A Development Of Optimal Buffer Allocation Determination Method For Μ-Unbalanced Unpaced Production Line

This research deals with a buffer allocation problem in an unpaced (asynchronous) μ-unbalanced production line. Kajian ini membincangkan masalah peruntukan pemampan di dalam talian pengeluaran tidak melangkah dengan ketidakseimbangan-μ

Survey instrument for measuring level of preparedness amongst healthcare personnel in radiation emergency

Drills and exercises are globally practiced to investigate the level of preparedness towards disaster events. However, these activities are rarely conducted because they require substantial investment, specifically to budget and time. A self-reported survey may serve as an alternative approach, although it may not be as effective as drills and exercises. As part of the survey development process, this article discusses preliminary validation of a survey instrument to measure the level of preparedness towards radiation emergency amongst healthcare personnel. Prior to this validation process, extensive literature reviews pointed out that the instrument consists of three constructs of preparedness, namely readiness, willingness, and ability. A total of seven subject matter experts were invited to judge the contents for verification purposes. Randolph Kappa analysis was then conducted to analyse their judgment to allow irrelevant items to be filtered from the rest prior to any improvements. Initially, the survey instrument consisted of 69 items; however, the analysis omitted 16 of them. The following values for each preparedness construct were: Readiness (0.77), Willingness (0.70), and Ability (0.73). These findings indicate that contents of the instrument are valid. Further analysis should be fulfilled to complete validation process to ensure its practicality prior to using it as an evaluation tool

Functional properties of throughput in tandem lines with unreliable servers and finite buffers

optimization;queueing theory;production

The impact of unequal processing time variability on reliable and unreliable merging line performance

Research on merging lines is expanding as their use grows significantly in the contexts of remanufacturing, reverse logistics and developing economies. This article is the first to study the behavior of unpaced, reliable, and unreliable merging assembly lines that are deliberately unbalanced with respect to their coefficients of variation (CV). Conducting a series of simulation runs with varying line lengths, buffer storage capacities and unbalanced CV patterns delivers intriguing results. For both reliable and unreliable lines, the best pattern for generating higher throughput is found to be a balanced configuration (equal CVs along both parallel lines), except for unreliable lines with a station buffer capacity of six. In that case, the highest throughput results from the descending configuration, i.e. concentrating the variable stations close to the beginning of both parallel lines and the steady stations towards the end of the line. Ordering from the least to most steady station also provides the best average buffer level. By exploring the experimental Pareto Frontier, this study shows the combined performance of unbalanced CV patterns for throughput and average buffer level. Study results suggest that caution should be exercised when assuming equivalent behavior from reliable and unreliable lines, or single serial lines and merging lines, since the relative throughput performance of some CV patterns changed between the different configurations

An Approximate analytical method to evaluate the performance of multi-product assembly manufacturing systems

The automotive industry is characterized by the continuous and frequent adoption of cutting edge technologies in manufacturing. The introduction of new technology often entails a system level investigation to determine whether it meets expected production requirements. Many system design alternatives are usually considered at this stage, and a fast performance evaluation tool is desired to quickly obtain the optimum system configuration. In this paper, we introduce an analytical tool that was developed for this specific purpose

Serial production line performance under random variation:Dealing with the ‘Law of Variability’

Many Queueing Theory and Production Management studies have investigated specific effects of variability on the performance of serial lines since variability has a significant impact on performance. To date, there has been no single summary source of the most relevant research results concerned with variability, particularly as they relate to the need to better understand the ‘Law of Variability’. This paper fills this gap and provides readers the foundational knowledge needed to develop intuition and insights on the complexities of stochastic simple serial lines, and serves as a guide to better understand and manage the effects of variability and design factors related to improving serial production line performance, i.e. throughput, inter-departure time and flow time, under random variation

Evaluation of stochastic flow lines with provisioning of auxiliary material

Flow lines are often used to perform assembly operations in multi-stage processes. During these assembly operations, components that are relatively small, compared to the work pieces travelling down the flow line, are mounted to the work pieces at a given stage. Those components, or more generally, any kind of auxiliary material, are provisioned to the corresponding production stage in a repetitive but not necessarily deterministic manner using a certain delivery frequency, each time filling the local storage up to a predetermined order-up-to level. Just like random processing times, machine failures, and repairs, the randomness of the provisioning process can impact the long-term throughput of such a flow line. In this paper, we develop a fast and accurate analytical performance evaluation method to estimate the long-term throughput of a Markovian flow line of this type for the practically important case of limited buffer capacities between the production stages. We first give an exact characterization of a two-machine line of that type and show how to determine system state probabilities and aggregate performance measures. Furthermore, we show how to use this two-machine model as the building block of an approximate decomposition approach for longer flow lines. As opposed to previous decomposition approaches, even the state space of the two-machine lines can become so large that an exact solution of the Markov chains can become impractical. We hence show how to set up, train, and use an artificial neural network to replace the Markov chain solver embedded in the decomposition approach, which then leads to an accurate and extremely fast flow line evaluation tool. The proposed methodology is evaluated by a comparison with simulation results and used to characterize the structural patterns describing the behaviour of flow lines of this type. The method can be used to systematically consider the combined impact of the delivery frequency and the local order-up-to levels for the auxiliary material when designing a flow line of this type