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.

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.

scholarly journals USING A CROSS-DOMAIN PRODUCT MODEL TO SUPPORT ENGINEERING CHANGE MANAGEMENT

2020 ◽  
Vol 1 ◽  
pp. 1165-1174
Author(s):  
R. Wilms ◽  
P. Kronsbein ◽  
D. Inkermann ◽  
T. Huth ◽  
M. Reik ◽  
...  
Keyword(s):  
Change Management ◽  
Product Design ◽  
Change Propagation ◽  
Product Model ◽  
Engineering Change ◽  
Engineering Change Management ◽  
Cross Domain ◽  
Product Models ◽  
Engineering Changes ◽  
Support Engineering

AbstractEngineering changes (ECs) and engineering change management (ECM) are crucial for successful product design processes (PDP). Due to the increasing complexity of today's products (like vehicles) and the interaction of different engineering domains (mechanics, electric/electronics, software) involved in the PDP, cross-domain EC impact assessments as well as processes are required. To better support engineers in assessing change propagation across domains and products, existing approaches for ECM product models are analyzed in this paper and an enhanced product model is derived using MBSE.

Part Change Management: A Case Study on Automotive OEM Development and Production Perspectives

2017 ◽  
Author(s):  
Stephan Knackstedt ◽  
Joshua D. Summers
Keyword(s):  
Statistical Analysis ◽  
Change Management ◽  
Employee Perceptions ◽  
Management Process ◽  
Engineering Change ◽  
Engineering Change Management ◽  
Production Development ◽  
Engineering Changes

Due to interest in aspects such as process, strategies, and tools of engineering changes expressed in a literature review, a case study was done on a major automotive OEM to assess the perceived quality of its part engineering change management process and supporting system through its employees’ eyes. A combination of 12 interviews lasting 12 hours and 46 written surveys was used to capture the views of participants from all major functions found at the research and development (R&D) headquarters of the OEM: Purchasing, Production, Development, and one group consisting of all other functions (“Other”). Statistical analysis was performed to identify statistically significant differences between employee perceptions of an engineering change management system among different departments, amount of use, and years of use. It was found that statistically significant differences exist in terms of understanding the usability of the system between different departments and also between different years of experience.

Managing engineering change requirements during the product development process

2017 ◽  
Vol 26 (2) ◽  
pp. 171-186 ◽  
Author(s):  
Inayat Ullah ◽  
Dunbing Tang ◽  
Qi Wang ◽  
Leilei Yin ◽  
Ishfaq Hussain
Keyword(s):  
Product Development ◽  
Change Management ◽  
Development Process ◽  
Product Development Process ◽  
Engineering Change ◽  
New Approach ◽  
Engineering Change Management ◽  
Engineering Changes ◽  
Optical Mouse

Product redesign is not a straightforward task, specifically for complex commodities. Engineering change requirements can be evoked in any phase of the product development process, thus making engineering change management a challenging task. The motive of this study is to explore the best possible way of managing engineering change requirements taking execution sequence of change requirements into consideration. In this article, a new approach supporting engineering change requirements implementation sequence, by considering the risk associated with engineering changes, is presented. The risk of the redesign is hard to foresee since the engineering change effects are being dispersed from the instigating component to other associated components. In this article, the term of rework-risk is used for the amount of rework needed to be done to redesign the products’ components. The practicality of suggested method is analyzed using the redesign of an optical mouse as a case study. Managing engineering change requirements in a group with proper sequence can ensue with a 15% decrease in the redesign duration as compared with the prompt implementation of engineering change requirements. Conversely, it can also cause 36.23% increase in the redesign duration, if not handled in an appropriate sequence. The results from a single, simple case, indicates that running engineering change requirement batches can be beneficial.

A Knowledge Discovery in Databases (KDD) Approach for Extracting Causes of Iterations in Engineering Change Orders

2011 ◽  
Author(s):  
Fatos Elezi ◽  
Armin Sharafi ◽  
Alexander Mirson ◽  
Petra Wolf ◽  
Helmut Krcmar ◽  
...  
Keyword(s):  
Change Management ◽  
Knowledge Discovery ◽  
Lead Time ◽  
Knowledge Discovery In Databases ◽  
Data Set ◽  
Change Orders ◽  
Engineering Change ◽  
Engineering Change Management ◽  
The Impact ◽  
Automatic Text

This paper describes an implementation of a Knowledge Discovery in Databases (KDD) process for extracting the causes of iterations in Engineering Change Orders (ECOs). A data set of approximately 53,000 historical Engineering Change Orders (ECOs) was used for this purpose. Initially, the impact of iterations in ECO lead time and uncertainty is assessed. Subsequently, a semi-automatic text-mining process is employed to classify the causes of iterations. As a result, cost and technical categories of causes were identified as the main reasons for the occurrence of iterations. The study concludes that applying KDD in historic ECO data can help in identifying the causes of iterations of ECO which subsequently can provide a framework for companies to reduce these iterations. In addition, the case represents an example of benefits that can be achieved with the application of KDD in engineering change management.

An Information-Theoretic Approach to Determine Important Attributes for Engineering Change Evaluation

2008 ◽  
Author(s):  
Chandresh Mehta ◽  
Lalit Patil
Keyword(s):  
Change Management ◽  
Combinatorial Problem ◽  
Theoretic Approach ◽  
Engineering Change ◽  
Information Theoretic ◽  
Engineering Change Management ◽  
Detailed Evaluation ◽  
Single Attribute ◽  
Engineering Changes ◽  
Information Theoretic Approach

A proposed Engineering Change (EC) can affect several lifecycle-wide components. Enterprises plan detailed evaluation of only those changes or effects that may have a significant impact. Using past knowledge of engineering changes can prove effective in determining whether an effect is significant. However, comparing ECs for every single attribute is a combinatorial problem, because an EC is composed of a large number of disparate and interdependent attributes. In this paper, we propose an information-theoretic approach to determine important attributes that should be compared to retrieve past ECs similar to the proposed change. Our approach accounts for unknown interdependencies between attributes of disparate datatypes. We believe that the method discussed in this paper will improve overall efficacy of the Engineering Change Management (ECM) process by facilitating fast and reliable evaluation of a proposed EC.

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.

Sign in / Sign up

Export Citation Format

Share Document