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The purpose of this paper is to carry out a reliability analysis of a mechanical system considering the degraded states to get a proper understanding of system behavior and its propagation towards complete failure.

The reliability analysis of computerized numerical control machine tools (CNCMTs) using a multi-state system (MSS) approach that considers various degraded states rather than a binary approach is carried out. The failures of the CNCMT are classified into five states: one fully operational state, three degraded states and one failed state.

The analysis of failure data collected from the field and tests conducted in the laboratory provided detailed understandings about the quality of the material and its failure behavior used in designing and the capability of the manufacturing system. The present work identified that Class II (major failure) is critical from a maintainability perspective whereas Class III (moderate failure) and Class IV (minor failure) are critical from a reliability perspective.

This research applies to reliability data analysis of systems that consider various degraded states.

MSS reliability analysis approach will help to identify various degraded states of the system that affect the performance and productivity and also to improve system reliability, availability and performance.

Industrial system designers recognized that reliability and maintainability is a critical design attribute. Reliability studies using the binary state approach are insufficient and incorrect for the systems with degraded failures states, and such analysis can give incorrect results, and increase the cost. The proposed MSS approach is more suitable for complex systems such as CNCMT rather than the binary-state system approach.

This paper presents a generalized framework MSS's failure and repair data analysis has been developed and applied to a CNCMT.

Reliability, maintainability and availability of modern complex engineered systems are significantly affected by four basic systems or elements: hardware, software, organizational and human. Computerized Numerical Control Turning Center (CNCTC) is one of the complex machine tools used in manufacturing industries. Several research studies have shown that the reliability and maintainability is greatly influenced by human and organizational factors (HOFs). The purpose of this paper is to identify critical HOFs and their effects on the reliability and maintainability of the CNCTC.

In this paper, 12 human performance influencing factors (PIFs) and 10 organizational factors (OFs) which affect the reliability and maintainability of the CNCTC are identified and prioritized according to their criticality. The opinions of experts in the fields are used for prioritizing, whereas the field failure and repair data are used for reliability and maintainability modeling.

Experience, training, and behavior are the three most critical human PIFs, and safety culture, problem solving resources, corrective action program and training program are the four most critical OFs which significantly affect the reliability and maintainability of the CNCTC. The reliability and maintainability analysis reveals that the Weibull is the best-fit distribution for time-between-failure data, whereas log-normal is the best-fit distribution for Time-To-Repair data. The failure rate of the CNCTC is nearly constant. Nearly 66 percent of the total failures and repairs are typically due to the hardware system. The percentage of failures and repairs influenced by HOFs is nearly only 16 percent; however, the failure and repair impact of HOFs is significant. The HOFs can increase the mean-time-to-repair and mean-time-between-failure of the CNCTC by nearly 65 and 33 percent, respectively.

The paper uses the field failure data and expert opinions for the analysis. The critical sub-systems of the CNCTC are identified using the judgment of the experts, and the trend of the results is verified with published results.

Life cycle cost (LCC) analysis is one of the key parameters in designing a sustainable product or system. The application of life cycle costing in the manufacturing industries is still limited due to several factors. Lack of understanding of LCC analysis methodologies is one of the key barriers. This paper presents a generalized framework for LCC analysis of repairable systems using reliability and maintainability principles.

The developed LCC analysis framework and stochastic point processes are applied for the analysis of a typical computerized numerical control turning center (CNCTC) and governing equations for acquisition cost, operation cost, failure cost, support cost and net salvage value are developed. The LCC of the CNCTC is evaluated for the renewal process (RP) and minimal repair process (MRP) approach.

The LCC analysis of the CNCTC reveals that, the acquisition cost is only 7.59% of the LCC, whereas the operation, failure and support costs dominate and contribute nearly 93% of the LCC. The LCC per day for RP requires additional US$ 1.03 than that for MRP. The detailed LCC analysis of the CNCTC identifies the critical components of CNCTC and these components are: spindle motor, spindle motor cooling fan, spindle belt, drawbar, spindle bearing, oil seals, hydraulic hose, solenoid valve, tool holder, lubrication pump motor system, lubrication hose, coolant pump motor system, coolant hose, supply cables, drive battery.

The developed framework of LCC of a repairable system can be applied to any other repairable systems with the appropriate modifications. LCC analysis of CNCTC reveals that the procurement decision of a product or system should be based on LCC and not only on the acquisition cost. The optimum utilization of consumables such as cutting tools, coolant, oil and lubricant can save operation cost. Thus, use of high-efficiency electric motors and the usage of recommended consumables can prolong the life of several components of a system. Therefore, due consideration and attention to these parameters at product design stage itself will decrease failure and support cost and ultimately its LCC.

The paper presents reliability, maintainability and life cycle cost (LCC) analysis of a computerized numerical control (CNC) turning center which is manufactured and used in India. The purpose of this paper is to identify the critical components/subsystems from reliability and LCC perspective. The paper further aims at improving reliability and LCC by implementing reliability-improvement methods.

