scholarly journals Design Evaluation of Multi-station Assembly Processes by Using State Space Approach

2002 ◽  
Vol 124 (3) ◽  
pp. 408-418 ◽  
Author(s):  
Yu Ding ◽  
Dariusz Ceglarek ◽  
Jianjun Shi
Keyword(s):  
State Space ◽  
Process Design ◽  
State Space Model ◽  
System Level ◽  
Space Representation ◽  
System Response ◽  
Design Evaluation ◽  
Assembly Process ◽  
Sensitivity Indices ◽  
Variation Propagation

This paper considers the problem of evaluating and benchmarking process design configuration in a multi-station assembly process. We focus on the unique challenges brought by the multi-station system, namely, (1) a system level model to characterize the variation propagation in the entire process, and (2) the necessity to describe the system response to variation inputs at both global (system level) and local (station level and single fixture level) scales. State space representation is employed to recursively describe the propagation of variation in such a multi-station process, incorporating process design information such as fixture locating layout at individual stations and station-to-station locating layout change. Following the sensitivity analysis in control theory, a group of hierarchical sensitivity indices is defined and expressed in terms of the system matrices in the state space model, which are determined by the given process design configuration. Implication of these indices with respect to variation control is discussed and a three-step procedure of applying the sensitivity indices for selecting a better design and prioritizing the critical station/fixture is presented. We illustrate the proposed method using the group of sensitivity indices in design evaluation of the assembly process of an SUV (Sport Utility Vehicle) side panel.

scholarly journals Design Evaluation of Multi-Station Assembly Processes by Using State Space Approach

2002 ◽  
Author(s):  
Yu Ding ◽  
Dariusz Ceglarek ◽  
Jianjun Shi
Keyword(s):  
State Space ◽  
Process Design ◽  
State Space Model ◽  
System Level ◽  
Space Representation ◽  
System Response ◽  
Design Evaluation ◽  
Assembly Process ◽  
Sensitivity Indices ◽  
Variation Propagation

This paper considers a problem of evaluating and benchmarking process design configuration in a multi-station assembly process. We focus on the unique challenges brought by the multi-station system: (1) a system level model to characterize the variation propagation in the entire process, (2) the necessity to describe the system response to variation inputs at both global (system level) and local (station level and single fixture level) scales. State space representation is employed to recursively describe the propagation of variation in such a multi-station process, incorporating process design information such as fixture locating layout at individual stations and station-to-station locating layout change. Following the sensitivity analysis in control theory, a group of hierarchical sensitivity indices is defined and expressed in terms of the system matrices in the state space model, which are determined by the given process design configuration. Implication of these indices with respect to variation control is discussed and a three-step procedure of applying the sensitivity indices to selecting a better design and prioritizing the critical station/fixture is presented. We illustrate the proposed method using the group of sensitivity indices in design evaluation of the assembly process of a SUV (Sport Utility Vehicle) side panel.

An assembly sensitivity analysis method based on state space model

2017 ◽  
Vol 37 (2) ◽  
pp. 249-259 ◽  
Author(s):  
Xin Li ◽  
Jianzhong Shang ◽  
Hong Zhu
Keyword(s):  
Sensitivity Analysis ◽  
State Space ◽  
Process Parameters ◽  
State Space Model ◽  
System Level ◽  
System Response ◽  
Assembly Process ◽  
Content Type ◽  
Space Model ◽  
Variation Propagation

Purpose This paper aims to consider a problem of assembly sensitivity in a multi-station assembly process. The authors focus on the assembly process of aircrafts, which includes cabins and inertial navigation system (INSs), and establish the assembly process state space model for their assembly sensitivity research. Design/methodology/approach To date, the process-related errors that cause large variations in key product characteristics remains one of the most critical research topics in assembly sensitivity analysis. This paper focuses on the unique challenges brought about by the multi-station system: a system-level model for characterizing the variation propagation in the entire process, and the necessity of describing the system response to variation inputs at both station-level and single fixture-level scales. State space representation is used to describe the propagation of variation in such a multi-station process, incorporating assembly process parameters such as fixture-locating layout at individual stations and station-to-station locating layout change. Findings Following the sensitivity analysis in control theory, a group of hierarchical sensitivity indices is defined and expressed in terms of the system matrices in the state space model, which are determined by the given assembly process parameters. Originality/value A case study of assembly sensitivity for a multi-station assembly process illustrates and validates the proposed methodology.

