Panel Assembly Process Research Articles

Digital twin-driven assembly accuracy prediction method for high performance precision assembly of complex products

The high performance precision assembly (HPPA) of complex products such as aerospace, aircraft and high-end machine tool has demanding requirements for assembly accuracy. Achieving the accurate prediction of assembly accuracy for these complex products before assembling is the premise of improving the assembly quality and performance, and also has always been a challenge. Existing assembly accuracy prediction methods focus on acquiring the assembly deviation based on CAD model and manufacturing errors of parts, but rarely involve the multidimensional error coupling of parts and the influencing factors in the assembly process, which inevitably cause a certain gap between the prediction result and the actual condition, affecting the reliability of the prediction result. To address the above problems, this paper presents a digital twin (DT)-driven assembly accuracy prediction method for the HPPA of complex products. Firstly, this paper introduces the methodology overview and proposes an overall framework for DT-driven assembly accuracy prediction. Secondly, three key enabling technologies realizing the DT-driven assembly accuracy prediction, including the construction of part digital twin model, the generation of DT-based assembly process model, and assembly deviation propagation and accuracy analysis are introduced in detail. Finally, an application implementation of a prototype system and a case study involving a simplified satellite structure panel assembly process are used to verify the effectiveness and feasibility of the proposed method.

Capacitor Bank Panel Design to Improve Industrial Power System Efficiency and Safety

Industrial loads generally use control equipment and power electronics that use semiconductor materials that are very sensitive to voltage fluctuations. As reactive power compensation, industries usually use capacitor banks to increase power factor, reduce losses and increase line capacity. But it turns out that the use of capacitor banks also causes problems related to capacitor bank switching during the energizing process. During the energizing process, transient voltages and currents will be generated which can potentially damage control equipment, power electronic equipment, switching equipment and the capacitor bank itself. The Capacitor Bank panel assembly process involves the preparation of components such as MCB (Miniature Circuit Breaker), MCCB (Molded Case Circuit Breaker), Capacitor Bank, and other components. After that, these components are carefully assembled according to the pre-prepared design. Next, the installation of the Capacitor Bank panel involves mounting the panel to the location according to the plan and connecting it to the building's main power system. Accurate wiring and meticulous testing are required to ensure that the panels function properly. Therefore, a good understanding of the assembly and installation process of Capacitor Bank panels is essential to ensure efficient, and safety.

A deep learning approach for balance optimisation of patch panel assembly line

This paper introduces an integrated methodology to enhance the efficiency of patch panel assembly lines by harnessing advanced artificial intelligence (AI) techniques. The primary objective is to minimise the total completion time of patch panels, a pivotal metric for manufacturing efficiency. The study employs the Assembly Line Production Optimisation (ALPO) model to analyze and enhance the production capacity of the bottleneck station. Existing challenges related to patch panel assembly line task distribution, process content, and tooling layout are scrutinised against production process standards for operational measurements. To achieve improvement, Deep Neural Network (DNN) and Recurrent Neural Network (RNN) models are employed in hidden layers, supplemented by deep feed-forward (DFF) layers for output, in adherence to engineering design principles. The bottleneck station's load rate is successfully reduced to below 80%, contributing to an overall balance rate increase from 73% to 88%. These outcomes signify a notable enhancement in production efficiency and employee satisfaction. The research utilises a dataset derived from the Microsoft Azure AI-based PdM dataset. The paper illustrates how AI techniques offer a comprehensive solution to address the inherent complexities in patch panel assembly line optimisation.

Simulation of a Ship’s Block Panel Assembly Process: Optimizing Production Processes and Costs through Welding Robots

Conventional welding techniques for complex structures often rely on human involvement, which can be prone to errors when deviations from the planned process occur. In contrast, robotic welding is highly precise and effective, particularly in the assembly of complex structures such as double-bottom ships. Therefore, this paper presents a comprehensive technical and economic analysis comparing robotic welding to conventional welding in the assembly process of a ship’s block panels. The study aims to evaluate and compare the strategies employed in robotic welding and conventional welding, with a specific focus on the ship double-bottom context. Furthermore, an economic value analysis is conducted to assess the cost effectiveness of each approach. The analysis reveals that robotic welding can achieve a significantly faster welding speed, completing the process approximately 3.85 times quicker compared to conventional methods. Moreover, the ratio of electricity and man-hours between robot welding and conventional welding is 1:2.75. These findings highlight the potential for cost savings by implementing robotic welding processes. The analysis reveals a significant difference in operational costs, highlighting the efficiency and cost effectiveness of robotic welding compared to conventional methods.

