scholarly journals Variation propagation modelling for multi-station machining processes with fixtures based on locating surfaces

2013 ◽  
Vol 51 (15) ◽  
pp. 4667-4681 ◽  
Author(s):  
José V. Abellán ◽  
J. Liu
Keyword(s):  
Machining Processes ◽  
Variation Propagation ◽  
Propagation Modelling

scholarly journals Variation propagation modelling in multistage machining processes using dual quaternions

2020 ◽  
Vol 111 (9-10) ◽  
pp. 2987-2998
Author(s):  
Filmon Yacob ◽  
Daniel Semere
Keyword(s):  
Motion Vector ◽  
Manufacturing Processes ◽  
Machining Processes ◽  
Dual Quaternions ◽  
Multistage Manufacturing ◽  
Differential Motion ◽  
Variation Propagation ◽  
Stream Of Variation ◽  
Matrix Differential ◽  
Propagation Modelling

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.

Multi-Operational Machining Processes Modeling for Sequential Root Cause Identification and Measurement Reduction

2004 ◽  
Author(s):  
Hui Wang ◽  
Qiang Huang ◽  
Reuven Katz
Keyword(s):  
Machine Tool ◽  
Propagation Model ◽  
Machining Processes ◽  
Error Sources ◽  
Variation Reduction ◽  
Measurement Reduction ◽  
Propagation Modeling ◽  
Root Cause ◽  
Variation Propagation ◽  
Root Cause Identification

Variation propagation modeling has been proved to be an effective way for variation reduction and design synthesis in multi-operational manufacturing processes (MMP). However, previously developed approaches for machining processes did not directly model the process physics regarding how fixture, and datum, and machine tool errors generate the same pattern on part features. Consequently, it is difficult to distinguish error sources at each operation. This paper formulates the variation propagation model using the proposed equivalent fixture error (EFE) concept. With this concept, datum error and machine tool error are transformed to equivalent fixture locator errors at each operation. As a result, error sources can be grouped and root cause identification can be conducted in a sequential manner. The case studies demonstrate the model validity through a real cutting experiment and model advantage in measurement reduction for root cause identification.

Research on Quality Control Architecture for Multistage Machining Processes in Small Batch Mode

2011 ◽  
Vol 130-134 ◽  
pp. 2573-2576
Author(s):  
Yan Wang ◽  
Ping Yu Jiang
Keyword(s):  
Quality Control ◽  
Process Quality ◽  
Propagation Model ◽  
Quality Data ◽  
Quality Prediction ◽  
Machining Processes ◽  
Batch Mode ◽  
Online Quality Control ◽  
Variation Propagation ◽  
Key Enabling Technologies

This paper presents a type of architecture of multistage machining processes in small batch mode, named Small-batch Quality Control System (SQCS), through analyzing various process quality control methods. The SQCS integrates complex network, workpiece variation propagation model and process quality prediction. And then, the three key enabling technologies are discussed in detail. Sensor network could be used to acquire real-time quality data, which include workpieces’ physical and dimensional information. Based on the above mentioned ideas, a general model of stage flow in small batch mode is constructed in order to realize process-driven online quality control and improve product machining quality.

A Quality Prediction Framework for Multistage Machining Processes Driven by an Engineering Model and Variation Propagation Model

2007 ◽  
Vol 129 (6) ◽  
pp. 1088-1100 ◽  
Author(s):  
Jianming Li ◽  
Theodor Freiheit ◽  
S. Jack Hu ◽  
Yoram Koren
Keyword(s):  
Dimensional Accuracy ◽  
Software Tool ◽  
Propagation Model ◽  
System Level ◽  
Quality Prediction ◽  
Machining Processes ◽  
Propagation Modeling ◽  
Variation Propagation ◽  
Quality Modeling ◽  
Dimensional Variation

This paper proposes a comprehensive quality prediction framework for multistage machining processes, connecting engineering design with the activities of quality modeling, variation propagation modeling and calculation, dimensional variation evaluation, dimensional variation analysis, and quality feedback. Presented is an integrated information model utilizing a hybrid (feature/point-based) dimensional accuracy and variation quality modeling approach that incorporates Monte Carlo simulation, variation propagation, and regression modeling algorithms. Two important variations (kinematic and static) for the workpiece, machine tool, fixture, and machining processes are considered. The objective of the framework is to support the development of a quality prediction and analysis software tool that is efficient in predicting part dimensional quality in a multistage machining system (serial, parallel, or hybrid) from station level to system level.

scholarly journals Variation propagation modeling in multistage machining processes considering form errors and N-2-1 fixture layouts

2021 ◽  
Author(s):  
Filmon Yacob ◽  
Daniel Semere ◽  
Nabil Anwer
Keyword(s):  
Machining Process ◽  
Quality Prediction ◽  
Machining Processes ◽  
Variation Reduction ◽  
Propagation Modeling ◽  
Form Errors ◽  
Part Quality ◽  
Fixture Layout ◽  
Variation Propagation ◽  
Cad Cam

AbstractVariation propagation modeling of multistage machining processes enables variation reduction by making an accurate prediction on the quality of a part. Part quality prediction through variation propagation models, such as stream of variation and Jacobian-Torsor models, often focus on a 3-2-1 fixture layout and do not consider form errors. This paper derives a mathematical model based on dual quaternion for part quality prediction given parts with form errors and fixtures with N-2-1 (N>3) layout. The method uses techniques of Skin Model Shapes and dual quaternions for a virtual assembling of a part on a fixture, as well as conducting machining and measurement. To validate the method, a part with form errors produced in a two-stationed machining process with a 12-2-1 fixture layout was considered. The prediction made following the proposed method was within 0.4% of the prediction made using a CAD/CAM simulation when form errors were not considered. These results validate the method when form errors are neglected and partially validated when considered.

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