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Development of a two-stage network data envelopment analysis (DEA) model to analyze production line's performance : combination of automation and labor

机译:开发用于分析生产线性能的两阶段网络数据包络分析(DEA)模型:自动化与人工相结合

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摘要

Nowadays, the growth of industry can be seen as a nature of the world. Each company race again each other to increase productivity to produce new, high quality and product that fulfil customer demand. One can achieve the Key Performance Indicator (KPI) or targeted goal but without considering the cost, manpower, time or others elements is inefficient toward productivity. Upgrade production line in manufacturing industry needs huge investment to come out with good performance. The company can receive Return of Investment (ROI) and save more money from paying labor salary and increase productivity. However, the company also may have the risk of losing their money from the investment done without proper production line evaluation. In this research, we studied the effectiveness of production Jine that equipped withudcombination between automation usage and labor to determine the productivity and quality of the production line. Then, compare those production line with production line that use labor energy. As a case study, this research focuses on the production line that producing a product with a high and continues demand to observe how the investment on automation can give good return or otherwise. Therefore, the model of Two-Stage Network DEA was developed in order to measure those production line in different stages. As a result, the evaluation of data through this model will show all the effectiveness of the production line. The model will benefit the related industries in their performance by show the efficiency of each production line then company can make improvement toward those inefficient production line.
机译:如今,工业的增长可以看作是世界的本质。两家公司都在相互竞争,以提高生产率,生产出满足客户需求的高质量新产品。一个人可以实现关键绩效指标(KPI)或目标目标,但不考虑成本,人力,时间或其他因素就无法提高生产力。制造业升级生产线需要大量投资才能取得良好的业绩。该公司可以获得投资回报(ROI),并节省了支付工资的更多钱,并提高了生产率。但是,如果没有适当的生产线评估,公司也可能会因进行的投资而蒙受损失。在这项研究中,我们研究了在自动化使用和人工之间配备组合的生产Jine的有效性,以确定生产线的生产率和质量。然后,将那些生产线与使用劳动力的生产线进行比较。作为案例研究,该研究集中于生产具有高且持续需求的产品的生产线,以观察对自动化的投资如何能带来良好的回报或其他回报。因此,开发了两阶段网络DEA模型,以测量不同阶段的生产线。结果,通过此模型进行的数据评估将显示生产线的所有有效性。该模型将通过显示每个生产线的效率来使相关行业的绩效受益,然后公司可以对那些效率低下的生产线进行改进。

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    Nik Afieza Che Azhar;

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  • 年度 2016
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