Controlling Geometrical Variation Caused by Assembly Fixtures

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Kristina Wärmefjord ◽  
Johan S. Carlson ◽  
Rikard Söderberg
Keyword(s):  
Control Chart ◽  
Manufacturing Processes ◽  
Assembly Process ◽  
Final Assembly ◽  
Sources Of Variation ◽  
Geometrical Variation ◽  
Auto Body

In the auto body assembly process, fixtures position parts during assembly and inspection. Variation in the positioning process propagates to the final assembly. To control the assembly fixtures, repeatability studies are used. Those studies are, however, usually done with long intervals and the fixtures might be afflicted with variation between studies. There are also other sources of variation in the final assembly, such as variation in parts due to previous manufacturing steps. To separate variation caused by fixtures and the variation caused by previous manufacturing processes, a multivariate fixture failure subspace control chart is proposed.

A Fixture Failure Control Chart for Variation Caused by Assembly Fixtures

2012 ◽  
Author(s):  
Kristina Wärmefjord ◽  
Johan S. Carlson
Keyword(s):  
Fault Diagnosis ◽  
Case Studies ◽  
Control Chart ◽  
Assembly Process ◽  
Final Assembly ◽  
Sources Of Variation ◽  
Auto Body ◽  
Different Sources

In the auto body assembly process, fixtures are used to position parts during assembly and inspection. If there is variation in the positioning process, this will propagate to the final assembly. There are also other sources of variation in the final assembly, such as variation in parts due to previous manufacturing steps. To facilitate the separation of the different sources of variation, and thereby also improve fault diagnosis, a fixture failure subspace control chart is proposed. This control chart is based on a multivariate T2-chart, but only variations in the fixture failure subspace are considered. The method is applied to two industrial case studies with satisfying results.

Analysis of Nonlinear Variation Accumulation in Auto-Body Assembly Process

Manufacturing ◽  
2002 ◽  
Author(s):  
Jun Lian ◽  
Zhongqin Lin ◽  
Fusheng Yao ◽  
Xinmin Lai
Keyword(s):  
Sheet Metal ◽  
State Equation ◽  
Assembly Process ◽  
Transformation Mechanism ◽  
Metal Parts ◽  
Sheet Metal Parts ◽  
Accumulation Mechanism ◽  
Auto Body ◽  
Non Gaussian ◽  
Geometrical Dimensions

In the assembly process of auto-body, variations in the geometrical dimensions of sheet metal parts and fixtures are inevitable. These variations accumulate through the multi-station assembly process to form the dimensional variations of the final products. Compared with the assembly of rigid parts, the assembly process of the elastic parts is more complex because the variation accumulation patterns rely much on the variations of fixture, jointing methods and mechanical deformation. This paper aims at analyzing the variation transformation mechanism and accumulation characteristics for the assembly of sheet metal parts based on the analysis of dimensional coordination relations among parts and fixtures. Finite element method (FEM) and Monte-Carlo Simulation (MCS) were used to analyze the effect of jointing contact on variation transformation, while a state equation was developed to describe the variation accumulation mechanism. The result of the analysis indicates that the main characteristics of elastic assembly jointing are the overlap jointing methods and elastic contacts action. The fact that the variation transform coefficients (VTC) are variable makes the assembly variation distribution Non-Gaussian even if the dimension variation of parts is Gaussian distribution. The analysis conclusions have potential value for more reasonable tolerance synthesis of elastic parts assembly.

Optimization of the installation sequence for the temporary fasteners in the aircraft industry

2021 ◽  
pp. 1-25
Author(s):  
Tatiana Pogarskaia ◽  
Sergey Lupuleac ◽  
Julia Shinder ◽  
Philipp Westphal
Keyword(s):  
Combinatorial Problem ◽  
Hole Drilling ◽  
Assembly Process ◽  
Process Verification ◽  
Final Assembly ◽  
Uncertain Input ◽  
Uncertain Input Data ◽  
Aircraft Production

Abstract Riveting and bolting are common assembly methods in aircraft production. The fasteners are installed immediately after hole drilling and fix the relative tangential displacements of the parts, that took place. A proper fastener sequence installation is very important because a wrong one can lead to a “bubble-effect”, when gap between parts after fastening becomes larger in some areas rather than being reduced. This circumstance affects the quality of the final assembly. For that reason, the efficient methods for determination of fastening sequence taking into account the specifics of the assembly process are needed. The problem is complicated by several aspects. First of all, it is a combinatorial problem with uncertain input data. Secondly, the assembly quality evaluation demands the time-consuming computations of the stress-strain state of the fastened parts caused by sequential installation of fasteners. Most commonly used strategies (heuristic methods, approximation algorithms) require a large number of computational iterations what dramatically complicates the problem. The paper presents the efficient methods of fastener sequence optimization based on greedy strategy and the specifics of the assembly process. Verification of the results by comparison to commonly used installation strategies shows its quality excellence.

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.