Flow time in a human-robot collaborative assembly process: Performance evaluation, system properties, and a case study

In this article, an analytical method is introduced to evaluate the flow time of an assembly process with collaborative robots. In such a process, an operator and a collaborative robot can independently carry out preparation tasks first, then they work jointly to finish the assembly operations. To study the productivity performance of such systems, a stochastic process model is developed, where the joint work is modeled as an assembly merge process, and the task times of all operation steps are described by phase-type distributions. Closed-form solutions of system performance, such as flow time expectation and variability, as well as service rate, are derived analytically. The system properties of monotonicity, work allocation, and bottleneck identification are investigated. In addition, a case study is introduced to evaluate the performance of a front panel assembly process in automotive manufacturing.

Assembly Variation Analysis of Aircraft Panels under Part-to-part Locating Scheme

A typical aircraft panel is the assembly consisting of a multitude of thin and lightweight compliant parts. In panel assembly process, part-to-part locating scheme has been widely adopted in order to reduce fixtures. By this locating scheme, a part is located onto the pre-fixed part/subassembly by determinant assembly (DA) holes, and temporary fasteners (e.g., spring pin) are used for joining these DA hole-hole pairs. The temporary fasteners can fasten DA hole-hole pairs in the axial and radial directions of DA holes. The fastening in the radial directions is realized by the expansion of temporary fasteners. Although the usage of temporary fasteners helps reduce the positional differences between hole-hole pairs, their clamping forces thereby may lead to elastic deformation of compliant parts/subassemblies. Limited research has been conducted on such elastic deformation produced by temporary fastener and its influence on assembly dimensional quality. This paper proposes a novel rigid-compliant variation analysis method for aircraft panel assembly, incorporating the deformation in part-to-part locating process. Based on the kinematic theory and linear elasticity deformation assumption, the variation propagation through the locating process, as well as the entire assembly process of an aircraft panel, is formulated. Then, the statistical variation analysis is performed with Monte Carlo (MC) simulation. Finally, the proposed method is validated by a case study. The result shows the deformation in the part-to-part locating process significantly impacts the assembly variations, and our method can provide a more accurate and reliable prediction.

Lean Built-Up Panel Assembly in a Newbuilding Shipyard

The main shipbuilding assembly processes greatly influence the flow of interim products in a newbuilding shipyard. The panel assembly line is a major process located upstream of all the other shipyard assembly processes. In a previous paper, the application of lean principles enabled a balanced and smaller takt time along the workstations and yielded significant savings in man-hours. Although a panel consists of butt-welded steel plates with multiple fillet-welded longitudinal stiffeners, a built-up panel is this same panel fitted with longitudinal and transverse steel elements. Since there are many internal structural elements, the man-hours along a traditional built-up panel assembly line are multiple times greater than that of panel assembly. Therefore, it is necessary to analyze and map built-up panel assembly in an actual newbuilding shipyard. Using value stream mapping along with kaizen principles of continual improvement to determine the transformative steps to make the traditional built-up panel assembly line leaner. This enables significant man-hour reductions of about 60%, which yields remarkable cost savings to the shipyard. 1. Introduction The built-up panel assembly line process is located downstream to the panel assembly process, and in most shipyards, half of all steel panels become built-up panels. It is very labor intensive since there are many steel elements that need to be joined in both longitudinal and transverse directions and there are both fillet and vertical welding jobs to be done. The joining of built-up panels to panels yields large three-dimensional blocks. Although in past papers (Kolich et al. 2017, 2015a) a lean value stream mapping methodology to transform panel assembly was developed, it makes sense to develop a methodology for the more complex and man-hour intensive built-up panel assembly process as well. The transformed built-up panel assembly process will further reduce bottlenecks in the shipyard and improve flow bringing down man-hours, which translates to critical savings for the shipyard.

