University of Cambridge
Designing Resilient Manufacturing Systems In the Presence of Change
Abstract
dc:description.abstractEconomic and technical changes force manufacturers to redesign and enhance their operational systems. The implications of such changes within a complex system such as manufacturing and the supply chain can be very challenging. In particular, where the number of system elements and their connections result in a high level of complexity, the potential effects of a change can be expensive concerning the delivery time and cost targets, as a change to one part or element of a design requires additional changes throughout the system. Companies need to understand the characteristics of their manufacturing systems that make them resilient to change. Considered from a system perspective, the structures of the system, and its elements and connections, contribute greatly to the characteristics and behaviour of the system and hence potential resilience. A change prediction method can help to analyse the change properties and improve complex systems by focusing on the underlying structural elements and dependencies. This thesis proposes a novel system change method that can enable the review of the current manufacturing system and understand how to design a more robust or adaptable system which addresses resilience. This method is a combination of matrix-based approaches and methods to assess the interaction between elements of the product and its manufacturing process in order to understand the risk of changes propagating through the system. Risk assessment across layers of a system can give valuable insight into how an element change interacts within the system. The goal of this thesis is to contribute to gaining fundamental understanding of manufacturing systems resilience by developing a method to evaluate capabilities of changes, performance robustness or adaptability and achieving high resilience.
Degree
thesis:*- Name dc:type.qualificationname
- Doctor of Philosophy (PhD)
- Level dc:type.qualificationlevel
- Doctoral
- Grantor dc:publisher.institution
- University of Cambridge
- Year dc:date.issued
- 2021
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Olmez, Hatice
- Advisor dc:contributor.advisor
-
- Clarkson, P John
Subjects
dc:subject × 2Rights
dc:rightsIdentifiers
dc:identifier.*- DOI dc:identifier.doi
- https://doi.org/10.17863/CAM.74334
- OAI identifier oai:identifier
- oai:www.repository.cam.ac.uk:1810/326885