Discovering Hidden Tasks and Process Structure through Email Logs for DSM

Authors

  • Lijun Lan Department of Mechanical Engineering, National University of Singapore Singapore
  • Ying Liu School of Engineering, Cardiff University, UK United Kingdom
  • Wen Feng Lu Department of Mechanical Engineering, National University of Singapore Singapore

Keywords:

DSM, process structure, interaction strength, email log, text mining, clustering

Abstract

The design structure matrix (DSM) method is a powerful network modelling tool to highlight the system architecture via presenting the interactions between the elements comprising a system. In DSM, measuring the interaction strength between elements is the first and crucial step. However, since the system elements are generally pre-identified by experts, their interaction relationships are often obtained from experts’ evaluation, which is time consuming and error-prone. To address this critical issue, in this paper, we aim to discover the hidden tasks of a process and their interactions from email logs with domain-specific contents. To this purpose, we have proposed a three-stage numerical DSM modeling approach, where text mining and clustering techniques are studied to discover hidden tasks. Furthermore, a metric concerning the measurement of interaction strength based on the overlapping time and the volume of exchanged information is presented. A case study is provided based on the emails collected from a design project.

Author Biographies

  • Lijun Lan, Department of Mechanical Engineering, National University of Singapore Singapore

    Lijun Lan is currently a PhD student in the Department of Mechanical Engineering at the National University of Singapore (NUS). She received his bachelor and master both in Computer Science from Chongqing University, China in 2009 and 2012, respectively. Her research interests include data mining, text mining, design informatics, and knowledge discovery and reuse in design and manufacturing.

  • Ying Liu, School of Engineering, Cardiff University, UK United Kingdom

    Ying Liu is currently a Senior Lecturer inthe Institute of Mechanical and Manufacturing Engineering at the School of Engineering in Cardiff University. He obtained his bachelor and master both in Mechanical Engineering from Chongqing University, China in 1998 and 2001, and then MSc and PhD from the Innovation in Manufacturing Systems and Technology (IMST) program under the Singapore MIT Alliance(SMA) at Nanyang Technological University and National Universityof Singapore in 2002 and 2006, respectively. His research interests focus primarily on design informatics, manufacturing informatics, intelligent manufacturing, design methodology and process, product design, data mining and machine learning, and ICT in design and manufacturing.

  • Wen Feng Lu, Department of Mechanical Engineering, National University of Singapore Singapore

    Wen Feng Lu is currently the Associate Professor of Mechanical Engineering at the National University of Singapore (NUS). He received his PhD in Mechanical Engineering from the University of Minnesota, USA and had been a faculty at the University of Missouri, USA for ten years after receiving his PhD degree. He later worked as the group manager and senior scientist in Singapore Institute of Manufacturing Technology for six years before joining NUS in 2005. His research interests include IT in Product Design, Sustainable Design and Manufacturing, 3D printing, and Intelligent Manufacturing.He is the recipient of 1997 Ralph R. Teetor Educational Award from Society of Automotive Engineers of USA and 2011 ASME Virtual Environments and Systems Technical Committee Best Paper Award.

References

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Published

2022-05-20

Issue

Vol. 3 No. 2 (2015): The Journal of Modern Project Management

Section

Articles-JMPM

License

Copyright (c) 2022 Lijun Lan, Ying Liu, Wen Feng Lu

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Discovering Hidden Tasks and Process Structure through Email Logs for DSM. (2022). The Journal of Modern Project Management, 3(2), 135. https://journalmodernpm.com/manuscript/index.php/jmpm/article/view/203

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