State space modeling of dimensional variation propagation in multistage machining process using differential motion vectors

2003 ◽  
Vol 19 (2) ◽  
pp. 296-309 ◽  
Author(s):  
Shiyu Zhou ◽  
Qiang Huang ◽  
Jianjun Shi
Keyword(s):  
State Space ◽  
Machining Process ◽  
Motion Vectors ◽  
Differential Motion ◽  
Variation Propagation ◽  
Space Modeling ◽  
State Space Modeling ◽  
Dimensional Variation ◽  
Differential Motion Vectors

State Space Modeling of Sheet Metal Assembly for Dimensional Control

1999 ◽  
Vol 121 (4) ◽  
pp. 756-762 ◽  
Author(s):  
Jionghua Jin ◽  
Jianjun Shi
Keyword(s):  
State Space ◽  
Sheet Metal ◽  
State Space Model ◽  
Measurement Information ◽  
Dimensional Control ◽  
Locating Error ◽  
Variation Propagation ◽  
Space Modeling ◽  
State Space Modeling ◽  
Sheet Metal Assembly

In this paper, a state space modeling approach is developed for the dimensional control of sheet metal assembly processes. In this study, a 3-2-1 scheme is assumed for the sheet metal assembly. Several key concepts, such as tooling locating error, part accumulative error, and re-orientation error, are defined. The inherent relationships among these error components are developed. Those relationships finally lead to a state space model which describes the variation propagation throughout the assembly process. An observation equation is also developed to represent the relationship between the observation vector (the in-line OCMM measurement information) and the state vector (the part accumulative error). Potential usage of the developed model is discussed in the paper.

A modification of DMVs based state space model of variation propagation for multistage machining processes

2017 ◽  
Vol 37 (4) ◽  
pp. 381-390 ◽  
Author(s):  
Fuyong Yang ◽  
Sun Jin ◽  
Zhimin Li
Keyword(s):  
Current Model ◽  
Propagation Model ◽  
Machining Processes ◽  
Motion Vectors ◽  
Content Type ◽  
Model Based ◽  
Differential Motion ◽  
Variation Propagation ◽  
Current Variation ◽  
Differential Motion Vectors

Purpose Complicated workpiece, such as an engine block, has special rough locating datum features (i.e. six independent datum features) due to its complex structure. This locating datum error cannot be handled by current variation propagation model based on differential motion vectors. To extend variation prediction fields, this paper aims to solve the unaddressed variation sources to modify current model for multistage machining processes. Design/methodology/approach To overcome the limitation of current variation propagation model based on differential motion vectors caused by the unaddressed variation sources, this paper will extend the current model by handling the unaddressed datum-induced variation and its corresponding fixture variation. Findings The measurement results of the rear face with respect to the rough datum W and the pan face with respect to the hole Q by coordinate measuring machine (CMM) are −0.006 mm and 0.031 mm. The variation results for rear face and pan face predicted by the modified model are −0.009 mm and 0.025 mm, respectively. The discrepancy of model prediction and measurement is very small. Originality/value This paper modifies the variation propagation model based on differential motion vectors by solving the unaddressed variation sources, which can extend the variation prediction fields for some complicated workpiece and is useful in the future work for many fields, such as process monitoring, fault diagnosis, quality-assured setup planning and process-oriented tolerancing.

Modelling of Variation Propagation for Multi-Operational Machining Processes Based on Perturbation Vectors

2010 ◽  
Vol 36 ◽  
pp. 120-128 ◽  
Author(s):  
Z.J. Wen ◽  
Ping Yu Zhu ◽  
X.P. Zhang ◽  
H.C. Liu
Keyword(s):  
State Space ◽  
State Space Model ◽  
Machining Process ◽  
Machining Processes ◽  
Machining Error ◽  
Space Model ◽  
Proposed Model ◽  
Variation Propagation ◽  
Dimensional Variation

A new state space model of multi-operational machining processes is presented for dimensional variation propagation, transformation and accumulation based on perturbation vectors (PV). Taking perturbation vectors (PV) for state vectors of part geometric variaton and the fixture variations for input vectors, the perturbation homogeneous transformation (PHT) is applied to analyze and derivate datum-induced deviation, re-location deviation, fixture error and machining error, and a state space model of variation propagation in multi-operational complicated machining processes is developed. Furthermore, a three-operation machining process of cylinder is given to illustrate the method presented. With the results of calculation and simulation, it is verified that the proposed model is effective and useful.

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