Hybrid sensing-based approach for the monitoring and maintenance of shared manufacturing resources

With the rapid development of information technologies, shared manufacturing is proposed to meet the prevailing tendency of servitization and digitalisation in the industry. As the crucial section for performing shared manufacturing, resource monitoring and maintenance aim to detect production excep...

Full description

Saved in:
Bibliographic Details
Published in:International journal of production research 2023-06, Vol.61 (12), p.3849-3867
Main Authors: Zhang, Geng, Chen, Chun-Hsien, Liu, Bufan, Li, Xinyu, Wang, Zuoxu
Format: Article
Language:English
Subjects:
Customers
Data acquisition
Digitization
hybrid sensing
Internet of Things
Maintenance
Manufacturing
Monitoring
resource monitoring and maintenance
Shared manufacturing
smart manufacturing
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:With the rapid development of information technologies, shared manufacturing is proposed to meet the prevailing tendency of servitization and digitalisation in the industry. As the crucial section for performing shared manufacturing, resource monitoring and maintenance aim to detect production exceptions and ensure normal task execution. Existing research mainly uses a resource-centric strategy to acquire production-related data and make decisions for the management of shared resources. The experience data from the users/customers of the shared resources or its similar resources is rarely acquired actively in a cost-effective manner. However, the user/customer's experience data may contain essential knowledge that can be used for effective production performance identification and maintenance. To fill this gap, a hybrid sensing-based approach is proposed to perform the monitoring and maintenance of the shared manufacturing resources. It leverages both the sensor-sensed production data and user/customer-generated data for value creation in a cost-effective manner. Based on the acquired hybrid data, a service model is constructed to achieve the monitoring of the shared manufacturing resource, and a knowledge-based mechanism is designed to perform efficient maintenance. A case study is further presented to verify the effectiveness of the proposed approach.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2021.2013564