of the EM algorithm is compared using several sets of incomplete warranty data generated using simulation. The EM algorithm is observed to be powerful in capturing the hidden failure patterns from the incomplete warranty data.
Received on October 3, 2007, revised on April 29, 2008
References: 19

Technology advancement in wireless sensor networks (WSN) is enabling a wide range of diverse applications such as homeland security, healthcare, environment monitoring, and mission-critical military operations. WSN offers a remarkable potential to bridge the gap between the physical world of sensors and a virtual world of information and services, thereby enabling us to assimilate a deep and broad understanding and control of the environment. However, before WSN is truly established as the environment-aware ubiquitous sensing, networking, and computing infrastructure, it is critical that these smart sensors deliver acceptable reliability. Due to severe resource constraints (for example, energy constraints) and usually harsh operational environments, sensor nodes are prone to failures. As a result, it is imperative to design fault tolerance into WSN so that the overall sensor network functionalities can be sustained without interruption despite sensor node failures. In this paper, a set of fault-tolerant models are presented, and reliability performance of these models is evaluated and compared through dynamic fault tree analysis. Reliability formulae and comparison results for different fault-tolerant designs generated from this study will provide useful insights and guidelines for designers in achieving or improving fault tolerance for WSN.
Received on November 3, 2007, revised on June 6, 2008
References: 22

The paper presents a generalized model of damage caused to a complex multi-state series-parallel system by intentional attacks. The model takes into account the defence strategy that presumes separation and protection of system elements and deployment of false targets. The defence strategy optimization methodology is suggested, based on the assumption that the attacker tries to maximize the expected damage of an attack. An optimization algorithm is presented that uses a universal generating function technique for evaluating the losses caused by system performance reduction and a genetic algorithm for determining the optimal defence strategy. The role of the fault targets in the optimal defence strategy is analyzed. Illustrative example of defence strategy optimization is presented.
Received on January 7, 2008, revised on October 6, 2008
References: 11

Quantitative Risk Assessment (QRA) is a young scientific discipline and is rapidly developing. New methods and techniques are produced, and the application areas cover now most industries and businesses. However, the discipline is faced with many challenges -- the quality of and the added value obtained by conducting QRAs, are still questioned. Are the trends that we experience in the field going in the right directions meeting these challenges? In this paper we discuss this issue. We characterise some of the main trends and point at areas which should be given increased attention. The discussion covers topics related to the scientific basis of the risk assessments, uncertainty representations and handling, the causal chains and event modelling, and the use of decision criteria such as risk acceptance (tolerability) limits.
Received on June 06, 2008, revised on April 15, 2009
References: 45

Remanufacturing is a process of recapturing value from returned products. Whole products are brought back to like-new condition. The seven factors, that make production planning and process control for remanufacturing more complicated than equivalent activities in normal manufacturing, have been proposed in literature. The main ones are the uncertain timing and quantity of returns. There is a lack of reliability based forecasting models to better predict products life-cycles, return rates and quantities. Only one reliability based production planning method for remanufacturing has been proposed. It identifies two return reasons and it is appropriate only for single-use products. In practice most of products are serviced and returned only in specific cases. In this article seven different return reasons have been identified and the third one has been investigated. Others will be studied in future papers.
Received on September 14, 2008, revised on May 14, 2009
References: 07

Understanding of depot level spare parts forecasting is needed for economical procurement of spares and effectively implementing the production planning from maintenance and logistics engineering perspective in military aviation environment. This paper reviews various existing techniques used in spare parts forecasting in aviation. A deterministic model to set production targets and forecast depot level maintenance spares of military aircraft rotables is presented in this work.
Received on October 4, 2008, finally revised on April 18, 2009
References: 04

Fiber reinforced plastics (FRP) materials are susceptible to impact damage. So impact testing has been done to study the effect of impact because a little impact can lead to catastrophic failure in marine or aerospace where these materials are being used. These materials have also resistance to corrosion along with weight saving properties. In this paper, comparison of experimental and theoretical values for mean energy absorbed in FRP materials, using izod test is presented for notch radii of 0.25 mm, 0.5 mm and 0.75 mm. The experiment shows that the experimental (actual) absorbed energy is less than the theoretical absorbed energy. Energy absorbed by a test sample decreases with increase in notch radius. Results also show that the energy absorbed by the specimen reduces by approximately 10% when the notch radius is doubled.
Received on August 25, 2008, revised on February 20, 2009
References: 07

Gamma Interconnection Network (GIN) is a type of Multistage Interconnection Network (MIN) that consists of layers of switching elements connected together in a predefined topology providing the connectivity between the set of processors and the set of memory modules. GIN is constructed by 1x3, 3x3 and 3x1 switching elements. In this paper, network reliability of four other different types of Gamma hybrid networks namely Monogamma Interconnection Network (MGIN), Reliable Gamma Interconnection Network (REGIN), Cyclic Gamma Interconnection Network (CGIN) and Extra Stage Gamma Network (ESGN) are analyzed. The results from the proposed simulation method show that the ESGN, CGIN and REGIN exhibit high network reliability performance. This is subsequently followed by the MGIN, with a marginal network reliability improvement compared to the GIN. It is also shown that the reliability model used for simulation closely approximates the exact network reliability of MGIN, CGIN, and REGIN.
Received on September 8, 2008 and revised on May 23, 2009
References: 14