Lean Methodology to Transform Shipbuilding Panel Assembly

The core competence of any medium-to-large sized shipyard includes the panel assembly line. Ship panels are the basic building blocks of well over 60% of the interim products of typical commercial ships. Therefore the improvement of the panel assembly process could greatly reduce the number of man-hours of all assembled panels, thereby yielding significant savings to the shipyard. Using a lean methodology to make kaizen improvements to traditional panel assembly lines will greatly reduce the costs in ship production. This means that shipyards, which are barely keeping earnings above costs, will be able to increase profits. Value stream mapping is a key way of determining how lean a production process is. The wastes in production assembly are readily identified as well as the takt time and the areas where there is push as opposed to pull. In this paper, a case study of a typical commercial shipyard, which builds a product mix of vessels is analyzed. The present state panel assembly line is mapped and then using lean tools and avantgarde technologies, such as hybrid laser arc welding, the new transformed panel assembly line is demonstrated to bring man-hour reductions of over 80%, so that a typical panel is assembled using 12 man-hours as opposed to the present 72 man-hours. 1. Introduction The core competence of virtually any medium-to-large sized shipyard includes a panel assembly line. Many times shipyard management takes for granted that the panel assembly line is just fine as is and therefore it is not necessary to make analysis to improve this core shipbuilding assembly process any further. However, since flat panels make up well over 60% of the building blocks of most commercial ships, any type of significant improvement to the panel assembly line will result in important cost savings for the shipyard.

Research on surface normal measurement and adjustment in aircraft assembly

Drilling and riveting are commonly used in aircraft panel assembly process. Due to the fixture positioning error and the deformation of workpiece, the real position and orientation of the workpiece as well as its 3D geometry at the drilling position varies from the nominal CAD model, which would cause an unfavorable impact on assembly quality. Therefore, surface normal measurement and adjustment at the drilling position is of great importance. In this paper, a fast and effective non-contact measurement method for normal vector and height of moderately curved surfaces is accomplished by four laser displacement sensors, and a dedicated NC machine tool is also developed for normal adjustment. Firstly, a novel sensor calibration method based on laser tracker is introduced, which can acquire the sensors’ position and orientation in Tool Coordinate System (TCS) at the same time. The normal vector at hole position is calculated by cross product of any two non-parallel vectors constructed by the four laser projection points on the panel surface. Secondly, the kinematic model of the machine tool is established to calculate the adjustment of each axis of the machine tool with the Homogeneous Transformation Matrix (HTM). Besides, an innovative method to identify the distance of two rotary centers based on two laser interferometers is proposed. Finally, a series of experiments are conducted to validate the feasibility of the proposed method. The results show that the angle deviation can be reduced to less than 0.5° after adjustment, while the accuracy of the surface height is ±0.04mm.

Positioning variation modeling for aircraft panels assembly based on elastic deformation theory

Dimensional variation in aircraft panel assembly is one of the most critical issues that affect the aerodynamic performance of aircraft, due to elastic deformation of parts during the positioning and clamping process. This article proposes an assembly deformation prediction model and a variation propagation model to predict the assembly variation of aircraft panels, and it derives consecutive three-dimensional deformation expressions which explicitly describe the nonlinear behavior of physical interaction occurring in compliant components assembly. An assembly deformation prediction model is derived from equations of statics of elastic beam to calculate the elastic deformation of panel component resulted from positioning error and clamping force. A variation propagation model is used to describe the relationship between local variations and overall assembly variations. Assembly variations of aircraft panels due to positioning error are obtained by solving differential equations of statics and operating spatial transformations of the coordinate. The calculated results show a good prediction of variation in the experiment. The proposed method provides a better understanding of the panel assembly process and creates an analytical foundation for further work on variation control and tolerance optimization.

Digital combined measuring technology assisted quality inspection for aircraft assembly

Aimed at the issues,including that detail features of the large size aircraft panel components couldn't be achieved directly and the low measuring efficiency by using a laser tracker separately in large size aircraft panel shape measurement,a combined measurement method based on the laser tracker and the articulated arm coordinate measuring machine( AACMM) was proposed. Under the premise of the measurement precision,by adding the AACMM to the measurement field of laser tracker,the detailed forming information of large size aircraft panel could be acquired comprehensively. According to the characteristics of the aircraft panel assembly process,some combined measurement tools were developed based on the Spatial Analyzer software,which could process all measurement data from the combined measurement system. Some examples are also given to illustrate the effectiveness and the efficiency of the method.

