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The purpose of this paper is to investigate the performance of unpaced reliable production lines that are unbalanced in terms of their mean operation times, coefficients of variation and buffer capacities.

Simulations were carried out for five‐ and eight‐station lines with various buffer capacities and degrees of means imbalance. Throughput, idle time and average buffer level performance indicators were generated and statistically analysed.

The results show that an inverted bowl allocation of mean service times, combined with a bowl configuration for coefficients of variation and a decreasing order of buffer sizes results in higher throughput and lower idle times than a balanced line counterpart. In addition, considerable reductions in average inventory levels were consistently obtained when utilizing a configuration of progressively faster stations, coupled with a bowl‐shaped pattern for coefficients of variation and an ascending buffer size order.

The results for these specific experiments imply that resources expended on trying to achieve a balanced line could be better used by seizing upon possible enhanced performance via controlled mean time, variability and buffer imbalance. Results are valid for only the line type and parameter values used (simulation results are specific and not general).

Guidelines are provided on design strategies for allocating labour and capital unevenly in unpaced lines for better performance in terms of increased throughput or lowered idle time or average buffer levels.

This paper might be viewed as one of the first simulation investigations into the performance of unpaced production lines with three sources of imbalance.

The purpose of this paper is to investigate the performance of unpaced unreliable production lines that are deliberately unbalanced in terms of their coefficients of variation (CVs).

A series of simulation experiments were carried out for five and eight station lines with mean buffer space set at one, two, four and six units. CVs were allocated in 12 different configurations for each of these lines.

The results show that the best unbalanced CV patterns in terms of throughput rates or idle times as compared to a balanced line counterpart are those where the steadiest stations are concentrated near the centre of the line. On the other hand, either concentrating the steadier operators towards the centre or close to the end of the line gives best average buffer level results.

The results provide guidelines for production line managers when designing unpaced unbalanced lines depending on their performance aims.

The investigation of the effects of unbalancing CVs in unreliable lines has not previously been studied and can provide insights into how best to place workstations with differing variability along the line.

The purpose of this paper is to develop a computer simulation model to evaluate the bowl phenomenon and the allocation at the end of the line of stations with either greater mean operation times or higher variability of operation times.

The model was developed on the basis of a realistic case problem and applied to a six‐station assembly line. The evaluation criteria were the: minimization of the total elapsed time; maximization of the average percentage of working time; and minimization of the average time in the system.

The performance of an assembly line with independently normally distributed operation times could be improved by applying the bowl phenomenon. The allocation of large operation mean times to stations located near the end of the line did not produce improved results. Instead a more balanced allocation proved to be more significantly effective. On the other hand, the assignment of larger variability of operation times to the stations near the end of the line improved the performance of the assembly line.

The investigation contributed to the computer simulation approach to solving assembly line problems that dealt with the impact of normally distributed operation times on the bowl phenomenon and assembly lines with increasing mean operation times and higher variability of operation times at the end of the line of stations.

Considers a class of control systems known as generalized kanban control systems (GKCS) which can be used to implement a pull control mechanism in a manufacturing system. In a GKCS, the production system is decomposed into stages, where each stage consists of a production sub‐system. There are two design parameters per stage: one controls the work‐in‐process in the stage and the other determines the maximum number of finished products of this stage. Investigates the influence of these design parameters on the efficiency of generalized kanban control policies by deriving qualitative properties as well as using experimental results on the behaviour of GKCS.

The purpose of this paper is to extend the optimal design problem of series manufacturing production lines to series‐parallel lines, where redundant machines and in‐process buffers are both included to achieve a greater production rate. The objective is to maximize production rate subject to a total cost constraint.

An analytical method is proposed to evaluate the production rate, and an ant colony approach is developed to solve the problem. To estimate series‐parallel production line performance, each component (i.e. each set of parallel machines) of the original production line is approximated as a single unreliable machine. To determine the steady state behaviour of the resulting non‐homogeneous production line, it is first transformed into an approximately equivalent homogeneous line. Then, the well‐known Dallery‐David‐Xie algorithm (DDX) is used to solve the decomposition equations of the resulting (homogenous) line. The optimal design problem is formulated as a combinatorial optimisation one where the decision variables are buffers and types of machines, as well as the number of redundant machines. The effectiveness of the ant colony system approach is illustrated through numerical examples.

