基于西格玛水平的供应链绩效评价方法

发布时间：2018-02-11 12:49

本文关键词： 供应链绩效评价供应链运作参考模型西格玛水平层次分析法流通率　出处：《南京理工大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着企业与企业之间的竞争转变为供应链与供应链之间的竞争,如何提高供应链的绩效与竞争力,从而使企业在激烈的竞争中立于不败之地,成为当务之急的问题。而供应链绩效评价,可以对企业供应链的营运能力进行综合评价,分析供应链的管理绩效,找出供应链中的薄弱环节,以提高供应链绩效,提升供应链整体竞争力。因此,供应链绩效评价对于优化供应链,提高供应链竞争力非常重要,是供应链管理领域的重要组成部分。然而供应链绩效评价往往只关注综合绩效,对于节点企业的绩效如何,并没有太多关注,这不利于找到供应链中的最短板,提出针对性的改进措施。而六西格玛管理中的流通率指标,不仅可以对供应链整体的绩效进行衡量,还可以对供应链上节点企业的绩效进行衡量,从而找出“隐藏工厂”。此外,六西格玛管理中的西格玛水平指标由于无量纲的特性,可以简化供应链绩效评价中繁琐的计算过程。因此,本文将六西格玛指标用于供应链绩效评价。本文分析了经典的供应链绩效评价模型,在供应链运作参考模型的基础上提出了指标体系。该指标体系在原有流程和财务指标的基础上,新增了可持续发展能力指标,共有目标层、准则层1、准则层2和操作层等四个层次,并对操作层进行了细分,从而使得体系易于操作、实用性强。传统指标评估多采用主观法,给绩效评价带来了消极影响,而本文用公式将操作层指标量化。此外,由于一些指标是望大型指标,而另一些指标是望小型指标,或是取值范围不一,因此需对指标进行一致化和归一化处理,并用西格玛水平衡量指标绩效值。本文首先在确定指标和节点企业权重时,采用基于三角模糊数的层次分析法。本方法不仅体现了人类判断的模糊性,还避开了矩阵一致性检验的问题。其次,提出流通率的模糊层次分析改进方法,克服了以往没有权重,或是客观权重对样本依赖性过强的缺点。再次,由于不同的供应链类型,流通率的计算方法不同,因此本文将从串联、并联和混联角度考虑流通率的计算,并把节点企业的绩效转换为衡量供应链整体的绩效。最后,给出了供应链综合绩效评价的方法,并通过一个跨国家电制造行业的混联型供应链验证了此方法的有效性,用雷达图给出了最终的数据结果。
[Abstract]:With the competition between enterprises changing into the competition between supply chain and supply chain, how to improve the performance and competitiveness of supply chain, so that enterprises in the fierce competition in an invincible position, The performance evaluation of supply chain can comprehensively evaluate the operation ability of enterprise supply chain, analyze the management performance of supply chain, find out the weak link in supply chain, and improve the performance of supply chain. Therefore, supply chain performance evaluation is very important to optimize supply chain and improve supply chain competitiveness, which is an important part of supply chain management. However, supply chain performance evaluation usually only pays attention to comprehensive performance. There is not much attention to the performance of the node enterprises, which is not conducive to finding the shortest board in the supply chain and putting forward targeted improvement measures. Not only can the performance of the supply chain as a whole be measured, but also the performance of the node enterprises in the supply chain can be measured to find the "hidden factory." in addition, the six Sigma level indicators are dimensionless because of their dimensionless characteristics. Therefore, this paper applies six Sigma indicators to supply chain performance evaluation. This paper analyzes the classic performance evaluation model of supply chain, and puts forward the index system based on the reference model of supply chain operation. There are four levels: goal layer, criterion layer 1, criterion layer 2 and operation layer, and the operation layer is subdivided to make the system easy to operate and practical. The traditional index evaluation mostly adopts subjective method, which brings negative impact to performance evaluation. In addition, because some indexes are large and others are small or have different values, it is necessary to unify and normalize the indicators. Using Sigma level to measure the performance of indicators. In this paper, the analytic hierarchy process (AHP) based on triangular fuzzy number is used to determine the index and the weight of nodal enterprises. This method not only reflects the fuzziness of human judgment, but also avoids the problem of matrix consistency test. An improved fuzzy analytic hierarchy process (FAHP) method for flow rate is proposed, which overcomes the shortcomings of no weight in the past, or the objective weight is too dependent on the sample. Thirdly, because of different supply chain types, the calculation method of circulation rate is different. Therefore, this paper will consider the calculation of flow rate from the point of view of series, parallel and hybrid, and convert the performance of node enterprises to measure the overall performance of supply chain. Finally, this paper gives the method of comprehensive performance evaluation of supply chain. The effectiveness of this method is verified by a hybrid supply chain in a multinational home appliance manufacturing industry. The final data results are given by radar diagrams.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F274

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