Scale up of Panel Assembly for Moss Rooftop Greening Material (Sphagnum sp.) Using Dimensional Analysis

The research of moss greening material (Sphagnum sp.) as a rooftop panel is prior to commercial industry. Scale up of production must be prepared for maintaining quality of product through. Production system of moss greening panel consists of aquaculture and panel assembly process. This paper highlighted scale up of panel assembly using dimensional analysis. It is a method based on the principle of geometric similarity which were used in scale up of aquaculture process. Subsequently, it is used as a basic assumption to design an analog models in panel assembly process. The research aims are: 1) To design an analog models in scale up of panel assembly process based on scale up of aquaculture process; 2) To identify the critical variables in the scale up of panel assembly process. Research results concluded that an analog model can be designed for panel assembly. Critical variables was identified and calculated in scale up of panel assembly process by increasing length of panel were air flow rate (v), mass of dry moss (m), width of panel (l), and thickness of panel (t).

Compliant assembly variation analysis of aeronautical panels using unified substructures with consideration of identical parts

The assembly process of aeronautical panel usually involves numerous parts and subprocesses. Thus a large number of Finite Element Analysis (FEA) runs are required to construct its compliant Deviation Propagation Model (DPM), when using the traditional compliant assembly variation analysis methods such as the Method of Influence Coefficients and the Linear Contact method. In this paper, an efficient DPM construction method based on substructures is proposed to reduce the modeling complexity. Finite element models of compliant parts are condensed into substructures which have relatively fewer Degrees of Freedom (DOFs). And for the identical parts commonly used in the aeronautical panels, once the substructure of one part is generated, the substructures of the others can be obtained by transformation of the generated one. By properly selecting the retained DOFs, the same substructures are applicative throughout the overall modeling process. Based on these unified substructures, the DPM of aeronautical panel assembly process is constructed, without executing extra FEA runs. A case study on a panel subassembly of the side fuselage is used to illustrate the proposed method. The results show that, this method reduces the model size as well as the model construction work, while maintaining the same accuracy as complete finite element analysis conducted in a commercial software package.

Tolerance Allocation and Maintenance Optimal Design for Fixture in Multi-Station Panel Assembly Process

Traditionally, tolerance and maintenance designs have been studied separately in manufacturing systems. An integration optimization model of tolerance and maintenance for multi-station sheet metal assembly was presented in this work. Based on the variation propagation state space model, a quality loss model of multi-station assembly processes was built. This model considered the effect of process loss. It built the function of fixture tolerance, replacement cycle and total cost. The nonlinear tolerance optimization of locating holes (slots) in multi-station sheet metal assembly was achieved. The optimization model was calculated with practical data in a vehicle body side assembly. Compared with the same type model, it’s verified correct and rational of the model in multi-station sheet metal assembly process quality control.

Sensor system reliability modeling and analysis for fault diagnosis in multistage manufacturing processes

This paper investigates the reliability of coordinate sensor systems used for process fault diagnosis in multistage manufacturing processes. When considering catastrophic sensor failure, the reliability of a coordinate sensor system is defined based on its diagnosability performance. A mathematical tool called matroid theory is applied to study the reliability of the coordinate sensor system; properties of the minimal paths and minimal cuts are derived; efficient methods are developed to evaluate the exact system reliability for two special types of systems; and an efficient algorithm to evaluate the min–max lower bound of system reliability is provided that does not require assuming that all minimal paths must be known in advance. The proposed models and the developed methods are illustrated and applied in two case studies for fault diagnosis of a multistage panel assembly process.

Application of Matroid Theory for Diagnosability Study of Coordinate Sensing Systems in Discrete-Part Manufacturing Processes

Coordinate sensing systems have been widely used in various manufacturing processes to monitor product quality and automatically identify process faults. They play a crucial role in manufacturing quality improvement. For complex manufacturing processes, especially processes with multiple stages, typically not all process faults can be uniquely identified by a feasible sensing system. For these complex processes, a diagnosability study is an important issue for the evaluation and usage of coordinate sensing systems. This article conducts a diagnosability study of coordinate sensing systems based on matroid theory. The use of matroid theory improves understanding of existing results on diagnosability. In addition, new results and more efficient algorithms related to diagnosability study are investigated based on matroid theory. The developed theory and algorithms, which can be applied in a broad class of diagnosis problems, are demonstrated using a panel assembly process.