Simulation results show that the analytical approximation used to estimate series‐parallel production lines is very accurate. It has been found also that ant colonies can be extended to deal with the series‐parallel extension to determine near‐optimal or optimal solutions in a reasonable amount of time.

The model and the solution approach developed can be applied for optimal design of several industrial systems such as manufacturing lines and power production systems.

The paper presents an approach for the optimal design problem of series‐parallel manufacturing production lines.

The purpose of this paper is to formulate a new problem of the optimal design of a series manufacturing production line system, and to develop an efficient heuristic approach to solve it. The optimal design objective is to maximize the efficiency subject to a total cost constraint.

To estimate series production line efficiency, an analytical decomposition‐type approximation is used. The optimal design problem is formulated as one of combinatorial optimization where the decision variables are buffers and types of machines. This problem is solved by developing and demonstrating a problem‐specific ant system algorithm. Numerical examples illustrate the effectiveness of the algorithm.

It has been found that this algorithm can always find near‐optimal or optimal solutions quickly. The approach developed in this paper for manufacturing lines can be adapted for power systems and telecommunication systems.

The paper presents a new approach for the optimal design of buffered series production lines. This optimization approach aims at selecting both the machines and the levels of buffers. The paper also develops an efficient solution approach based on the ant system meta‐heuristic.

In today′s rapidly changing market environment it has become necessary for manufacturing systems to have quick response times and high flexibility. This has led to the development of flexible manufacturing systems (FMS). Owing to its highly automated nature, a typical FMS has a high investment cost. Hence it becomes necessary to select the best configuration and decision rules at the design stage itself. The decision rules can have a substantial effect on the system performance. Attempts to simulate a particular FMS system. Applies different combinations of scheduling rules at the workstation buffers and at the loading buffer to the system and evaluates their effect on system performance.

A programme to simulate part flow in assembly automation, SIMAS, has been developed with support from Swiss industry. It allows the user to optimise investment as well as preview system behaviour.

Extant theory tends to treat Organizational Culture (OC) and fraud-related values as static, characterizing culture as synonymous with potential ethical values − but devoting less attention to how the culture and values arose and where they are headed. Buffer/conduit theory proposes that accountants learn to use a taxonomy containing three dynamic layers: collective fraud orientation, a buffer/conduit layer, and individual fraud orientation. The middle layer contains OC-related internal controls that buffer the orientation layers from spreading fraud-encouraging values, and serve as conduits transmitting fraud-deterring values − or, when controls do not function as intended, transmitting fraud-encouraging values. A factor analysis of 11 indicators of this three-layer taxonomy suggests that older generations of accounting practitioners apply the taxonomy, but millennials do not. Predisposition to commit fraud is especially salient to internally focused millennials, who uniquely perceive recruitment and training as compensating mechanisms and as collective buffers.

The purpose of this study is to develop a joint production, maintenance and quality control strategy involving a periodic preventive maintenance policy.

The proposed integrated policy is defined and modeled mathematically.

The paper focuses on finding simultaneously the optimal values of the preventive maintenance period, the buffer stock size, the sample size, the sampling interval and the control chart limits, such that the expected total cost per time unit is minimized.

The paper attempts to integrate in a single model the three main aspects of any manufacturing system: production, maintenance and quality. The considered system consists of one machine subject to a degradation process that directly affects the quality of products. The process and product quality control is carried out using an “x-bar” control chart. In the proposed model, a preventive maintenance action is performed every α inspections of product quality in order to reduce the shift rate to the “out-of-control” state. A corrective maintenance action is undertaken once the control limits are exceeded. In order to palliate perturbations caused by the stopping of the machine to undergo maintenance actions, a buffer stock is built up to ensure the continuous supply of the subsequent machine. The main goal of this work is to develop a model that captures the underlying link between the preventive maintenance policy, the buffer stock size and the parameters of an “x-bar” control chart used to control the quality of the product. Numerical experiments and a study of the effects of the input parameters variation on the obtained results are performed.

The existing models that simultaneously consider maintenance, inventory and control charts consist of a condition-based maintenance (CBM) policy. Periodic preventive maintenance (PM) has not been considered in such models. The proposed integrated model is original, in that it links production through buffer stocks, quality through a control chart and maintenance through periodic preventive maintenance (different practical settings and modeling approach than when CBM is used). Hence, this paper addresses practical situations where, for economic or technical reasons, only systematic periodic preventive maintenance is possible.