Assumption Of Constant Failure Rate Research Articles

Scenario-based multi-objective optimization for manufacturing reliability with production routes and available machine types

This study introduces a multi-objective reliability model designed to meet the customization needs of production systems by integrating manufacturing routes and machine types within a multilevel framework. A novel encoding approach and evolutionary operations are embedded within the indicator-based Artificial Bee Colony algorithm (ε-MOABC) to search for near-optimal solutions that accommodate diverse production requirements. A series of experiments were conducted to validate the multi-objective manufacturing scenarios. Initially, the model was tested using serial and serial-parallel systems, demonstrating that higher component reliabilities and redundancy levels are closely associated with shared machine types. The experiments further showcased the model’s effectiveness in managing key machine characteristics, such as maintenance, changeover, and workload. In a case study involving a steel forging plant, the model was extended to optimize the reliability of 12 products while minimizing costs and floor space. The findings emphasize the importance of balancing cost savings, machine efficiency, and transportation logistics. This study additionally explores Pareto-optimal solutions across production lines, providing insights into preference selection. Sensitivity analysis was also conducted to validate the model’s robustness. The discussion includes the assumption of constant failure rates and offers managerial implications, providing practical guidance for optimizing resource allocation in various production environments.

Resilience of wave energy farms using metocean dependent failure rates and repair operations

Emerging offshore renewable energy technologies are expected to become an important part of the future energy system, and reliability for these new technologies in different metocean scenarios must be guaranteed. This poses a challenge in extreme weather scenarios like storms, in particular for less mature technologies such as wave energy. Not only the offshore survivability must be controlled; the restoration after disruptive events and failures should be addressed and optimized. Offshore operations are costly and cannot be carried out if the weather is too harsh, and the resulting downtime after failures may be financially devastating for projects. In this paper, the resilience of large wave energy systems is studied with respect to wave conditions, metocean dependent failure rates, and weather windows available for offshore repair operations. A metocean- and time-dependent failure rate is derived based on a Weibull distribution, which is a novelty of the paper. The performance of the farm is assessed using the varying failure rates and metocean data at different offshore sites. Critical metocean thresholds for different offshore vessels are considered, and the resilience is quantified using relevant measures such as unavailability and expected energy not supplied. The resilience analysis is coupled to an economic assessment of the wave farm and different repair strategies. Our results show that the commonly used assumption of constant failure rates is seen to overestimate the annual energy production than when a more realistic varying failure rate is used. Two offshore sites are compared, and the availability is found to be higher at the calmer site. Most of the evaluated repair strategies cannot be considered to be economically justified, when compared to the cost of the energy not supplied.

Performance analysis of redundant safety-instrumented systems subject to degradation and external demands

Safety-instrumented systems (SISs) play a vital role in preventing hazardous events in the offshore facilities. Many of existing performance analysis of SISs are based on the constant failure rate assumption, which is however doubtful when it is applied to actuator sub-systems or mechanical final elements of a SIS. These mechanical SIS components can become vulnerable with time and with upcoming demands given the past exposures to shocks/demands. In this paper, we analyze SIS reliability and unavailability by considering that a failure occurs when total degradation of a SIS component, including continuous degradation and increments caused by random demands, exceeds to a predefined critical threshold. The dependency of two components in a redundant structure of mechanical actuators caused by random demands is also taken into account in the analysis. Approximation formulas for reliability and unavailability of the redundant SIS sub-system under a degradation process are developed. Finally, a numerical example is conducted to illustrate effects of degradation parameters on SIS performance.

Stochastic Characterization of Voltage Sag Occurrence Based on Field Data

Computational methods for predicting voltage sags consider their occurrence as a Poisson process, although without confirmation from monitoring data, until now. In this paper, the stochastic nature of voltage sags is analyzed and discussed using monitoring data from 60 sites of the Portuguese Transmission Network, covering the years 2011–2015 (a total of 17 157 recorded voltage sags). A mathematical model to describe the voltage sag occurrence as a stochastic process is presented. The assumption of constant failure rates of the network elements implies that the occurrence of voltage sags is a Poisson process. However, that assumption is not valid if voltage sag clusters are included, as these imply considering time-dependent failure rates. Then, the time between voltage sags is described by an exponential distribution, if clusters are not included, and may be described by the gamma distribution, if including clusters. The boundaries of the adequacy of exponential and gamma distributions are assessed, based on monitoring data. The time of occurrence of monitored voltage sags are analyzed and results confirm that the Poisson process describes the occurrence of voltage sags when voltage sag clusters are disregarded. The gamma distribution fitting is also confirmed when clusters are included in the analysis.

