An analytical formula for variance of output from a series-parallel production system with no interstation buffers and time-dependent failures

This paper presents a method to determine the mean and the variance of the amount of materials produced in a fixed time interval by a continuous materials flow production system with N stations in series and M stations in parallel and no interstation buffers. Unreliable stations with exponential failure and repair times, time dependent failures, and deterministic processing times are considered. Closed-form expressions for the asymptotic mean and variance of the amount of materials produced per unit time are given for series, parallel, and series-parallel production systems with identical stations. It is shown that the distribution of the amount of materials produced in a fixed time is asymptotically normal. By using this property, effects of variability on the due-date performance are investigated by considering the probability of meeting a customer order on time. Numerical experiments that explore some relationships among performance measures and production system parameters are also presented.     

Asymptotic variance rate of the output of a transfer line with no buffer storage and cycle-dependent failures

In this study the variability properties of the output of transfer lines are investigated. The asymptotic variance rate of the output of an N-station synchronous transfer line with no interstation buffers and cycle-dependent failures is analytically determined. Unlike the other studies, the analytical method presented in this study yields a closed-form expression for the asymptotic variance rate of the output. The method is based on a general result derived for irreducible recurrent Markov chains. Namely, the limiting variance of the number of visits to a state of an irreducible recurrent Markov chain is obtained from the n-step transition probability function. Thus, the same method can be used in other applications where the limiting variance of the number of visits to a state of an irreducible recurrent Markov chain is of interest. Numerical results show that the asymptotic variance rate of the output does not monotonically increase as the number of stations in the transfer line increases. The asymptotic variance rate of the output may first increase and then decrease depending on the station parameters. This property of the production rate is investigated through numerical experiments and the results are presented.     

Asymptotic variance rate of the output in production lines with finite buffers

Production systems that can be modeled as discrete time Markov chains are considered. A statespacebased method is developed to determine the variance of the number of parts produced per unit time in the long run. This quantity is also referred to as the asymptotic variance rate. The block tridiagonal structure of the probability matrix of a general twostation production line with a finite buffer is exploited and a recursive method based on matrix geometric solution is used to determine the asymptotic variance rate of the output. This new method is computationally very efficient and yields a thousandfold improvement in the number of operations over the existing methods. Numerical experiments that examine the effects of system parameters on the variability of the performance of a production line are presented. The computational efficiency of the method is also investigated. Application of this method to longer lines is discussed and exact results for a threestation production line with finite interstation buffers are presented. A thorough review of the pertinent literature is also given.     

Modelling and scheduling of an asynchronous cyclic production line with multiple parts

In this study, we model and analyse a production line with asynchronous part transfers, processing time variability, and cyclic scheduling in the same framework. We consider a production line with multiple parts and finite interstation buffers. The line produces a batch of n jobs repetitively using the same order of jobs in every batch. The processing time of a job on a station is a random variable and is assumed to have a phase-type distribution. Parts are transferred between the stations in an asynchronous manner. We first present a continuous time Markov chain model to analyse the performance of this system for a given sequence. A state-space representation of the model and the associated rate matrix are generated automatically. The steady state probabilities of the Markov chain are determined by using a recursive method that exploits the special structure of the rate matrix. The cycle time, the production rate, and the expected Work-In-Progress (WIP) inventory are used as the main performance measures. We then present an approximate procedure to determine the cyclic sequence that minimises the cycle time. We then investigate the effects of operating decisions, system structure, processing time variability, and their interaction in the same framework. Numerical results for the performance evaluation and scheduling of cyclic production lines are also presented.     

An analytic formula for the mean throughput of K-station production lines with no intermediate buffers

Using the holding time model (HTM) method, an approximate analytic formula is derived for calculating the average throughput of a K-station production line with exponential service times, manufacturing blocking and no intermediate buffers between adjacent stations. The usefulness of the proposed analytical formula relies on the fact that it can handle the (general) case of workstations with different mean processing times — this being the contribution of this work compared against that of Alkaff and Muth — provided a good estimation of some coefficients involved is being made. By doing this for the balanced lines case, a simple formula is proposed with very good numerical results.     

Representation and analysis of transfer lines with machines that have different processing rates

A transfer line is a tandem production system, i.e. a series of machines separated by buffers. Material flows from outside the system to the first machine, then to the first buffer, then to the second machine, the second buffer, and so forth. In some earlier models, buffers are finite, machines are unreliable, and the times that parts spend being processed at machines are equal at all machines. In this paper, a method is provided to extend a decomposition method to large systems in which machines are allowed to take different lengths of time performing operations on parts. Numerical and simulation results are provided.     