The Modeling and Prediction of Gravity Deformation in Precision Machine Tool Assembly

2013 ◽  
Author(s):  
Junkang Guo ◽  
Jun Hong ◽  
Xiaopan Wu ◽  
Mengxi Wang ◽  
Yan Feng
Keyword(s):  
Machine Tool ◽  
State Space ◽  
State Space Model ◽  
Variation Theory ◽  
Assembly Process ◽  
Motion Error ◽  
Space Model ◽  
Precision Machine ◽  
Variation Propagation ◽  
Tool Assembly

The variation propagation in mechanical assembly is an important topic in several research fields, such as computer aided tolerancing (CAT) and product quality control. Mathematical models and analysis methods have been developed to solve this practical problem. Tolerance analysis which is based on the rigid hypothesis can be used to simulate the mass manufacturing and assembly. The state space model and stream of variation theory are mainly applied in flexible part assembly. However, in precision machine tool assembly, both tolerance design and process planning critically impact the accuracy performance, mainly because of the fact that the gravity deformation, including the part deformation and the variation in the joint of two connecting parts, cannot be ignored in variation propagation analysis. In this paper, based on the new generation GPS (Geometrical Product Specification and Verification) standards, the verification and modeling of key characteristics variation due to gravity deformation of single part and adjacent parts are discussed. The accurate evaluation of position and orientation variation taking into account form errors and gravity deformation can be solved from this model by FEM. A mathematical model considering rail error, stiffness of bearings is introduced to simulate the motion error in gravity effect. Based on this work to more accurately calculate the variation propagation considering gravity impact, a state space model describing the assembly process of machine tools is proposed. Then, in any assembly process, the final accuracy can be predicted to find out whether the accuracy is out of design requirement. The validity of this method is verified by a simulation of the assembly of a precision horizontal machining center.

Dynamic prediction and compensation of aerocraft assembly variation based on state space model

2015 ◽  
Vol 35 (2) ◽  
pp. 183-189 ◽  
Author(s):  
Yujun Cao ◽  
Xin Li ◽  
Zhixiong Zhang ◽  
Jianzhong Shang
Keyword(s):  
State Space ◽  
State Space Model ◽  
Propagation Model ◽  
Small Displacement ◽  
Assembly Process ◽  
Dynamic Prediction ◽  
Content Type ◽  
Assembly Accuracy ◽  
Variation Propagation ◽  
State Space Theory

Purpose – This paper aims to clarify the predicting and compensating method of aeroplane assembly. It proposes modeling the process of assembly. The paper aims to solve the precision assembly of aeroplane, which includes predicting the assembly variation and compensating the assembly errors. Design/methodology/approach – The paper opted for an exploratory study using the state space theory and small displacement torsor theory. The assembly variation propagation model is established. The experiment data are obtained by a real small aeroplane assembly process. Findings – The paper provides the predicting and compensating method for aeroplane assembly accuracy. Originality/value – This paper fulfils an identified need to study how the assembly variation propagates in the assembly process.

System of System Based Sociotechnical Complexity Challenges in Product and Process Design

2011 ◽  
Author(s):  
Zulfiqar Ali-Qureshi
Keyword(s):  
Product Design ◽  
Process Design ◽  
Product Life Cycle ◽  
Process Development ◽  
Physical Structure ◽  
System Level ◽  
Design System ◽  
Assembly Process ◽  
Product And Process ◽  
Physical Elements

Unique characteristic of system of system based product life cycle challenges evolves different level of systems. This means the product design system and process level system consideration are very important besides the system level issues for product and process development which are part of systems of system. These core issues include the physical elements, assembly process and its related cognitive elements of component to that particular assembly and its process at Sub system level which are fundamental of System of system in holistic perspective of new product and process design. Any system level change or variety affects the next adjacent system in the same product as a member of same family of a system of system. In this paper the aspect of Hybrid electric car battery has been explored to reduce the system of system level sociotecnical complexity in product design. In this context, the affect of changeability in the assembly system level has been explored and DFA analysis and the complexity Index of the product at physical structure, assembly process and cognitive system level been discussed to draw analogy for making an understanding of similar nature of the system in platform based product and process family development.

Time-Domain Hydroelastic Analysis of a Flexible Marine Structure Using State-Space Models

2008 ◽  
Vol 131 (1) ◽  
Author(s):  
Reza Taghipour ◽  
Tristan Perez ◽  
Torgeir Moan
Keyword(s):  
State Space ◽  
Time Domain ◽  
State Space Model ◽  
Space Representation ◽  
Regular Waves ◽  
State Space Representation ◽  
Alternative State ◽  
Marine Structure ◽  
Hydroelastic Analysis ◽  
The Mathematical Model

This article deals with time-domain hydroelastic analysis of a marine structure. The convolution terms associated with fluid memory effects are replaced by an alternative state-space representation, the parameters of which are obtained by using realization theory. The mathematical model established is validated by comparison to experimental results of a very flexible barge. Two types of time-domain simulations are performed: dynamic response of the initially inert structure to incident regular waves and transient response of the structure after it is released from a displaced condition in still water. The accuracy and the efficiency of the simulations based on the state-space model representations are compared to those that integrate the convolutions.

Diagnosability Analysis of Multi-Station Manufacturing Processes

2001 ◽  
Vol 124 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Yu Ding ◽  
Jianjun Shi ◽  
Dariusz Ceglarek
Keyword(s):  
Manufacturing Process ◽  
State Space Model ◽  
Manufacturing Processes ◽  
Assembly Process ◽  
Space Model ◽  
Distribution Strategy ◽  
Variation Propagation ◽  
Distribution Scheme ◽  
Stream Of Variation ◽  
Comprehensive Study

Variation propagation in a multi-station manufacturing process (MMP) is described by the theory of “Stream of Variation.” Given that the measurements are obtained via certain sensor distribution scheme, the problem of whether the stream of variation of an MMP is diagnosable is of great interest to both academia and industry. We present a comprehensive study of the diagnosability of MMPs in this paper. It is based on the state space model and is parallel to the concept of observability in control theory. Analogous to the observability matrix and index, the diagnosability matrix and index are first defined and then derived for MMP systems. The result of diagnosability study is applied to the evaluation of sensor distribution strategy. It can also be used as the basis to develop an optimal sensor distribution algorithm. An example of a three-station assembly process with multi-fixture layouts is presented to illustrate the methodology.

