Performance metrics in engineering change management - Key Performance Indicators and engineering change performance levels

2016 ◽  
Author(s):  
N. Kattner ◽  
T. Wang ◽  
U. Lindemann
Keyword(s):  
Change Management ◽  
Performance Indicators ◽  
Performance Metrics ◽  
Key Performance Indicators ◽  
Engineering Change ◽  
Performance Levels ◽  
Engineering Change Management

A Comparative Study of Engineering Change Management in Three Swedish Engineering Companies

1998 ◽  
Author(s):  
Peter Pikosz ◽  
Johan Malmqvist
Keyword(s):  
Change Management ◽  
Data Management ◽  
Product Data Management ◽  
Management Systems ◽  
Optimal Process ◽  
Engineering Change ◽  
Data Management Systems ◽  
Product Data ◽  
Engineering Change Management ◽  
Specific Factors

Abstract This paper analyses the engineering change management (EC) process in three engineering companies in Sweden. In the paper, the influence of various company specific factors, such as change leadtime, on the design of the EC process are analysed. The current use of computer support is surveyed and the possibility to apply a modern product data management (PDM) system to support the process is analysed. The paper also presents different strategies for improving the engineering change management process as well as of the product data management systems in order to achieve an optimal process.

scholarly journals Distinction of Domain-Specific and Cross-Domain Linkage Types for Engineering Change Management

2019 ◽  
Vol 1 (1) ◽  
pp. 1125-1134
Author(s):  
Robert Wilms ◽  
David Inkermann ◽  
Vadym Finn Cemmasson ◽  
Michael Reik ◽  
Thomas Vietor
Keyword(s):  
Change Management ◽  
Organizational Structures ◽  
Change Propagation ◽  
Engineering Change ◽  
Domain Specific ◽  
Engineering Change Management ◽  
Cross Domain ◽  
Product Models ◽  
Additional Costs ◽  
Engineering Changes

AbstractEngineering Changes (ECs) are substantial elements of the design process of technical products and are in particular relevant for companies due to enormous additional costs and time delays they can cause. In order to better understand ECs and realize efficient Engineering Change Management (ECM), different approaches exist. One aspect of ECM are change propagation analysis, which try to analyze knock-on effects of an EC on other product elements or the development process. How ECs can propagate is in particular difficult to assess for complex products realized within different engineering domains (mechanical, electrical and software engineering). To address this challenge, ECs are classified, strategies to cope with ECs are presented and change propagation approaches are analyzed in this paper. Thereby a lack of indicators for cross-domain propagation is identified. To overcome this issue, the distinction of domain-specific and cross-domain linkage types is proposed and a set of linkage types is presented. Further research is motivated to integrate these linkage types in product models while also considering processes and organizational structures as additional dimensions of ECM.

Systematic Decision Support for Engineering Change Management in PLM

2005 ◽  
Author(s):  
Nikhil Joshi ◽  
Farhad Ameri ◽  
Debasish Dutta
Keyword(s):  
Change Management ◽  
Lead Times ◽  
Change Orders ◽  
Engineering Change ◽  
Engineering Change Management ◽  
Industry Standard ◽  
Downstream Effects ◽  
Engineering Changes ◽  
Automated Tools ◽  
Change Requests

Engineering Change Management (ECM) is an important component of PLM. ECM modules in current PLM solutions conform to the industry-standard CMII closed-loop change model. They provide customised forms and pre-defined workflows for creating and processing change requests, change orders, etc. Evaluating the effects of the proposed Engineering Change on manufacturing processes, BOM, lead times, inventory, etc., usually form tasks in this generic workflow. However, each change has different downstream effects, which themselves lead to further changes that may not be evident. Identifying these impacts requires considerable experience and expertise. This paper addresses the need for automated tools to assist this process. The approach involves dynamic creation of workflow tasks for evaluating cascaded effects of any change using a predefined industry specific knowledge base. The process is further enhanced by prioritising the evaluation of effects based on experience generated by past engineering changes.

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