带缓冲串行生产系统预防性维护建模及运行参数优化研究

为了保证串行生产系统的产能和提高系统可靠性,提出了带缓冲区的串行生产系统预防性维护决策模型。首先,分析了生产线各执行单元可靠性和运行参数之间的关系,建立了考虑执行单元运行参数和缓冲库存的维护模型。在此基础上,结合串行生产线的特点,建立综合考虑维护成本、有效运行速度和缓冲库存的多目标优化函数。最后,构建启发式算法求解目标函数,并以串行包装生产线为例进行仿真实验分析,结果表明本文所建模型是有效且实用的。     

Pooling in tandem queueing networks with non-collaborative servers

This paper considers pooling several adjacent stations in a tandem network of single-server stations with finite buffers. When stations are pooled, we assume that the tasks at those stations are pooled but the servers are not. More specifically, each server at the pooled station picks a job from the incoming buffer of the pooled station and conducts all tasks required for that job at the pooled station before that job is placed in the outgoing buffer. For such a system, we provide sufficient conditions on the buffer capacities and service times under which pooling increases the system throughput by means of sample-path comparisons. Our numerical results suggest that pooling in a tandem line generally improves the system throughput—substantially in many cases. Finally, our analytical and numerical results suggest that pooling servers in addition to tasks results in even larger throughput when service rates are additive and the two systems have the same total number of storage spaces.     

A polynomial time algorithm for solving a quality control station configuration problem

We study unreliable serial production lines with known failure probabilities for each operation. Such a production line consists of a series of stations; existing machines and optional quality control stations (QCS). Our aim is to simultaneously decide where and if to install the QCSs along the line and to determine the production rate, so as to maximize the steady state expected net profit per time unit from the system.We use dynamic programming to solve the cost minimization auxiliary problem where the aim is to minimize the time unit production cost for a given production rate. Using the above developed O(N²) dynamic programming algorithm as a subroutine, where N stands for the number of machines in the line, we present an O(N⁴) algorithm to solve the Profit Maximization QCS Configuration Problem.     

Throughput,flow times,and service level in an unreliable assembly system

This paper considers an unreliable assembly network where different types of components are processed by two separate work centers before being merged at an assembly station. The operation complexity of the system is a result of finite inter-station buffers, uncertain service times, and random breakdowns that lead to blocking at the work centers and starvation at the assembly station. The objective of this study is to gain an understanding of the behavior of such systems so that we can find a way to maximize the system throughput while maintaining the required customer service level. By constructing appropriate Markov processes, we obtain the probability distribution of the production flow time and derive formulas for throughput, the loss probability of type-2 workpieces, and the mean flow time. We present expressions for average work-in-process (WIP) and study their monotone properties. Using the distribution of the flow time, a customer service level can be defined and computed. We then formulate a system optimization model that can be used to maximize the throughput while maintaining an acceptable service level.     

Transient analysis of a single server queue with catastrophes, failures and repairs

A transient solution is obtained analytically using continued fractions for the system size in an M/M/1 queueing system with catastrophes, server failures and non-zero repair time. The steady state probability of the system size is present. Some key performance measures, namely, throughput, loss probability and response time for the system under consideration are investigated. Further, reliability and availability of the system are analysed. Finally, numerical illustrations are used to discuss the system performance measures.      

A Priority Tandem Queue with No Intermediate Buffer

Priority queues are important in modelling and analysis of manufacturing systems, and computer and communication networks. In this paper, a priority tandem queueing system with two stations in series is studied. There is no intermediate buffer between the two stations, and the lack of buffers may cause blocking at the first station. K types of customers arrive at the system according to Poisson processes. The expected delay in the system for each type of customer is obtained when all the customers have the same service time distribution at the second station. Two cases are studied in detail when service times are either all exponentially distributed or all deterministic.     

Partial Pooling in Tandem Lines with Cooperation and Blocking

For a tandem line of finite, single-server queues operating under the production blocking mechanism, we study the effects of pooling several adjacent stations and the associated servers into a single station with a single team of servers. We assume that the servers are cross-trained (so that they can work at several different stations) and that two or more servers can cooperate on the same job. For such a system, we provide sufficient conditions on the service times and sizes of the input and output buffers at the pooled station under which pooling will decrease the departure time of each job from the system (and hence increase the system throughput). We also show that pooling decreases the total number of jobs in the system at any given time and the sojourn time of each job in the system if the departure time of each job from the system is decreased by pooling and there is an arrival stream at the first station. Moreover, we provide sufficient conditions under which pooling will improve the holding cost of each job in the system incurred before any given time, and extend our results to closed tandem lines and to queueing networks with either a more general blocking mechanism or probabilistic routing. Finally, we present a numerical study aimed at quantifying the improvements in system performance obtained through pooling and at understanding which stations should be pooled to achieve the maximum benefit. Our results suggest that the improvements gained by pooling may be substantial and that the bottleneck station should be among the pooled stations in order to obtain the greatest benefit. AMS subject classification: 90B22     

Bounding blocking probabilities and throughput in queueing networks with buffer capacity constraints

We propose a new technique for upper and lower bounding of the throughput and blocking probabilities in queueing networks with buffer capacity constraints, i.e., some buffers in the network have finite capacity. By studying the evolution of multinomials of the state of the system in its assumed steady state, we obtain constraints on the possible behavior of the system. Using these constraints, we obtain linear programs whose values upper and lower bound the performance measures of interest, namely throughputs or blocking probabilities. The main advantages of this new technique are that the computational complexity does not increase with the size of the finite buffers and that the technique is applicable to systems in which some buffers have infinite capacity. The technique is demonstrated on examples taken from both manufacturing systems and communication networks. As a special case, for the M/M/s/s queue, we establish the asymptotic exactness of the bounds, i.e., that the bounds on the blocking probability asymptotically approach the exact value as the degree of the multinomials considered is increased to infinity. This revised version was published online in June 2006 with corrections to the Cover Date.     