This paper uses a methodology for the reliability analysis based on the assessment of trends in maintenance data. The data required for reliability and LCC analysis are collected from the manufacturers and users of CNC turning center over a period of eight years. ReliaSoft’s Weibull++9 software has been used for verifying goodness of fit and estimating parameters of the distribution. The LCC of the system is estimated for five cost elements: acquisition cost, operation cost, failure cost, support cost and net salvage value.

The analysis shows that the spindle bearing, spindle belt, spindle drawbar, insert, tool holder, drive battery, hydraulic hose, lubricant hose, coolant hose and solenoid valve are the components with low reliability. With certain design changes and implementation of reliability-based maintenance policies, system reliability is improved, especially during warranty period. The reliability of the CNC turning center is improved by nearly 45 percent at the end of warranty period and system mean time between failure is increased from 15,000 to 17,000 hours. The LCC analysis reveals that the maintenance cost, operating cost and support costs dominate the LCC and contribute to the tune of 87 percent of the total LCC.

The proposed methodology provides an excellent tool that can be utilized in industries, where safety, reliability, maintainability and availability of the system play a vital role. The approach may be improved by collecting data from more number of users of the CNC turning centers.

The approach presented in this paper is generic and can be applied to analyze the repairable systems. A real case study is presented to show the applicability of the approach.

The proposed methodology provides a practical approach for the analysis of time-to-failure and time-to-repair data based on the assessment of trends in the maintenance data. The methodology helps in selecting a proper approach of the analysis such as Bayesian method, parametric methods and nonparametric methods.

The demand of sewage treatment plants is increasing day by day, especially in the countries like India. Biological and chemical unit of such sewage treatment plants are critical and needs to be designed and developed to achieve desired level of reliability, maintainability and availability.

This paper investigates and optimizes the availability of biological and chemical unit of a sewage treatment plant. A novel mathematical model for this unit is developed using the Markovian birth-death process. A set of Chapman–Kolmogorov differential equations are derived for the model and a generalized solution is discovered using soft computing techniques namely genetic algorithm (GA) and particle swarm optimization (PSO).

Nature-inspired optimization techniques results of availability function depicted that PSO outperforms GA. The optimum value of the availability of biological and chemical processing unit is 0.9324 corresponding to population size 100, the number of evolutions 300, mutation 0.6 and crossover 0.85 achieved using GA while PSO results reflect that optimum achieved availability is 0.936240 after 45 iterations. Finally, it is revealed that PSO outperforms than GA.

This paper investigates and optimizes the availability of biological and chemical units of a sewage treatment plant. A novel mathematical model for this unit is developed using the Markovian birth-death process.

Availability model of biological and chemical units of a sewage treatment is developed using field failure data and judgments collected from the experts. Furthermore, availability of the system has been optimized to achieve desired level of reliability and maintainability.

The effective, efficient and optimal design of micromixer is the need in the field of biochemical and biomedical diagnostic systems.

In this paper, multi-objective optimization of split and recombine micromixer (SRM) with different geometrical configurations is carried out. The finite element method-based three-dimensional models are prepared and analyzed using COMSOL Multiphysics 5.0 Software. Taguchi’s design of experiment (DoE), main effect plot analysis, ANOVA and grey relational analysis (GRA) method are used to find out optimum condition. The five geometrical parameters with three levels, namely, angle between inlets, pillar size, pillar shape, aspect ratio and constriction height of SRM are considered as design variables. The mixing index (MXI) and pressure drop (∆P) are considered objective functions.

The MXI is significantly influenced by pillar shape and aspect ratio, whereas the pressure drop (∆P) by constriction height. Maximum MXI (0.97) with minimum pressure drop (64,587 Pa) is the optimal conditions and obtained at 180 deg angle between inlets, 50 µm of pillar size, 1.5 of aspect ratio, 100 µm of constriction height and ellipse shape pillar cross-section, respectively.

This optimized SRM can be combined with lab-on-a-chip for biochemical and biomedical analysis.

This work is useful to obtain optimal geometry of SRM for getting efficient performance of micromixer.

Reliability analysis is required to identify the components or subsystems with low reliability for a given designed performance. Life cycle cost analysis helps understand the cost implications over the entire life span of a product. The purpose of this paper is to present a case study describing reliability analysis and life cycle cost optimization of a band saw cutting machine manufactured and used in India.

The data required for reliability analysis is collected from the manufacturer and users of band saw cutting machine. The parameters of failure distribution have been estimated by using ReliaSoft’s Weibull++6 software. The life cycle cost is divided into various cost elements such as acquisition cost, operation cost, failure cost, support cost and net salvage value.

The results of the analysis show that the components such as band wheel bearing, guide roller bearing, limit switch, carbide pad, hydraulic cylinder oil seal, control panel dial, control panel and solenoid valve are critical from reliability and life cycle cost analysis perspective.

With certain design changes it is found that the reliability of the system is increased by 15.85 percent while the life cycle cost is reduced by 22.09 percent. The study also shows that the reliability analysis is useful for deciding maintenance intervals.