An integrated strategy for fleet maintenance planning

PurposeConventionally, fleet maintenance decisions are made based on the level of repair (LOR) analysis. A general assumption made during LOR analysis is the consideration of the lifetime distribution with constant failure rate (CFR). However, industries do use preventive maintenance (PM) to extend the life of such components, which in turn may affect the LOR decisions such as repair/move/discard. The CFR assumption does not allow the consideration of effect of PM in LOR analysis. The purpose of this paper is to develop a more practical LOR analysis approach, considering the time-dependent failure rate (TDFR) of components and the effect of PM.Design/methodology/approachIn the proposed methodology, first, a detailed life cycle model considering the effect of various parameters related to LOR and PM is developed. A simulation-based genetic algorithm approach is then used to obtain an integrated solution for LOR and PM schedule decisions. The model is also evaluated for the various cases of quality of maintenance measured in terms of degree of restoration.FindingsThe results, from the illustrative example for a multi-indenture and multi-echelon fleet maintenance network, show that the proposed integrated strategy leads to better LCC performance compare to the conventional approach. Additionally, it is identified that the degree of restoration also affects the PM schedule as well as LOR decisions of the fleet system. Therefore, consideration of TDFR is important to truly optimize the LOR decisions. The proposed approach can be applied to fleet of any equipment.Research limitations/implicationsThe approach is illustrated using a hypothetical example of an industrial system. A more complex system structure in terms of number of machines, types of machines (identical vs non-identical), number of echelons, possible repair actions at various echelons, etc. may be present for a particular industrial case. However, the approach presented is generic and can be extended to any system. Moreover, the aim of the paper is to highlight the importance of the considering PM and quality of maintenance in LOR decision making.Originality/valueTo the best of the authors’ knowledge, this is the first work which considers the effect of PM and quality of maintenance on LOR analysis. Consideration of TDFR and imperfect maintenance while optimizing LOR decisions is a complex problem. Thus, the work is of high significance from the research point of view. Also, most of the real life fleet systems use PM to extend the life of the equipment. Thus, present paper is a more practical approach for LOR analysis of such systems.

Reliability and availability analysis for robot subsystem in automotive assembly plant: a case study

The automotive assembly plant in a manufacturing environment consists of conveying systems and robots. Robots with high reliability will ensure no interruption during production. This study is to analyze the individual robot reliability compared to reliability of robots subsystem in series configuration. Availability was computed based on individual robots breakdown data. Failures due to robots breakdown often occurred during the operations. Actual maintenance data for a period of seven years were used for the analysis. Incorporation of failures rate and mean time between failures yield the reliability computation with the assumption of constant failure rate. Result from the analysis based on 5000 operating hours indicated reliability of series configuration of robots in a subsystem decreased to 2.8% in comparison to 38% reliability of the individual robot with the lowest reliability. The calculated lowest availability of the robots is 99.41%. The robot with the lowest reliability and availability should be considered for replacement.

Operational Reliability of the Rotary Cup Burner Type Saacke - SKV 60 of Marine Boiler

One of the steps in predicting the reliability of a system includes determining the failure rate of the system’s components. The latter is obtained on the basis of the data available to the manufacturer, experience in using similar systems, using statistical methods and technical literature. In practice, the starting point in the process of foreseeing the reliability of any technical system is the assumption of constant failure rates. The system components’ failure rates which are determined in this way represent the so-called nominal values. This value is commonly modified by taking into account operation loads and environment conditions under which the observed system component is supposed to operate. In most cases the quantitative values of these two factors result from the engineering assessment that is based on the data available to the manufacturer or the user and takes into account the inevitable effect of a number of subjective factors. Predicting reliability is a process of determining numerical values which show the probability that machinery or engine will meet previously set requirements. The basic objective of reliability prediction is to ensure timely maintenance. This paper discusses predicting the operational reliability of the rotary cup burner type SAACKE - SKV 60 in the marine steam boiler TPK/VIC 8.5/7.

