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Reliability and replacement characteristics of Great Lakes marine diesel engines have been studied. A Colt-Pielstick PC2-400 series marine diesel engine has been used as a prototype for our modeling. Failure Modes and Effects, and Fault Tree analyses for our engine have been performed. Censored field data have been processed from six identical engines of the above type. Parameters of Weibull and Exponential PDF's have been evaluated for seven vital system components, namely connecting rod bearing, cylinder head, cylinder jacket, cylinder liner and o-ring, cylinder piston, and fuel cam. Reliability and hazard functions for these items have been derived and discussed using both above PDF's. Exponential PDF's have been found to be inappropriate for representations of components failure times. Reliability based models have been developed and implemented to rationalize current winter layup replacement practices. Two systems have been considered: One for a ship equipped with one engine only and another for a two-engine ship. Incorporating the age dependent nature of system failure characteristics, a semi-Markov competing-process approach has been used in our models, where system failure behavior has been treated as a race among engine components. Howard's one-set competing process model has been implemented and extended to two sets of competing processes. A recursive iteration procedure has been used in the expected cost calculation. An efficient enumeration procedure has been presented to select the replacement policy which produces the minimum expected cost for an operating season. Computer codes have been developed using the above models, and several examples have been examined. Sensitivity analyses have been performed for several parameters for which we had insufficient or no information from the industry to see the influence of their variation on our expected costs and corresponding winter layup policies. We have observed that current replacement practices are conservative. Our results have also indicated that the total expected cost function changes almost linearly with time for our parameters. However, this linearity is very sensitive to the length of operating season. As far as replacement policies are concerned, there is a group of \"good\" replacement policies immediately following the best replacement policy; differences between the total expected costs resulting from these policies are not very significant for some cases within our parameter range. Besides, the value of the minimum expected cost function is very sensitive to component ages, and operating costs.

Advances in information technology provide new tools and resources to optimize total life cycle of ships in terms of reliability, safety and the control of operating costs. Regulatory agencies and classification societies are moving towards risk-based/reliability-centered rule-making in the shipping industry. However, reliability, maintenance and risk assessment were not considered to be a part of the traditional Naval Architecture and Marine Engineering curriculum in the US. In this paper, the current status of existing curricula, accreditation requirements and new developments are presented. Finally, emerging needs of the maritime industry are discussed.

Automated monitoring systems are now the standard on most large vessels; however, few are equipped with diagnostic systems. This paper presents new developments in the area of fault diagnosis based on intelligent software agents. The research objective was to design an agent capable of continuous real-time machine learning by using an artificial neural network known as the cerebellar model articulation controller (CMAC). An engine simulator that can model both normal and faulty engine operations was used to develop the learning system controller in a flexible and cost-efficient manner. This paper provides a description of the selected CMAC, a brief overview of the real-time engine simulator and its integration with the learning system as well as a few results.

An industry-wide international network is needed to collect Reliability, Availability and Maintainability (RAM) data on shipboard machinery and share this data at different levels by linking vessel chief engineers, ship operators-managers, regulatory agencies, equipment manufacturers, and shipyards/designers. This network should facilitate the efficient collection and flow of RAM information between these entities with industry-wide continuous improvement in safety and cost-effectiveness. This paper describes the implementation of a worldwide information network, called RAM/SHIPNET to support the optimization of safety, reliability and cost effectiveness throughout all stages of a vessel's life cycle. Development of this network was started with seed funding from SNAME and continued under the umbrella of the Ship Operations Cooperative Program with primary funding from the Gulf Coast Region Maritime Technology Center at the University of New Orleans. First generation data collection and processing tools have been completed and, pilot validation and testing has been performed in the USA. The project is now moving into the second implementation stage enabling full scale testing, validation and roll-out on a global scale. A call is made to the industry for suggestions on improvement to meet emerging needs.