JOINING SEQUENCE ANALYSIS AND OPTIMIZATION FOR IMPROVED GEOMETRICAL QUALITY

Disturbances in the manufacturing and assembly processes cause geometrical variation from the ideal geometry. This variation eventually results in functional and aesthetic problems in the final product. Being able to control the disturbances is the desire of the manufacturing industry. \ua0 Joining sequences impact the final geometrical outcome in an assembly considerably. To optimize the sequence for improved geometrical outcome is both experimentally and computationally expensive. In the simulation-based approaches, based on the finite element method, a large number of sequences need to be evaluated.\ua0 In this thesis, the simulation-based joining sequence optimization using non-rigid variation simulation is studied. Initially, the limitation of the applied algorithms in the literature has been addressed. A rule-based optimization approach based on meta-heuristic algorithms and heuristic search methods is introduced to increase the previously applied algorithms\u27 time-efficiency and accuracy. Based on the identified rules and heuristics, a reduced formulation of the sequence optimization is introduced by identifying the critical points for geometrical quality. A subset of the sequence problem is identified and solved in this formulation.\ua0 For real-time optimization of the joining sequence problem, time-efficiency needs to be further enhanced by parallel computations. By identifying the sequence-deformation behavior in the assemblies, black-box surrogate models are introduced, enabling parallel evaluations and accurate approximation of the geometrical quality. Based on this finding, a deterministic stepwise search algorithm for rapid identification of the optimal sequence is introduced.\ua0 Furthermore, a numerical approach to identify the number, location from a set of alternatives, and sequence of the critical joining points for geometrical quality is introduced. Finally, the cause of the various deformations achieved by joining sequences is identified. A time-efficient non-rigid variation simulation approach for evaluating the geometrical quality with respect to the sequences is proposed. \ua0 The results achieved from the studies presented indicate that the simulation-based real-time optimization of the joining sequences is achievable through a parallelized search algorithm and a rapid evaluation of the sequences. The critical joining points for geometrical quality are identified while the sequence is optimized. The results help control the assembly process with respect to the joining operation, improve the geometrical quality, and save significant computational time

JOINING SEQUENCE OPTIMIZATION IN COMPLIANT VARIATION SIMULATION

Disturbances in the manufacturing and assembly processes cause deviation and geometrical variation from the ideal geometry. This variation eventually results in functional and aesthetic problems in the final product. Being able to control the disturbances is the desire of the manufacturing industry. This, in other words, means turning the noise factors to control factors, in a robust design perspective.With the recent breakthroughs in the technology, the new digitalization reform, and availability of big data from the manufacturing processes, the concepts of digital twins have grasped the attention of the researchers and the practitioners.In line with this trend, S\uf6derberg et al. have introduced the geometry assurance digital twin and the concept of the self-compensating individualized assembly line. Steering the assembly process with online real-time optimization, through the digital twin medium is the vision of such a concept.Joining sequences impact the final geometrical outcome in an assembly considerably. To optimize the sequence for the optimal geometrical outcome is both experimentally and computationally expensive. In the simulation-based approaches, several sequences need to be evaluated together with the finite element method and Monte Carlo simulations.In this thesis, the simulation-based joining sequence optimization, using compliant variation simulation is studied. Initially, the limitations of the formulations and the applied algorithms in the literature have been addressed. Two evolutionary algorithms have been introduced to compare the computational performances to the genetic algorithm. Secondly, a reduced formulation of the sequence optimization is introduced through the identification of the critical points to lock the geometry, geometry joints. A rule-based method has been proposed to initiate the evolutionary algorithm and thereby to increase the algorithm’s computational efficiency. This approach has been further improved by a contact displacement minimization approach to generate model-dependent rules. Finally, a surrogate-assisted approach has been introduced to parallelize the computation process, saving computation time drastically. The approach also unveiled the potential of the simulation-based geometry joint identification, simultaneous to complete sequence determination.The results achieved from the presented studies indicate that the simulation-based real-time optimization of the joining sequences is achievable through a parallelized search algorithm, to be implemented in the geometry assurance digital twin concept. The results can help to control the joining sequence in the assembly process, improving the geometrical quality in a cost-effective manner, and saving significant computational time

Standardizing 1RU Chassis to PCBA Interfaces

Cisco currently designs a variety of custom chassis for different types of servers, routers, and switches. Our senior design project aims to reduce the number of custom chassis Cisco develops by standardizing the perimeter mounting locations for the printed circuit board assembly on the chassis. The purpose of this report is to document our selected project direction and support the decisions with appropriate evidence. In addition to research on the customer’s needs, the product, and the technical background used to understand the project scope, our group has come up with a way to analyze and compare mounting locations for various designs. Our team focused on the Quake chassis family to compare new designs with existing tooling and created a guideline for future standardization. We completed a MATLAB script that compares existing and future chassis hole locations to tooling locations in order to determine the best tooling set for a given chassis. We also made a document that analyzes hole locations based on the different depths of the Quake chassis families. We hope that our research and analysis will become a future guideline for designers to implement common features for PCBA mounting locations and chassis interfaces

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Adhesive joint geometry variation in non-rigid aircraft structures

Adhesive bonding is a proven alternative to mechanical fasteners for structural assembly, offering lighter and thus more fuel efficient aircraft and cost-effective manufacturing processes. The effective application of bonded structural assemblies is however limited by the tight fit-up requirement, which is with tolerance ranges of hundreds of microns; this can be a challenge for the industry to meet considering the variability of current part manufacturing methods and the conservative nature of the conventional tolerance stack-up analysis method. Such a (perceived) limitation can discourage effective exploitation of bonding technologies, or lead to development of overengineered solutions for assurance. This work addresses such challenge by presenting an enhanced bondline thickness variation analysis accounting for part deflection of a bonded skinstringer assembly representing a typical non-rigid airframe structure. A semianalytical model accounting for unilateral contact and simplified 1D adhesive flow has been developed to predict bondline thickness variation of the assembly given the adherends’ mechanical properties, adhesive rheological properties, and external assembly forces or boundary conditions. A spectral-analysis method for assembly force requirement estimation has also been tested. The bondline dimensions of several representative test articles have been interrogated, including a reconfigurable test assembly designed specifically to test the input conditions that affect bondline geometry variation. It has been demonstrated that the part deflections need to be accounted for regarding the fit-up requirement of bonded non-rigid structural assembly. The semi-analytical model has been found to more reliable and realistic prediction of bondline thickness when compared to a rigid tolerance stack-up. The analysis method presented can be a major technology enabler for faster, more economical development of the aircraft of the future, as well as of any analogue structures with high aspect ratios where weight savings and fatigue performance may be core objectives.Aerospac

Numerical modelling of additive manufacturing process for stainless steel tension testing samples

Nowadays additive manufacturing (AM) technologies including 3D printing grow rapidly and they are expected to replace conventional subtractive manufacturing technologies to some extents. During a selective laser melting (SLM) process as one of popular AM technologies for metals, large amount of heats is required to melt metal powders, and this leads to distortions and/or shrinkages of additively manufactured parts. It is useful to predict the 3D printed parts to control unwanted distortions and shrinkages before their 3D printing. This study develops a two-phase numerical modelling and simulation process of AM process for 17-4PH stainless steel and it considers the importance of post-processing and the need for calibration to achieve a high-quality printing at the end. By using this proposed AM modelling and simulation process, optimal process parameters, material properties, and topology can be obtained to ensure a part 3D printed successfully