增值指数-不间断存在时间中包含的直接工作的份额

Christopher Görsch, Zhao Jianyu, O. Seppänen
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引用次数: 1

摘要

持续改进依赖于适当的生产力措施。生产力可以通过时间运动研究来衡量,但在很大程度上依赖于人工工作,因此在动态环境(如建筑)中对实时意识的贡献不足。基于低功耗蓝牙技术,室内定位实时显示建筑工人VA (value - added)的潜在决定份额。不同的研究表明,VA和生产力之间存在正相关关系。然而,从位置数据中无法得知有多少员工在现场工作。将这两种方法同时应用于一名工人,本文展示了如何在数字上量化直接工作(DW)和直接工作价值量。这些组合数据可以显示在应用阈值时检测到不间断存在时发生的直接工作价值量和直接工作价值量,表明在工作场所内花费的最小持续时间。利用小数据样本进行概念验证测试,并得出DW和VA的数值量化结果。初步结果表明,不间断存在时间越长,DW和VA的比例越大。未来的研究需要扩大纳入的数据。如果研究结果成立,不间断的高阈值存在可以更准确地实时预测员工的VA水平。该研究还通过将工人现场行为与监测运动的监测技术联系起来,有助于知识对施工产生积极影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Value-Adding Index - Share of Direct Work Included in Uninterrupted Presence Time
Continuous improvement depends on appropriate productivity measures. Productivity can be measured through time-motion studies but relies heavily on manual efforts and therefore contributes insufficiently to real-time awareness in dynamic environments such as construction. Indoor positioning shows potential determining shares of construction workers VA (Value-adding), based on Bluetooth Low Energy technology in real-time. Different studies show positive correlations between VA and productivity. However, it is unknown from location data how much workers engage in VA work while being present. Applying both methods simultaneously to one worker, this paper shows how to numerically quantify direct work (DW) and VA. Such combined data can show how much VA and DW occur when uninterrupted presence is detected while applying thresholds, indicating minimum durations spent inside work locations. Utilizing a small data sample enabled proof-of-concept testing and resulted in numerical quantifications of DW and VA. Preliminary findings show larger proportions of DW and VA when uninterrupted presence time is higher. Future research needs to enlarge the included data. If findings hold true, uninterrupted presence with higher thresholds could predict more accurate workers´ VA levels in real-time. The study also contributes to knowledge positively impacting construction by bridging workers’ behaviors on-site with monitoring technologies detecting movement.
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