Exact analysis of asymmetric random polling systems with single buffers and correlated input process

We introduce a simple approach for modeling and analyzing asymmetric random polling systems with single buffers and correlated input process. We consider two variations of single buffers system: the conventional system and the buffer relaxation system. In the conventional system, at most one customer may be resided in any queue at any time. In the buffer relaxation system, a buffer becomes available to new customers as soon as the current customer is being served. Previous studies concentrate on conventional single buffer system with independent Poisson process input process. It has been shown that the asymmetric system requires the solution ofm 2 ^m –1) linear equations; and the symmetric system requires the solution of 2 ^m–1–1 linear equations, wherem is the number of stations in the system. For both the conventional system and the buffer relaxation system, we give the exact solution to the more general case and show that our analysis requires the solution of 2 ^m –1 linear equations. For the symmetric case, we obtain explicit expressions for several performance measures of the system. These performance measures include the mean and second moment of the cycle time, loss probability, throughput, and the expected delay observed by a customer.     

Multi-state throughput analysis of a two-stage manufacturing system with parallel unreliable machines and a finite buffer

This paper models and analyzes the throughput of a two-stage manufacturing system with multiple independent unreliable machines at each stage and one finite-sized buffer between the stages. The machines follow exponential operation, failure, and repair processes. Most of the literature uses binary random variables to model unreliable machines in transfer lines and other production lines. This paper first illustrates the importance of using more than two states to model parallel unreliable machines because of their independent and asynchronous operations in the parallel system. The system balance equations are then formulated based on a set of new notations of vector manipulations, and are transformed into a matrix form fitting the properties of the Quasi-Birth–Death (QBD) process. The Matrix-Analytic (MA) method for solving the generic QBD processes is used to calculate the system state probability and throughput. Numerical cases demonstrate that solution method is fast and accurate in analyzing parallel manufacturing systems, and thus prove the applicability of the new model and the effectiveness of the MA-based method. Such multi-state models and their solution techniques can be used as a building block for analyzing larger, more complex manufacturing systems.     

Approximate analysis of production systems

In this paper complex production systems are studied where a single product is manufactured and where each production unit stores its output in at most one buffer and receives its input from at most one buffer. The production units and the buffers may be connected nearly arbitrarily. The buffers are supposed to be of finite capacity and the goods flow is continuous. For such netwroks it is possible to estimate the throughput by applying repeated aggregation over the production units. The approximation appears to be best when the network shows some resemblance with a flow line.     

An integrated inventory model with controllable lead time and distribution‐free demand

The impact of lead time reduction on an integrated periodic review inventory system comprising a single vendor and multiple buyers with a step crashing cost function and service‐level constraints is studied. The probability distribution of demand during the protection period for each buyer is unknown, but the mean and the variance are given. Each production lot of the vendor can be delivered in a number of shipments to all buyers. A minimax distribution‐free procedure with Lagrange multipliers is applied to determining the lead time, the common shipment cycle time, the target levels of replenishments and the number of shipments per production cycle so that the expected total system cost is minimized. Numerical experiments along with sensitivity analysis were performed to illustrate the effects of parameters on the decision and the total system cost. Copyright © 2009 John Wiley & Sons, Ltd.     

Regenerative pull (Kanban) production control policies

A production system consists of a set of parallel robotic cells manufacturing parts for several distinct work stations. The stations order parts from these cells and withdraw parts from their buffers only at the rate and at the time of consumption. The desired decision vector provides for the instantaneous number of cells assigned to produce parts for each work station. Two novel tractable and optimal regenerative pull (‘Kanban’) control policies are formulated: one policy minimizes the weighted starvation penalty, while the other maximizes the weighted throughputs per unit time. Following these regenerative policies the production schedules are re-evaluated at each decision epoch to mitigate the effects of processing time variability.Several important properties regarding the inherent interaction between the structure of the optimal policy, the performance of the system and the desired allocation of productive capabilities among the manufacturing resources are examplified. It is shown that the optimal policy attempts to marginally assign as much of the cells capacity as possible to certain critical part types. Substantial changes in the structure of the optimal policy, resulting either from incrementing the number of cells or from increasing their capacity, are also identified. More generally, attention is drawn to the qualitative behavior of the optimal pull control policy in certain manufacturing systems with stochastic processing rates.     

Probabilistic analysis of redundant systems with human errors and common-cause failures

This paper presents two mathematical models representing three unit redundant systems with common cause failures and human errors. Reliability, steady state availability, mean time to failure (MTTF) and variance of time to failure formulas are developed for both models. Supplementary variables and Markov techniques were employed to obtain the resulting expressions. Reliability, availability, failure probability and MTTF plots are .shown