M. Phil. / Concrete is worldwide the most commonly used construction material and, although concrete is durable when exposed to aggressive conditions, it requires some maintenance. If this maintenance is neglected for a prolonged period of time, intrinsic and extrinsic factors will cause the concrete to degrade necessitating repair and rehabilitation. The correct diagnosis of the root cause of degradation, proper specification of repair materials and quality execution of the concrete repairs all contribute to the reliability of the repairs. The correct management of the repair process is necessary to ensure reliability in order for the structure to be returned to an acceptable state.

Reliability levels of Japanese 2x4 wood frame structures were evaluated using lumber property data derived from evaluation of Canadian Spruce-Pine-Fir dimension lumber. The evaluations were made using the "Standard for Limit States Design of Steel Structures (Draft)", which was newly published by the LRFD Subcommittee of Architectural Institute of Japan, and In-Grade Data obtained by a Canadian Wood Council research project. These analyses were implemented using the computer program "RELAN" developed by Dr. R.O. Foschi at UBC and Monte Carlo simulations. Reliability levels of current Japanese 2x4 wood frame structures were also evaluated. Recommendations were made to encourage the application of limit states design into existing Japanese design methods. / Forestry, Faculty of / Graduate

Reliability Centred Maintenance (RCM) started a new chapter in the history of preventive maintenance strategy setting. It was now possible to develop a scientifically based, highly successful maintenance program for complex systems. It developed as a result of the reliability problems and cost of maintenance of aircraft during the late 50’s and early 60’s. The result was a methodology called MSG-1, followed by the improved MSG-2. When MSG-2 was used contractually for the United States Department of Defence, it led to the present definition of RCM. In academic circles there developed a growing dissatisfaction with the technique [Pintelon et al (1999], of which part stems from watering down its scientific basis to make RCM more marketable [Moubray (2000)], while at least part is based on perceived inherent scientific weaknesses in the methodology itself. This thesis, in setting out to solve these limitations, makes several important contributions to the RCM methodology. The first of these is a method of concentrating the RCM analysis effort on the most important failure modes encountered by the organisation. Secondly, it introduces a Quality Improvement task in the RCM task selection tree, based on a limitation identified by Harris (1985). The third contribution is the addition of a formal task packaging methodology, following Gits (1984). The thesisalso combines the use of RCM for the most important failure modes with conventional maintenance tasks for the remaining failure modes, to form a total methodology for the typical industrial concern. It furthermore introduces the application of sound management principles in the implementation of RCM and lastly, blends concepts from different RCM authors, together with the innovations listed above, into one logical whole. In summary, the proposed revised methodology can play a very important part to achieve the goal of World Class manufacturing standards, including ensuring that the organisation’s maintenance effort is as proactive as possible. D13/4/90 / Thesis (PhD (Industrial Engineering))--University of Pretoria, 2002. / Industrial and Systems Engineering / unrestricted

<p> </p> <p>In the mechanical design stage, engineers always meet with uncertainty, such as random</p> <p>variables, stochastic processes, and random processes. Due to the uncertainty, products may</p> <p>behave randomly with respect to time and space, and this may result in a high probability of failure,</p> <p>low lifetime, and low robustness. Although extensive research has been conducted on the</p> <p>component reliability methods, time- and space-dependent system reliability methods are still</p> <p>limited. This dissertation is motivated by the need of efficient and accurate methods for addressing</p> <p>time- and space-dependent system reliability and probabilistic design problems.</p> <p>The objective of this dissertation is to develop efficient and accurate methods for reliability</p> <p>analysis and design. There are five research tasks for this objective. The first research task develops</p> <p>a surrogate model with an active learning method to predict the time- and space-independent</p> <p>system reliability. In the second research task, the time- and space-independent system reliability</p> <p>is estimated by the second order saddlepoint approximation method. In the third research task, the</p> <p>time-dependent system reliability is addressed by an envelope method with efficient global</p> <p>optimization. In the fourth research task, a general time- and space-dependent problem is</p> <p>investigated. The envelope method converts the time- and space-dependent problem into time- and</p> <p>space-independent one, and the second order approximation is used to predict results. The last task</p> <p>proposes a new sequential reliability-based design with the envelope method for time- and spacedependent</p> <p>reliability. The accuracy and efficiency of our proposed methods are demonstrated</p> <p>through a wide range of mathematics problems and engineering problems.</p>