Identification of Stochastic System and Controller via Projection Filters

1996 ◽  
Vol 118 (2) ◽  
pp. 169-176 ◽  
Author(s):  
Hyun Chang Lee ◽  
Min-Hung Hsiao ◽  
Jen-Kuang Huang ◽  
Chung-Wen Chen
Keyword(s):  
Kalman Filter ◽  
State Space ◽  
Stochastic System ◽  
State Space Model ◽  
Open Loop ◽  
The State ◽  
Loop System ◽  
Test Facility ◽  
System Response ◽  
Space Model

A method based on projection filters is presented for identifying an open-loop stochastic system with an existing feedback controller. The projection filters are derived from the relationship between the state-space model and the AutoRegressive with eXogeneous input (ARX) model including the system, Kalman filter and controller. Two ARX models are identified from the control input, closed-loop system response and feedback signal using least-squares method. Markov parameters of the open-loop system, Kalman filter and controller are then calculated from the coefficients of the identified ARX models. Finally, the state-space model of the open-loop stochastic system and the gain matrices for the Kalman filter and controller are realized. The method is validated by simulations and test data from an unstable large-angle magnetic suspension test facility.

Diagnosability Analysis of Multi-Station Manufacturing Processes

Manufacturing ◽  
2002 ◽  
Author(s):  
Yu Ding ◽  
Jianjun Shi ◽  
Dariusz Ceglarek
Keyword(s):  
Manufacturing Process ◽  
State Space Model ◽  
Manufacturing Processes ◽  
Assembly Process ◽  
Space Model ◽  
Distribution Strategy ◽  
Variation Propagation ◽  
Distribution Scheme ◽  
Stream Of Variation ◽  
Comprehensive Study

Variation propagation in a multi-station manufacturing process (MMP) is described by the theory of “Stream of Variation.” Given that the measurements are obtained via certain sensor distribution scheme, the problem of whether the stream of variation of an MMP is diagnosable is of great interest to both academia and industry. We present a comprehensive study of the diagnosability of MMPs in this paper. It is based on the state space model and is parallel to the concept of observability in control theory. Analogous to the observability matrix and index, the diagnosability matrix and index are first defined and then derived for MMP systems. The result of diagnosability study is applied to the evaluation of sensor distribution strategy. It can also be used as the basis to develop an optimal sensor distribution algorithm. An example of a three-station assembly process with multi-fixture layouts is presented to illustrate the methodology.

Generic Modeling and Control of an Open-Circuit Piston Pump—Part II: Control Strategies and Designs

2016 ◽  
Vol 138 (4) ◽  
Author(s):  
Shu Wang
Keyword(s):  
State Space ◽  
Control Strategies ◽  
State Space Model ◽  
Control Valve ◽  
Open Circuit ◽  
The State ◽  
Operating Conditions ◽  
Torque Control ◽  
Space Representation ◽  
Load Pressure

Hydromechanical compensators are often integrated with piston-type pumps to produce various control behavior, for example, pressure, load-sensing, power, or torque control. Various hydromechanical mechanisms (e.g., spring forces and load pressure) are found in the industry to ensure the desired effect of the system outputs: swash angle, discharge pressure, and input torque following the reference inputs. In a companion paper (Part I of this paper), a generic linearized state-space model is derived to investigate the pump dynamics and determine the design criteria and parameters. In the study, the state-space equations are used to propose and define the generic compensating control pump to conduct the similar strategies as hydromechanical pumps do. The different control purposes (pressure/flow/power compensating) are accomplished by only manipulating the generic regulate inputs given by an electrical proportional control valve. In the open-circuit pump, the generic controllers are proposed to generate these inputs by using one unique mechanical and electronic architecture to establish various purposes of flow, pressure, torque desired control, and even more control objectives. The controller is developed in accordance with the state-space representation and by following the models of the hydromechanical compensators that can facilitate the correlation verification. The proposed controllers are able to offer more intelligent and cost-saving control strategies for open-circuit piston pumps. To achieve the similar performance as hydromechanical compensators do and implement the comparative study, control gains and settings in the controller can be determined from ones that hydromechanical compensators have. The difference is that electronic signals (swash plate position, pressure, etc.) work as feedbacks together with other control gains to regulate the input signals. For the different control purposes, control gains are able to be set conveniently for the various control operating conditions with combining the certain feedbacks on the same hardware platform that will be value efficient and capable of control intelligence. In the paper, results of predictions made by the model are presented and compared with some experimental data of hydromechanical designs. Further work on the advanced model-based control and estimation is anticipated to be addressed.

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