Edward A. Pohl

Combining preventive maintenance and statistical process control: a preliminary investigation

The economic design of control charts and the optimization of preventive maintenance policies are two research areas that have recently received a great deal of attention in the quality and reliability literature. Both of these research areas are focused on reducing the costs associated with operating manufacturing processes. In addition, it is widely recognized that the maintenance of manufacturing equipment and the quality of manufactured product are related. However, these two research areas are rarely integrated. In this paper, a combined control chart-preventive maintenance strategy is defined for a process which shifts to an out-of-control condition due to a manufacturing equipment failure. An X¯ chart is used in conjunction with an age-replacement preventive maintenance policy to achieve a reduction in operating costs that is superior to the reduction achieved by using only the control chart or the preventive maintenance policy. This superior cost performance is demonstrated using a simulation-optimization approach.

Selective maintenance modeling for industrial systems

In many industrial environments, systems are required to perform a sequence of operations (or missions) with finite breaks between each operation. During these breaks, it may be advantageous to perform repair on some of the system’s components. However, it may be impossible to perform all desirable maintenance activities prior to the beginning of the next mission due to limitations on maintenance resources. In this paper, a mathematical programming framework is established for assisting decision‐makers in determining the optimal subset of maintenance activities to perform prior to beginning the next mission. This decision‐making process is referred to as selective maintenance. The selective maintenance models presented allow the decision‐maker to consider limitations on maintenance time and budget, as well as the reliability of the system. Selective maintenance is an open research area that is consistent with the modern industrial objective of performing more intelligent and efficient maintenance.

Selective maintenance for support equipment involving multiple maintenance actions

Abstract Selective maintenance is the process of identifying a subset among sets of desirable maintenance actions. Previous works use mathematical programming models for making selective maintenance decisions for production equipment and military vehicles, which perform sequences of missions and are repaired only between missions. In this paper, extensions of these models are proposed. First, system component life is assumed to follow Weibull distributions. Second, the decision-maker is given multiple maintenance options: minimal repair on failed components, replacement of failed components, and replacement of functioning components (preventive maintenance).

Optimal Stress Screening strategies formulti‐component systems sold under warranty:The case of phase‐type lifetimes

Environmental Stress Screening (ESS) is employed to reduce, if not eliminate, the occurrence of early field failures. This paper examines the necessary trade‐offs between the reduction in warranty costs and the increase in manufacturing costs associated with optimal stress screening strategies. A multi‐level ESS model is presented for a multi‐component electronic system. Screening can be performed at component, unit, and system levels. Components and connections are assumed to come from good and substandard populations and their time‐to‐failure distributions are modeled by mixed distributions. The majority of ESS models found in the literature assume that the time‐to‐failure distributions are exponential. The exponential distribution is used primarily to take advantage of its mathematical tractability. This paper generalizes previous work by modeling component and connection lifetimes with phase-type distributions. Phase‐type distributions offer the advantage of mathematical tractability as well as versatility in the family of distributions they can represent. To date there is no significant research into the impact that the selection of a lifetime distributions for modeling the failure process has on ESS decisions. In this paper, we evaluate screening strategies for several lifetime distributions. Numerical examples are provided to illustrate the effect of various model parameters on the optimal stress screening strategy.

Moment matching using a family of phase-type distributions

An approach to matching the first three moments is presented for distributions with positive support and coefficient of variation greater than one Necessary and sufficient bounds are derived for the phase-type distribution defined by appending a Coxian stage to an Erlang distribution. This result is an extension of Altioks use of a Coxian-2 distribution for 3-moment matching

Sensitivity analysis of availability estimates to input data characterization using design of experiments

Reliability analysts are often faced with the challenge of characterizing the behaviour of system components based on limited data. The purpose of this study is to provide insight into which availability model input data are most significant and how many data are necessary to achieve desired accuracy requirements. The overall goal is to improve the efficiency and cost-effectiveness of the data collection and data characterization processes. A 2 V 5-1 factorial designed experiment was conducted to determine which of five input data characterization factors (for a simple series-parallel structure) may significantly affect availability model accuracy. The results from this experiment show that in this instance the factors under study do not have a significant effect on model output accuracy. Additional research is planned to more closely scrutinize the effects of these factors.

Environmental stress screening strategies for complex systems: A 3-level mixed distribution model

Abstract Environmental Stress Screening (ESS) is employed to reduce, if not eliminate, the occurrence of early field failures. In this paper, a three level ESS model is presented for a complex electronic system. Screening is performed at the component, board and system level. Components are screened for a specified duration before being assembled into printed circuit boards (PCBs). Defects introduced during the assembly of the PCBs are screened at the board level, while defects introduced during final assembly are screened at the system level. Components and connections are assumed to come from good and substandard populations and their times-to-failure distributions are modeled by mixed distributions. Mixed exponential distributions are used to model component timesto-failure and mixed Weibull distributions are used to model the times-to failure for board and system level connections. The mixed Weibull distributions are used to model wear-out characteristics at the board and system level. Optimal screen durations in the presence of wear-out are obtained by minimizing the systems life-cycle cost. ESS is shown to be a cost effective strategy when properly implemented. The optimal screening strategies are shown to be relatively robust to the system warranty period.

Choosing the best approach to matrix exponentiation

Abstract There is no ideal single approach to matrix exponentiation; an application may have some characteristic that enables or precludes a specific approach. Even methods that theoretically yield precise answers can produce extremely large errors when implemented in floating point arithmetic, and simply utilizing double or quadruple precision representations may not ensure accuracy. An empirical method is employed here to examine the efficacy of selected methods of matrix exponentiation for a particular application. The method centers around parametrizing a sample matrix in order to determine the effects of specific characteristics. The matrices to be exponentiated are upper triangular and stochastic. They may have nearly confluent eigenvalues, as well as widely divergent eigenvalues. Such problems are common in queueing applications using phase-type distributions. Scope and purpose The solution procedures for many modeling problems involve the exponentiation of matrices. Many competing approaches are available, each with advantages and potentially catastrophic disadvantages in different applications. This article summarizes some common procedures, and presents a comparative evaluation in a particular problem context (determination of state probabilities in a transient queueing system). Practitioners may find the evaluation to be a useful model for comparing exponentiation methods in another problem domain.

Input data characterization factors for complex systems affecting availability estimation accuracy

Reliability analysts are often faced with the challenge of characterizing the behavior of system components based on limited data. Insights into which data is most significant and how much data is necessary to achieve desired accuracy requirements would improve the efficiency and cost effectiveness of the data collection and data characterization processes. This research assesses potential significant factors in the probabilistic characterization of component failure and repair behavior with respect to their effect on system availability estimates. Potential factors were screened for significance utilizing a Plackett-Burman experimental design for several system models. Two input data characterization factors were found to have a significant affect on availability estimation accuracy: the size of the system and the number of data points used for component failure and repair distributional fitting. The estimating error was minimized when the structures analyzed were small and many data points (in this case, 25) were used for the distributional fittings. Surprisingly, the assumption of constant component failure rates and the use of empirical repair distributions were found to be equally effective component characterization methods. The results of this study also indicate that there is no apparent benefit in concentrating on important components for the highest fidelity distributional fittings.

A small satellite system design process

Satellites, like any complex system, require the application of a systematic, rational process for their design. Although the essential elements and overall structure of systematic design processes are common, each application may require some customization to be as effective as possible. The design process presented here combines features of two classic approaches. The resulting process was used to develop a preliminary design of a common bus for small tactical satellite applications.