Operation-dependent Failures Research Articles

Reliability evaluation of production systems with finite buffers subject to time-dependent and operation-dependent failures

Reliability evaluation of production systems with finite buffers subject to time-dependent and operation-dependent failures

Performance Analysis of Exponential Multi-Server Production Lines with Fluid Flow and Finite Buffers

This article presents an approximation method for fluid flow production lines with multi-server workstations and finite buffers. Each workstation consists of parallel identical servers, which are subject to operation-dependent failures with exponentially distributed uptimes and downtimes. The proposed method decomposes the production line into single-buffer subsystems, each described by a continuous state Markov process, the parameters of which are determined iteratively. The approximation method is appropriate for the analysis of longer production lines, able to accurately estimate performance characteristics (e.g., throughput and mean buffer content), and shown to perform well on a large test set.

Integrating production planning and maintenance: an iterative method

Purpose – Making decisions on production and maintenance separately, as is often done in practice and research literature, may not result in overall optimization. This paper aims to propose a joint method that better integrates production planning and maintenance at the tactical level. The potential of improving the performance of the classic planning method is also explored. Design/methodology/approach – An integrated production planning and maintenance model is proposed. The production capacity losses resulted from both preventive and corrective maintenance activities are considered. Meanwhile, the reliability deterioration of the machine is considered to be operation dependent. An iterative approach is presented to find a solution for the nonlinear model through iteratively solving a sequence of mixed integer linear programming instances, accompanied by modification of some parameters prior to each iteration. Computational experiments are conducted to evaluate the performance of the proposed method compared with three other methods, including two methods based on separate planning and one integrated model. Findings – The superiority of the proposed method compared with all the other three methods is demonstrated. Thus, the values of both integrated planning and considering operation-dependent failures are testified. The advantage of the proposed method is highlighted in the cases of high capacity utilization, long maintenance durations and low maintenance costs. The performance of the two methods based on separate planning is sensitive to the system utilization, and when utilization is high, the one with an availability-sensitive objective function defined for the maintenance problem performs better. Originality/value – Few studies have been carried out to integrate decisions on production lot and maintenance. Their considerations are either incomplete or not realistic enough. A more comprehensive and realistic integrated model is proposed in this paper, along with an iterative solution algorithm for it. A potential way to improve the performance of the classic planning method with its simplicity preserved is also presented.

Production rate of synchronous transfer lines using Monte Carlo simulation

In this paper, we consider unpaced synchronous transfer lines producing a single product. The transfer line stations are arranged in a series configuration, have no buffers, and are subject to operation-dependent failures. Throughput is an important performance measure for transfer lines, and we have adopted that measure. Analytical methods for determining capacity of such transfer lines are available only for the simplest systems, but we show Monte Carlo simulation to be a fast, flexible, easy, and accurate method of estimating throughput in lines of any length and having a wide range of operating characteristics.

An improved decomposition method for evaluating the performance of transfer lines with unreliable machines and finite buffers

In this paper, we consider transfer lines consisting of a series of machines separated by finite buffers. The processing time of each machine is deterministic and may be not identical. All machines are prone to operation-dependent failures, and the times between failures and the times to repair are assumed to be exponentially distributed. Many analytical methods have been developed to evaluate the performance of such lines. In general, these methods provide fairly accurate results. However, in some real cases where the orders of magnitude of machines’ reliability parameters (mean times between failures and mean times to repair) are not at the same level, the accuracy of these existing methods may not be good enough. The purpose of this paper is to propose an improved decomposition method that performs well even in the situation above. We use generalised exponential distributions instead of exponential distributions to approximate the repair-time distributions of the fictitious machines, and a new ADDX algorithm is developed to calculate the performance parameters such as the production rate and the average buffer levels. Numerical results indicate that the improved decomposition method provides more accurate results and converges in most cases. It is feasible and valid to evaluate the performance of transfer lines with unreliable machines and finite buffers.

Availability modelling and analysis of multi-product flexible transfer lines subject to random failures

Product requirements have changed dramatically in today’s industries forcing companies to implement flexible transfer lines manufacturing diverse product types. However, most of the researches dealing with transfer lines are so far limited to the mono-product and homogeneous lines (i.e., perfectly balanced). This paper addresses the problem of estimating the performance of multi-product, flexible transfer lines. Such lines are composed of several machines in series and can be used to manufacture a variety of products in a batch production environment. The machines are subject to random operation-dependent failures, and there are no intermediate buffers between adjacent machines. This paper aims to propose an analytical model for assessing the steady-state availability of such lines. A simulation model is also developed to mimic the real dynamic behaviour of flexible transfer lines. Thousands of production line configurations are tested in order to compare analytical results with simulation results. We used statistical tests to prove that the proposed formulae are exact and robust to model the steady-state availability of multi-product, unbuffered, flexible transfer lines subject to random failures.

Throughput assessment of mixed-model flexible transfer lines with unreliable machines

Most of the research that has been carried out to date to analyse transfer line performance is so far limited to the mono-product systems due to the complexity associated with multi-product considerations. In this paper, we consider mixed-model flexible transfer lines manufacturing several product types. The flexible transfer line workstations are arranged in a serial configuration, interconnected by an automatic transfer mechanism, and subject to operation-dependent failures. The throughput is an important tool for measuring the performance of transfer lines, and this paper establishes a method for assessing this throughput. A general simulation model is proposed, allowing a comparison of the performance of the proposed method with those of approximate existing techniques. Numerical computations show that the proposed formulae are robust to estimate the throughput of multi-product transfer lines, and that the results are very satisfactory.

