RELIABILITY OPTIMIZATION OF SOME INDUSTRIAL SYSTEMS USING ABC TECHNIQUE

Abstract

With modern technology and higher reliability requirements, systems are getting more complicated day-by-day and hence job of the system analyst or plant personnel becomes so difficult to run the system under failure-free pattern. In the competitive market scenario, reliability and maintainability are the most important parameters that determine the quality of the product with the aim to estimate and predict the probability of the failure, and optimize the operation management. From a system effectiveness viewpoint, reliability and maintainability jointly provide system availability and dependability. Increased reliability directly contributes to system uptime, while improved maintainability reduces downtime. If reliability and maintainability are not jointly considered and continually reviewed, serious consequences may result. Therefore, the primary objective of any industrial system is to acquire quality products/systems that satisfy user needs with measurable improvements to mission capability and operational support in a timely manner, and at a fair and reasonable price. In determining the complexity and consequent frequent failure of the critical combination and complex integration of large engineering processes and systems, both in their level of technology as well as in their integration, the integrity of their design needs to be determined. This includes reliability, availability and maintainability (RAM) of the inherent process and system functions and their related equipments. The main objective of the thesis is to present a technique for optimizing the reliability and availability issues of the industrial systems under different scenarios. For i ii this firstly, availability optimization model has been constructed for computing the optimal design parameters-MTBF and MTTR- of the system by considering manufacturing as well as repairing cost as an objective functions subject to predetermined availability constraints. Moreover, most of the data collected for analysis are taken from their historical records/sheets which are generally representing the past behavior of the system. Thus the issue of handling the uncertainties play a dominant role. For this fuzzy set theory has been used during the analysis and based on that various reliability parameters are depicted in the form of membership functions by using a proposed hybridized technique named as artificial bee colony based lambda-tau (ABCBLT). In this technique nonlinear optimization problem has been formulated by taking ordinary arithmetic operations instead of fuzzy arithmetic operations. Apart from their behavior analysis, an investigation has been done for finding the most critical component of the system on which more attention may be given for increasing the production as well as productivity of the system. For this a composite measure of reliability, availability and maintainability named as RAMIndex has been given for a time varying failure rate components and studied their behavior in fuzzy environment. The advantage of defining this index is to analyze the impact of each component failure rate or repair time individually as well as simultaneously on its performance. Also this approach has been extended by taking degree of hesitation between the membership and nonmembership functions in terms of intuitionistic fuzzy set theory. The present thesis is organized into nine chapters which are briefly summarized as follows: A brief account of the related work of various authors in evaluation of system reliability by using conventional, fuzzy and optimization techniques is presented in the first chapter. The overview of the thesis is also presented in this chapter. In Chapter 2, the basics and preliminaries related to the reliability analysis and to be used in subsequent chapters are given. iii Chapter 3 deals with performance analysis of a Butter-oil processing plant, which consists of subsystems namely Separator, Pasteurizer, Continuous butter making, Melting vats, Butter-oil Clarifier and Packaging units in series. For this an optimization model has been constructed by considering the system cost-manufacturing as well as repairing- as an objective and their system availability as a constraint. The reliability block diagram (RBD) of this system is drawn and ABC is used to compute optimal values of MTBF and MTTR. Finally computed results are shown to be statistically significant as compared to other algorithm techniques. This work has been submitted after revision to Mathematics and Computers in Simulation, Elsevier. In Chapter 4, the computed results from the Chapter 3 are used for analyzing the behavior of their system. For this, the uncertainties which are present in the data are handled with the help of fuzzy set theory and based on that behavior of their corresponding system are analyzed in the form of fuzzy membership functions. A nonlinear optimization model has been formulated and solved by ABC algorithm for computing their reliability indices. Sensitivity as well as performance analysis on the system performance index has been analyzed which shows the effect of its component failure rate and repair time on the performance of the system. Finally the computed results are compared with the existing results as obtained by other researchers. In Chapter 5, the behavior analysis of a paper mill, a complex repairable industrial system has been investigated by using ABC and fuzzy methodology. For this, time varying failure rate which follows the Weibull distribution and a constant repair time model, which follows the exponential distribution, have been taken corresponding to each component of the system. Uncertainties in the data are handled with fuzzy set theory and then behavior of the system has been analyzed in the form of various reliability parameters. To study the failure behavior of the system, crisp and defuzzified values are obtained at ±15%, ±25% and ±50% spreads. This iv work has been published in International Journal of Industrial and Systems Engineering, International Journal of Performability Engineering, International Journal of Applied Mathematics and Mechanics and 16th Online World Conference on Soft computing in Industrial Application conference. In Chapter 6, performance analysis of repairable industrial systems has been done by defining a composite measure of reliability parameters called as RAM-Index. A time dependent RAM-Index as given below has been introduced in this chapter to analyze and rank the sensitive components of each unit of the system. RAM(t) = w1 × Rs(t) + w2 × As(t) + w3 ×Ms(t) where wi ∈ (0, 1), i = 1, 2, 3 are weights such that Σ3 i=1 wi = 1. Advantage of this index is that by varying the component failure parameters, the corresponding effect on its performance has been analyzed. The presented approach has been applied to optimize the performance of a paper mill. This work has been published in Applied Soft Computing, Elsevier and International Journal of Quality, Statistics & Reliability, Hindawi. Chapter 7 introduces a two-phase approach for solving the reliability-redundancy allocation problem of a series, series-parallel, complex design problems. In the first phase, an optimal reliability and their corresponding redundant component of each subsystem has been computed using ABC algorithm and the results are compared with other evolutionary algorithm results. While the improvement of their component reliability has been made in their second phase by preserving the redundant components corresponding to each subsystem. Finally the computed results during both the phases are compared to show the superbly of the proposed approach with the existing techniques. In Chapter 8, a structural framework has been developed to model, analyze and predict the failure pattern of the system behavior in both quantitative as well v as qualitative manner. In their framework, degree of hesitation or indeterminacy between the membership functions have been considered in which basic event are represented in the form intuitionistic fuzzy numbers of triangular membership functions. To strengthen the analysis, various reliability parameters of interest are computed and compared their results with their crisp as well as fuzzy technique results. Sensitivity analysis on the system MTBF has been computed for different combinations of reliability parameters. The part of this chapter has been published in proceeding of International Conference on Applied Mathematics and Numerical Analysis held at Paris. Chapter 9 deals with the overall concluding observations of this study and a brief discussion on the scope for future work.