Optimal coordinate sensor placements for estimating mean and variance components of variation sources

In-process optical coordinate measuring machines offer the potential to diagnose the sources of the variations that are responsible for product quality defects. Such a sensor system can thus help manufacturers to improve product quality and reduce process downtime. The effective use of sensor data in the diagnosis of the sources of variations depends on the optimal design of the sensor system, which is often also called the problem of sensor placement. This paper addresses coordinate sensor placement for the diagnosis of dimensional variation sources in assembly processes. Sensitivity indices for the detection of the process mean and variance components are defined as the design criteria and are derived in terms of process layout and sensor deployment information. Exchange algorithms, originally developed for optimal experimental design, are revised and then used to maximize the detection sensitivity. A sort-and-cut procedure is proposed, which is able to significantly improve the algorithm efficiency of the current exchange routine. The resulting optimal sensor layout and its implications are illustrated in the specific context of a panel assembly process.

Optimal Engineering System Design Guided by Data-Mining Methods

An optimal engineering design problem is challenging because nonlinear objective functions usually need to be evaluated in a high-dimensional design space. This article presents a data-mining–aided optimal design method, that is able to find a competitive design solution with a relatively low computational cost. The method consists of four components: (1) a uniform-coverage selection method, that chooses design representatives from among a large number of original design alternatives for a nonrectangular design space; (2) feature functions, of which evaluation is computationally economical as the surrogate for the design objective function; (3) a clustering method, that generates a design library based on the evaluation of feature functions instead of an objective function; and (4) a classification method to create the design selection rules, eventually leading us to a competitive design. Those components are implemented to facilitate the optimal fixture layout design in a multistation panel assembly process. The benefit of the data-mining–aided optimal design is clearly demonstrated by comparison with both local optimization methods (e.g., simplex search) and random search-based optimizations (e.g., simulated annealing).

A High-Performance Short-Channel Bottom-Contact OTFT and Its Application to AM-TN-LCD

We have demonstrated an organic thin-film-transistor (OTFT)-driven active-matrix twisted-nematic liquid crystal display (AM-TN-LCD) on a glass substrate, with a resolution of 160/spl times/120 pixels, 79 ppi. Substrate temperature was kept below the plastic-compatible temperature of 180/spl deg/C throughout the fabrication process. In order to realize an OTFT-driven display with fine resolution, we employed short-channel bottom-contact (BC) pentacene OTFTs. It has been known that their drivability is limited by contact resistance at source/drain (S/D). We found that the S/D contact resistance was markedly reduced when the thickness of the nonohmic Ti adhesion layer for ohmic Au S/D electrodes was reduced less than /spl sim/3 nm. We elucidate that this 3 nm corresponds to the thickness of the accumulating layer in a pentacene channel. When we use a self-assembled monolayer of mercapto-silane-coupling agent as the adhesion layer, the contact resistance becomes negligibly small and BC OTFTs scalable below 10 /spl mu/m were obtained. In addition to this OTFT-cell technology, we developed a low-damage pentacene patterning technique for integration of OTFTs and introduced low-temperature panel assembly process to suppress thermal-stress degradation of pentacene OTFTs, which are the key technologies to achieve OTFT-driven AM-TN-LCD.

A Comparison of Process Variation Estimators for In-Process Dimensional Measurements and Control

Dimensional variation reduction is critical to assure high product quality in discrete-part manufacturing. Recent innovations in sensor technology enable in-process implementation of laser-optical coordinate sensors and continuous monitoring of product dimensional quality. The abundance of measurement data provides an opportunity to develop next generation process control technologies that not only detect process change, but also provide guidelines respective of root cause identification. Given continuous product dimensional measurements, a critical step leading to root cause identification is the variance estimation of process variation sources. A few on-line variance estimators are available. The focus of this paper is to study the interrelationships and properties of the available variance estimators and compare their performance. An operating characteristics curve is developed as a convenient tool to guide the appropriate use of on-line variance estimators under specific circumstances. The method is illustrated using examples of dimensional control for a panel assembly process.