Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes

Author(s):  
Jianjun Shi
2020 ◽  
Vol 111 (9-10) ◽  
pp. 2987-2998
Author(s):  
Filmon Yacob ◽  
Daniel Semere

Abstract Variation propagation models play an important role in part quality prediction, variation source identification, and variation compensation in multistage manufacturing processes. These models often use homogenous transformation matrix, differential motion vector, and/or Jacobian matrix to represent and transform the part, tool and fixture coordinate systems and associated variations. However, the models end up with large matrices as the number features and functional element pairs increase. This work proposes a novel strategy for modelling of variation propagation in multistage machining processes using dual quaternions. The strategy includes representation of the fixture, part, and toolpath by dual quaternions, followed by projection locator points onto the features, which leads to a simplified model of a part-fixture assembly and machining. The proposed approach was validated against stream of variation models and experimental results reported in the literature. This paper aims to provide a new direction of research on variation propagation modelling of multistage manufacturing processes.


2004 ◽  
Vol 126 (3) ◽  
pp. 611-618 ◽  
Author(s):  
Qiang Huang ◽  
Jianjun Shi

In a Serial-Parallel Multistage Manufacturing System (SP-MMS), identical work-stations are utilized at each stage to meet the productivity and line balance requirements. In such a system, parts could go through different process routes and some routes may merge at certain stage(s). Due to the existence of multiple variation streams, it is challenging to model and analyze variation propagation in a system. This paper extends the state space modeling approach from single process route to the SP-MMS with multiple routes. Several model dimension reduction techniques are proposed to reduce model complexity. Properties of these techniques are studied from the perspectives of system representation and diagnosability. Furthermore, these techniques are applied to analyze system measurement strategies.


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