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Determining job complexity in an engineer to order environment for due date estimation using a proposed framework

机译:使用提议的框架确定工程师订购环境中的工作复杂度以进行到期日估算

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摘要

The engineer to order (ETO) environment is a common operating strategy found in industry today. ETO is a growing strategy as customers are increasingly demanding personalized solutions. In ETO, the engineering process is the largest controllable consumer of lead-time consuming one half of the total. A critical process is to determine engineering complexity for purposes of flow time prediction. One distinguishing factor of ETO is that each product is the culmination of a unique design prepared for a particular customer order. The only information available is limited to that which has been gathered during the quoting stage. Hence, the question becomes how does one determine the job difficulty in a complex transactional process when the job has not even been designed yet? This paper presents the results of a study that was conducted in conjunction with multiple ETO firms to identify factors which drive complexity in the engineering environment. One important application of these complexity factors is as a potential input to the accurate prediction of flow times. This paper presents a framework for using these complexity factors to predict ETO engineering flow times.
机译:工程师订购(ETO)环境是当今行业中常见的操作策略。随着客户对个性化解决方案的要求越来越高,ETO是一项不断发展的战略。在ETO中,工程流程是最大的可控提前期消耗者,消耗了总量的一半。一个关键的过程是确定工程复杂性,以预测流动时间。 ETO的一个独特因素是,每种产品都是针对特定客户订单准备的独特设计的最终产物。唯一可用的信息仅限于报价阶段收集的信息。因此,问题就变成了,即使尚未设计工作,如何在复杂的交易过程中确定工作难度呢?本文介绍了与多家ETO公司联合进行的一项研究的结果,以确定导致工程环境复杂化的因素。这些复杂性因素的一个重要应用是作为准确预测流动时间的潜在输入。本文提出了使用这些复杂度因素来预测ETO工程流程时间的框架。

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