Proposing a holistic framework for the assessment and management of manufacturing complexity through data-centric and human-centric approaches

Item Type Conference or Workshop Item (Speech)
Abstract A multiplicity of factors including technological innovations, dynamic operating environments, and globalisation are all believed to contribute towards the ever-increasing complexity of manufacturing systems. Although complexity is necessary to meet functional needs, it is important to assess and monitor it to reduce life-cycle costs by simplifying designs and minimising failure modes. This research paper identifies and describes two key industrially relevant methods for assessing complexity, namely a data-centric approach using the information theoretic method and a human-centric approach based on surveys and questionnaires. The paper goes on to describe the benefits and shortcomings of each and contributes to the body of knowledge by proposing a holistic framework that combines both assessment methods.
Authors Kohr, Dominik; Ahmad, Mussawar; Alkan, Bugra; Chinnathai, Malarvizhi Kaniappan; Budde, Lukas; Vera, Daniel; Friedli, Thomas & Harrison, Robert
Language English
Subjects business studies
economics
other research area
HSG Profile Area SoM - Business Innovation
Date March 2018
Page Range 86-93
Title of Book Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk
Event Title 3rd International Conference on Complexity, Future Information Systems and Risk
Event Location Funchal, Madeira, Portugal
Event Dates 20.03.2018 - 21.03.2018
ISBN 978-989-758-297-4
Official URL http://www.complexis.org/
Depositing User Dominik Kohr
Date Deposited 30 Apr 2018 13:49
Last Modified 20 Jul 2022 17:35
URI: https://www.alexandria.unisg.ch/publications/254116

Download

[img] Image (Book Cover Image)
med_img.jpg - Cover Image

Download (5kB)

Citation

Kohr, Dominik; Ahmad, Mussawar; Alkan, Bugra; Chinnathai, Malarvizhi Kaniappan; Budde, Lukas; Vera, Daniel; Friedli, Thomas & Harrison, Robert: Proposing a holistic framework for the assessment and management of manufacturing complexity through data-centric and human-centric approaches. [Conference or Workshop Item]

Statistics

https://www.alexandria.unisg.ch/id/eprint/254116
Edit item Edit item
Feedback?