基于scoor模型的制革行业逆向物流监控系统的开发

Rangga Yudhista Kuswandi, Ari Yanuar Ridwan, R. M. El Hadi
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引用次数: 13

摘要

PT endes皮革公司印度尼西亚Sejahtera (Elco)是一家以生产服装皮革鞣制和手套为主要业务的中小型企业。在最近六个季度的销售中,PT Elco每个季度都从客户那里获得索赔,从而产生退货流程,即由于某种原因从客户那里取回产品给公司。目前,PT Elco的回运过程监控系统仍然非常小,只有几个关键绩效指标(kpi)得到监控。本研究的目的是确定在业务流程中的关键绩效指标,以返回鞣业。KPI将被映射到供应链操作参考(SCOR)模型中。在本研究中,有13个经过验证的kpi,并将根据SCOR中的性能属性进行分类,即可靠性、响应性、敏捷性、成本和资产管理。采用AHP法对各指标进行权重值搜索,采用归一化准则得到各指标的性能值。将每个属性的权重值与指标性能值相乘,得到每个属性的性能值,以百分比为单位输入到监控系统中,实现监控系统的指标、数字和数据可视化。该监控系统的实施有望帮助公司根据输入的数据准确、快速地做出与退货过程相关的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Monitoring Reverse Logistic System for Leather Tanning Industry using Scor Model
PT Endies Leather Company Indonesia Sejahtera (Elco) is a Small and Medium Business (SME) that manufactures garment leather tanning and gloves as the main business. In the last six quarters of sales, PT Elco obtained claims from customers every quarter, resulting in a return process, which is the retrieval of products from customers to the company for certain reasons. At this time, the monitoring system of the return process at PT Elco is still very minimal, and only a few Key Performance Indicators (KPIs) are monitored. This study aims to determine the KPI in the business process of returning the tanning industry. The KPI will be mapped into the Supply Chain Operation Reference (SCOR) model. In this study there were 13 verified KPIs and will be categorized based on the attributes of performance in SCOR, namely reliability, responsiveness, agility, cost, and asset management. All Indicator are searched for weight value per each attribute by using the AHP method and by using the normalization snorm de boer will get the performance value of each indicator. By multiplying the weight value per attribute with the indicator performance value, the performance value of each attribute will be obtained in percent units which will later be input into the monitoring system so that the monitoring system can show metrics, numbers and data visualization. The implementation of this monitoring system is expected to help companies make decisions that are related to the return process accurately and quickly based on the data entered.
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