Availability and reliability of system with dependent components and time-varying failure and repair rates

System reliability depends not only on the reliabilities of components in the system but also on their interactions. Generally, in a system, not only s-independent failures but also s-dependent failures among components can occur; thus there are many studies where the s-dependencies among components are taken into account in system reliability and availability analysis, but in which the failure and repair rates were assumed constant. Whereas, from a practical viewpoint, the constant failure rate assumption for components has been, and is repeatedly challenged by knowledgeable reliability practitioners. Therefore, there are other studies which handled the problem of time-varying failure rates, among which all concerned repairable systems did not involve s-dependent failures. In most cases, however, to combine s-dependent failures and time-varying failure and repair rates in system reliability and availability analysis is the most appropriate for real systems. But it is very difficult to obtain the analytic solution and, in most cases, the closed-form solution for system reliability and availability does not exist, so that numerical or simulation methods must be used. This paper studies one kind of system that endures environmental shocks, and where one or more components can fail simultaneously due to a cumulative shock-damage process. An approach for reliability and availability analysis of such kinds of repairable systems is presented, where failure and repair rates of components can be varied with time. One type of special vehicle with such mechanical systems illustrates system reliability and availability solutions.

Exponential approximation for maintained Weibull distributed component

Exponential distribution is widely used in reliability and maintainability studies although it is well known that the constant failure rate assumption may not be valid. The purpose of this paper is to investigate the use of exponential distribution as an approximation. In fact, for components undergoing regular maintenance or replacement, the exponential assumption can be acceptable. In this paper, the exponential approximation for regularly maintained Weibull component is studied. The approximated exponential distribution using the average failure rate is compared with the exact reliability. The asymptotic relative error is derived, which can be used to adjust the exponential approximation when needed. Based on the framework of exponential approximation for Weibull distributed components, the problems of decision‐making regarding the optimal maintenance time and spare allocation are also addressed.

Consideration of component failure mechanisms in the reliability assessment of electronic equipment— Addressing the constant failure rate assumption : DAVID E. MORTIN, JANE G. KROLEWSKI and MICHAEL J. CUSHING. Proceedings of the Annual IEEE Reliability and Maintainability Symposium, 54 (1995)

Consideration of component failure mechanisms in the reliability assessment of electronic equipment— Addressing the constant failure rate assumption : DAVID E. MORTIN, JANE G. KROLEWSKI and MICHAEL J. CUSHING. Proceedings of the Annual IEEE Reliability and Maintainability Symposium, 54 (1995)

New definitions of basic R&M terms

This paper is addressed to designers as well as R&M specialists. Existing definitions of basic reliability and maintainability terms are vague and ambiguous. Lacking structure, they fail to interrelate; and failing this, they lack precision. Also, some basic terms that ought to have been defined, were not. Starting with reliability itself, and availability in the case of maintainability, the paper traces their genealogies, diagramming basic minimum sets of terms for each. Members of each set are then restated with due regard for logical interrelationships. Complementary notes, including derivational outlines as appropriate, provide necessary restatement rationale. One outcome is that the key concept from a designer's viewpoint is not reliability per se, but useful life. Another (vis-a-vis “useful life”) is an explicit defense of the constant failure rate assumption. A relatively simple derivation of the Poisson process is outlined using functional equations (the so-called “Composed Poisson Distribution”). An even simpler heuristic argument is given to derive the expression for steady-state availability. Consideration is given to explaining the difference between the various failure classes and causes, particularly wearout and random failures. An Addendum briefly discusses the dispute over the efficacy of Mil-Hdbk-217 and related issues.

Reliability prediction: A constructive critique of MIL‐HDBK‐217E

AbstractMIL‐HDBK‐217E is based on some major fallacies and oversimplifications. These include the assumption of constant failure rate, the assumed independence of the Pi factors, the oversimplification of temperature dependence, the neglect of process yield and screening fall‐out as determinants in the categorization of quality grade and the absence of manufacturing date information. These weaknesses are discussed and some recommendations made.