A framework for diagnosing the delivery reliability performance of make-to-order companies
A framework for diagnosing the delivery reliability performance of make-to-order companies
复制标题
用于诊断按订单生产公司的交付可靠性绩效的框架
DOI：
10.1080/00207543.2011.643251
复制
发表时间：
2012
影响因子：
9.2
通讯作者：
G. Gaalman
中科院分区：
文献类型：
--
作者：
G. D. Soepenberg;M. Land;G. Gaalman
对于按订单生产(MTO)的公司来说，提高交付可靠性方面的绩效越来越重要。发现改进机会需要对当前绩效进行结构化诊断。一般的问题解决文献一般提供了诊断过程的结构，但根据要诊断的性能问题，需要基于特定领域的科学知识的理论框架。本文提出了一个诊断MTO公司交付可靠性绩效的框架。该框架由诊断树组成，该树构建了诊断过程，使人们能够从所取得的业绩导航到与生产计划和控制(PPC)相关的根本原因。能够构建不可靠交付的可能原因的理论基础是基于PPC文献中的最新科学发展。三个案例研究举例说明了该框架的使用。开发的框架在(1)选择正确的问题领域，(2)提供正确的诊断工具，以及(3)检测与PPC决策相关的原因方面显示了其独特的优势。它还支持从标准ERP软件包中提供的定量数据进行诊断，并支持使用来自基本决策过程的定性数据进行诊断三角测量。
Improving performance in terms of delivery reliability is increasingly important for make-to-order (MTO) companies. Detecting improvement opportunities requires a structured diagnosis of the current performance. General problem-solving literature provides structures for diagnosis processes in general, but – depending on the performance problem to be diagnosed – a theoretical framework based on domain-specific scientific knowledge is required. This paper presents a framework for diagnosing delivery reliability performance in MTO companies. The framework consists of a diagnosis tree that structures the diagnosis process, enabling one to navigate from the achieved performance to the underlying causes related to production planning and control (PPC). A theoretical foundation, enabling the possible causes of unreliable deliveries to be structured, is based on recent scientific developments in PPC literature. Three case studies exemplify the use of the framework. The developed framework shows its particular strengths in (1) selecting the right problem areas, (2) providing the right diagnosis instruments, and (3) detecting causes related to PPC decisions. It also supports diagnosis from quantitative data available in standard ERP software packages and enables diagnosis triangulation using qualitative data from the underlying decision processes.