Real-time detection of grip length during fastening of bolted joints: A Mahalanobis-Taguchi system (MTS) based approach

Citation data:

Journal of Intelligent Manufacturing, ISSN: 0956-5515, Vol: 21, Issue: 4, Page: 377-392

Publication Year:
Usage 70
Abstract Views 61
Full Text Views 5
Link-outs 4
Captures 15
Readers 15
Citations 10
Citation Indexes 10
Repository URL:
Saygin, Can; Mohan, Deepak; Sarangapani, Jagannathan
Springer Nature; Springer-Verlag
Computer Science; Engineering; Mahalanobis-Taguchi System; Automation; Automation Inspection; In-Process Quality Control; Mahalanobis-Taguchi System; Automation; Automation Inspection; In-Process Quality Control; Electrical and Computer Engineering
article description
This paper presents a Mahalanobis-Taguchi System (MTS) based methodology that detects grip length of bolted joints in real-time during fastening. Grip length is the length of the unthreaded portion of a bolt shaft. When the total thickness of joining members is greater than the grip length of the bolt, it is called under-grip, which compromises the structural integrity of a joint. In this study, a pneumatic, hand-held, rotary-type tool for bolted joints is integrated with a torque sensor and an optical encoder in order to obtain torque-angle signatures. Then, the signature is processed in real-time using the MTS-based approach in order to detect the grip-length, all of which occurs in real-time as the fastening process is completed. The proposed approach is also applied to detect the presence of re-used fasteners, which is another quality concern since some material properties and physical conditions of bolts and nuts can change if they are reused several times. The proposed approach reads in various characteristics from the torque-angle process signature, including mean and standard deviation of the torque-over-angle and angle-over-torque ratios, total angle turned, and work done during the different stages of the fastening process in order to infer about the quality of the bolted joint. The experimental results show that the proposed approach is successful with an accuracy of over 95% in detecting various grip lengths and presence of re-used fasteners. © 2008 Springer Science+Business Media, LLC.