A project report submitted to the Faculty of Engineering, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering. / The simulator uses the Monte Carlo technique to quickly and accurately estimate the reliability and availability of complex network systems, Non-exponential failure and repair distributions are included in the model, as is standby redundancy and K out of N active redundancy. The program is easy to use and will work on a large variety of computers and FORTRAN compilers. Some knowledge of FORTRAN is required to program the simulator for each reliability network, The simulator is limited to the analysis of network systems, i.e, those systems whose logic can be fully represented by a reliability block diagram. The applicability of the model was demonstrated by the analysis of numerous systems in the aerospace and industrial environments. Validation of the model was accomplished by comparing these results with analytically determined values, or those from AMIR and SPAR where an analytic solution was impossible. / Andrew Chakane 2018

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Any product sold is expected to be reliable and available when the customer wants to operate it. Companies that produce large capital products (LCP), such as rockets, satellites, or large gas turbines to generate electrical energy, tend to shy away from extending their testing and validation method above the requirements by law, mainly due to the very high costs of each additional test and the uncertain return on investment. This research shows that today’s state of the art validation methods for LCP, required by law, or suggested in literature, and adapted by these industries, are not capable of capturing all significant failure modes (or even enough failure modes), with the consequence that the subsequently sold commercial product will still experience failures with significant effects on product reliability, and subsequently on the companies’ bottom line earnings projections. The research determines the type of data (significant variables) necessary to correlate a company’s validation policy to product failures after commercialization, and predicts the financial impact of the current validation policy on the company’s profitability. An optimized validation plan and testing policy is suggested, and its impact on a company’s profitability is demonstrated through simulation. A generic methodology is derived and its viability is illustrated using a specific product and a dynamic model developed with data available to the researcher. The generic method can be applied by any company to develop its own model for optimizing product reliability prior to market introduction. iv

Accelerated Life Testing (ALT) is an effective method of demonstrating and improving product reliability in applications where the products are expected to perform for a long period of time. ALT accelerates a given failure mode by testing at amplified stress level(s) in excess of operational limits. Statistical analysis (parameter estimation) is then performed on the data, based on an acceleration model to make life predictions at use level. The acceleration model thus forms the basis of accelerated life testing methodology. Well established accelerated models such as the Arrhenius model and the Inverse Power Law (IPL) model exist for key stresses such as temperature and voltage. But there are other stresses like subsea pressure, where there is no clear model of choice. This research proposes a pressure-life (acceleration) model for the first time for life prediction under subsea pressure for key mechanical/physical failure mechanisms. Three independent accelerated tests were conducted and their results analyzed to identify the best model for the pressure-life relationship. The testing included material tests in standard coupons to investigate the effect of subsea pressure on key physical, mechanical, and electrical properties. Tests were also conducted at the component level on critical components that function as a pressure barrier. By comparing the likelihood values of multiple reasonable candidate models for the individual tests, the exponential model was identified as a good model for the pressure-life relationship. In addition to consistently providing good fit among the three tests, the exponential model was also consistent with field data (validation with over 10 years of field data) and demonstrated several characteristics that enable robust life predictions in a variety iv of scenarios. In addition the research also used the process of Bayesian analysis to incorporate prior information from field and test data to bolster the results and increase the confidence in the predictions from the proposed model.

The purpose of this research is not to research new technology but how to improve existing technology and understand how the manufacturing process works. Reliability Engineering fall under the category of Quality Control and uses predictions through statistical measurements and life testing to figure out if a specific manufacturing technique will meet customer satisfaction. The research also answers choice of materials and choice of manufacturing process to provide a device that will not only meet but exceed customer demand. Reliability Engineering is one of the final testing phases of any new product development or redesign.

No description available.