Application of a Unified Jacobian—Torsor Model for Tolerance Analysis

2003 ◽  
Vol 3 (1) ◽  
pp. 2-14 ◽  
Author(s):  
Alain Desrochers ◽  
Walid Ghie ◽  
Luc Laperrie`re
Keyword(s):  
Three Dimensional ◽  
Tolerance Analysis ◽  
Small Displacement ◽  
Manufacturing Processes ◽  
Functional Requirements ◽  
Tolerance Zone ◽  
Kinematic Chains ◽  
Final Assembly ◽  
Novel Method ◽  
Assembly Constraints

Because of uncertainties in manufacturing processes, a mechanical part always shows variations in its geometrical characteristics (ex. form, dimension, orientation and position). Quality then often reflect how well tolerances and hence, functional requirements, are being achieved by the manufacturing processes in the final product. From a design perspective, efficient methods must be made available to compute, from the tolerances on individual parts, the value of the functional requirement on the final assembly. This is known as tolerance analysis. To that end, existing methods, often based on modeling of the open kinematic chains in robotics, are classified as deterministic or statistical. These methods suppose that the assembled parts are not perfect with regard to the nominal geometry and are rigid. The rigidity of the parts implies that the places of contacts are regarded as points. The validation or the determination of a tolerance zone is therefore accomplished by a series of simulation in specific points subjected to assembly constraints. To overcome the limitations and difficulties of point based approaches, the paper proposes the unification of two existing models: the Jacobian’s matrix model, based on the infinitesimal modeling of open kinematic chains in robotics, and the tolerance zone representation model, using small displacement screws and constraints to establish the extreme limits between which points and surfaces can vary. The approach also uses interval algebra as a novel method to take tolerance boundaries into account in tolerance analysis. The approach has been illustrated on a simple two parts assembly, nevertheless demonstrating the capability of the method to handle three-dimensional geometry. The results are then validated geometrically, showing the overall soundness of the approach.

scholarly journals Optimalisasi Proses Perakitan Pesawat Tanpa Awak dengan Metoda Critical Path Methods (CPM)

2016 ◽  
Vol 15 (1) ◽  
pp. 87
Author(s):  
Dendi Adi Saputra M ◽  
Eka Satria ◽  
Gusman Arif Pandy
Keyword(s):  
Critical Path ◽  
Optimal Time ◽  
Manufacturing Processes ◽  
Assembly Process ◽  
Work Breakdown Structure ◽  
Design Attributes ◽  
Structural Work ◽  
Work Distribution ◽  
Long Time ◽  
Optimal Assembly

The manufacturing of Unmanned Aerial Vehicles (UAV) requires a design process that involves the design of aircraft’s components such as fuselage, wing, horizontal stabilizer, vertical stabilizer, ailerons, elevators, tail, and wing. The process takes a long time. Therefore, the distribution of structural works based on their characteristics and classifications by considering their design attributes and manufacturing processes is required. This research aims to find the optimal time and critical path of the assembly process of an UAV based on product work breakdown structure (PWBS) and critical path method (CPM). The result reveals that the optimal assembly time is 139 minutes. Finally, the application of product-oriented structural work distribution and the optimization of the assembly activities involved in the critical path successfully minimize the duration of the assembly process. 

Using Yielded Cost As a Metric for Modeling Manufacturing Processes

2001 ◽  
Author(s):  
Daniel V. Becker ◽  
Peter Sandborn
Keyword(s):  
New Method ◽  
Manufacturing Processes ◽  
Assembly Process ◽  
Sequential Process ◽  
Process Step ◽  
New Approach ◽  
Complex Processes ◽  
Effective Cost ◽  
Step Step ◽  
Manufacturing Yield

Abstract Yielded cost is defined as cost divided by yield and can be used as a metric for representing an effective cost per good (non-defective) assembly for a manufacturing process. Although yielded cost is not a new concept, it has no consistent definition in engineering literature, and several different formulations and interpretations exist in the context of manufacturing and assembly. In manufacturing, yield is the probability that an assembly is non-defective. To find the effective cost per good assembly that is invested in the manufacturing or assembly process, cost is accumulated and divided by yield. This paper reviews and correlates existing yielded cost formulations and presents a new method that enables consistent measurement of sequential process flows. This new method views the yielded cost associated with an individual process step (step yielded cost) as the change in the process’s yielded cost when the step is removed from the process. This approach is preferred because it incorporates upstream and downstream information and because it provides a specific process step’s effective cost per good assembly that is independent of step order between steps that scrap defective product (i.e., test steps). Conventional wisdom dictates that the best way to improve a process is to increase the yield of the lowest yield step. The new approach developed in this paper produces an auxiliary cost that can be used to determine the best method of improving processes that, for complex processes, does not always correspond to improving the lowest yield step. Simple and complex assembly process examples are presented to demonstrate the interpretation of yielded cost. The new approach is applied to a microwave module (MWM) manufacturing and assembly process example.

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.

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