Availability and throughput of unreliable, unbuffered production lines with non-homogeneous deterministic processing times

This paper studies production lines composed of several serial machines which are subject to random operation-dependent failures. The production lines have no intermediate buffers between adjacent machines. Machines have different deterministic processing times. The purpose of this paper is to propose analytical models to assess steady-state availability and throughput of such lines. Thousands of production line configurations have been experimented to compare the performance of the proposed approach to approximate existing techniques. A general simulation model was developed and statistical tests carried out to prove that the proposed approach is exact and robust to model unreliable, unbuffered, and non-homogeneous production lines.

Failure models and throughput rate of transfer lines

This paper addresses the impact of failure models on the performance of transfer lines composed of N machines separated by N − 1 buffers. The two most used failure models, operation-dependent failures (ODF) and time-dependent failures (TDF), are considered. A machine subject to TDF can fail even it is not working on a part. A machine subject to ODF cannot fail if it is not working on a part. A transfer line considered in this paper contains both machines subject to TDF and machines subject to ODF. Up times, repair times and processing times are continuous random variables of general distribution. We prove that modelling a machine subject to ODF of a transfer line as a machine subject to TDF, as usually done in the literature, leads to under-estimation of the throughput rate if the time between failures of the related machine is exponentially distributed while all other times are general random variables. We then propose a timed Petri net approach for performance evaluation and simulation of transfer lines with both machines subject to TDF and machines subject to ODF. Numerical results show that this result holds under more general conditions.

Simulation-based optimization of a single-stage failure-prone manufacturing system with transportation delay

This paper addresses the optimization of the continuous-flow model of a single-stage single-product manufacturing system with constant demand and transportation delay from the machine to the inventory. The machine is subject to either time-dependent or operation-dependent failures. The production is controlled by a hedging point policy. The goal is to determine the optimal hedging point, which minimizes the long-run average inventory holding and backlogging cost. Sample path analysis shows that the cost function is convex and sample gradient estimators are derived. A bi-section search algorithm based on simulation and sample gradients is proposed to determine the optimal hedging point.

Comparisons of two-machine line models in throughput analysis

Throughput analysis is important for the design, operation and management of manufacturing systems. Due to the large state space, exact analytical results only exist for two-machine serial lines. To analyse longer lines or more complex systems, the two-machine line model becomes the building block for further development. Therefore, many two-machine line models have been presented in the literature. A thorough understanding of the nature and differences of the various two-machine line models is critical for future analysis and development. In this paper, we study eight different two-machine models, categorized by synchronous and asynchronous lines with both time-dependent and operation-dependent failures, respectively. For each model, we introduce and compare the assumptions, calculation formulae, and their performance in system throughput. The results show that all the models exhibit similar performance with small differences, comparable to (or less than) the accuracy of data collection on the factory floor.

OPTIMAL CONTROL OF A CONTINUOUS-FLOW FAILURE PRONE MANUFACTURING SYSTEM

In this article the problem of inventory management of a single-stage single-product and two-machine-state continuous-flow manufacturing system with constant demand is considered. The machine is subject to operation-dependent failures. All the random variables are exponentially distributed. The goal is to obtain, in this case, the optimal policy which minimizes the discounted cost function. It is then proved that the optimal control is of hedging point type and that the value of the hedging point is nonnegative. This value is estimated by simulation.

Exact analysis of a discrete material three-station one-buffer merge system with unreliable machines

In this paper, a model of a discrete material flow line consisting of three unreliable machines and one buffer of limited capacity is analysed. A similar system, but with continuous flow of material was examined by Helber and Mehrtens (2001) and Tan (2001). In our system it is assumed that the buffer has two immediate preceding machines, performing the same operations and one immediate succeeding machine that receives material from the buffer. For the case where the buffer reaches its own capacity, one of the two preceding machines has priority over the other to dispose its processed part into the buffer. Processing times are assumed to be deterministic and identical for all machines and are taken as the time unit. Geometrically distributed operation dependent failures at the machines are assumed. All possible transition equations for the examined model are derived and a recursive algorithm that generates the transition matrix for any value N of the storage level is developed. Once the transition matrix is known the performance measures of the model under consideration can be easily evaluated. This model may be used as a building block in a decomposition method to evaluate large production systems with split/merge operations (for example, flow lines with quality inspections and rework loops).

Derivative Estimation for Buffer Capacity of Continuous Transfer Lines Subject to Operation-Dependent Failures

We derive estimators of throughput sensitivity to changes in buffer capacity for continuous flow models of a transfer line comprising two machines separated by a buffer of finite capacity, where machines are subject to operation-dependent failures, i.e., a machine cannot fail when it is idle. Both repair times and failure times may be general, i.e., they need not be exponentially distributed. The system is hybrid in the sense that it has both continuous dynamics—as a result of continuous material flow—and discrete events: failures and repairs. The combination of operation-dependent failures and buffer capacity as the parameter of interest make the derivative estimation problem difficult, in that unlike previous work on continuous flow models, careful use of conditional expectation (i.e., smoothed perturbation analysis) is required to obtain unbiased estimators.