Towards Intelligent Self-Reconfiguration of Manufacturing Systems
Date
2024
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Cranfield University
Abstract
Global market demand is undergoing significant and rapid changes, creating an
unprecedented challenge for conventional manufacturing systems such as mass
production. As the demand for highly customized products surges, these
traditional methods struggle to handle the dynamic market demands. However, a
promising solution may lie in Reconfigurable Manufacturing Systems (RMS),
developed in the late 1990s. RMS have the potential to address the current
demand fluctuations effectively. Despite their promise, many manufacturers
worldwide encountered challenges when attempting to adopt the concept of
Reconfigurable Manufacturing Systems, particularly concerning the integration
and modularity aspects. This research’s goal is to close this gap by providing a
comprehensive framework that addresses these challenges and elevates the
effectiveness of RMS to new heights. Extensive data were collected from relevant
literature and expert interviews to develop the framework. Utilizing the collected
data, a conceptual framework was formulated, serving as a blueprint to overcome
the identified issues and enhance the performance of RMS. To ensure the validity
and practicality of the proposed framework, a second round of interviews was
conducted, seeking validation from industry experts. By offering a robust and
validated framework, this research seeks to contribute to the manufacturing
landscape by empowering industries to embrace Reconfigurable Manufacturing
Systems confidently. This transformation has the potential to unlock unparalleled
flexibility and responsiveness, enabling manufacturers to meet the ever-changing
demands of the global market efficiently. As a result, this paper lays the
foundation for a more adaptive and competitive manufacturing ecosystem for the
future.
Description
Keywords
Framework, Experts’ Interviews, Semi-structured Interviews, Manufacturing Systems, Artificial Intelligence, Industry 4.0.