Automated Assembly Systems Research Articles

Self-Repairing Humidity-Adjustable Anisotropic Adhesion Switch for Smart Manipulation.

Stimuli-responsive surface adhesion regulation is widely used in automated assembly systems, intelligent pick-up and placement systems, and soft crawling robots. However, in the actual separation process, it tends to produce separation residue or excessive adhesion. Therefore, how to regulate surface adhesion on demand is a significant challenge. Herein, inspired by the anisotropic adhesion behavior of butterflies and the controlled adhesion behavior of octopuses, based on molecular conformational rearrangement and anisotropic structures, a humidity-responsive PES-PI/PDMS composite surface is achieved to meet the needs of controllable adhesion orientation and strength, which could be used for an intelligent transfer system (grasping and releasing and anisotropic transporting). Humidity can effectively tune the hydrogen bonding and the interaction between polymers, resulting in excellent self-healing and durability properties of the composite surface. Moreover, humidity could adjust the surface transmittance as well, making it possible to be used in humidity sensing and in a detection and encryption/decryption system to enhance environmental monitoring and information protection capabilities. This work not only establishes a method for the fabrication of innovative "high-flexibility" adhesive materials but also provides approaches for the design and development of intelligent response devices.

Assembly process analysis and system design for deep in-situ fidelity corer

The deep in-situ corer is an essential tool for exploring the physical and mechanical behaviours of rocks at varying depths. Corers are multi-part products, encompassing extensive redundant assembly information stemming from the intricate assembly processes and numerous components. Thus, designing assembly systems for corers poses complexity challenges. This paper proposes an automated assembly system design framework, comprising assembly process analysis and system development. The proposed framework offers comprehensive design processes for multi-part product assembly systems, emphasizing managing information amount and complexity during the design phase. Specially, design principles and methods for minimizing information amount are analysed. And the directed graph is utilized to express the assembly information. Building upon this foundation, automated assemblability assessment and assembly process modular clustering is proposed to amalgamate and streamline assembly information, thus reducing design complexity. Leveraging pre-processed assembly information, the sub-functional solutions for assembly system are solved and optimized with AD (Axiomatic Design) and TRIZ (the Theory of Inventive Problem Solving). A case study of the deep-sea gas hydrate corer validated the effectiveness of the proposed methods in reducing information amount and yielding sub-functional solutions, thereby facilitating overall system design realization. Assembly experiments verified the designed system accomplished functional requirements. This study serves as a valuable reference for automated assembly analysis and system development for multi-part products, offering technical insights into developing deep in-situ cores from an assembly perspective.

A Robust Texture-Less Gray-Scale Surface Matching Method Applied to a Liquid Crystal Display TV Diffuser Plate Assembly System

In most liquid crystal display (LCD) backlight modules (BLMs), diffuser plates (DPs) play the essential role in blurring the backlight. A common BLM consists of multiple superimposed optical films. In a vision-based automated assembly system, to ensure sufficient accuracy, each of the multiple cameras usually shoots a local corner of the DP and jointly estimates the target pose, guiding the robot to assemble the DP on the BLM. In general, DPs are typical of texture-less objects with simple shapes. Due to the image background of superimposed multilayer optical films, the robustness of the most common detection methods must be improved to meet industrial needs. To solve the above problem, a texture-less surface matching method based on gray-scale images was proposed. An augmented and normalized gray-scale vector represents the texture-less gray-scale surface in a low-dimensional space. The cosine distance is then used to calculate the similarity between the template and matching vectors, combined with shape-based matching (SBM); the proposed method can obtain high robustness when detecting DPs. An image database from actual production lines was used in the experiment. In comparative tests with the NCC, SBM, YOLOv5s, and YOLOv5x methods, our proposed method had the best precision at all confidence thresholds. Although recall was slightly inferior to SBM, the comprehensive evaluation F1-Score reached 0.826, significantly outperforming the other methods. Regarding localizing accuracy, our algorithm also performed best, reaching 5.7 pixels. Although the time consumption of a single prediction is about 0.6 s, it can still meet industrial needs. These experimental results show that the proposed method has high robustness in detecting DPs and is especially suitable for vision-based automatic assembly tasks in BLM.

Automatic cover assembly system for a certain type of pendulum accelerometer

Automatic cover assembly system for a certain type of pendulum accelerometer

Automatic assembly and adjustment system for target surface of CMOS circuit board of star sensor

Automatic assembly and adjustment system for target surface of CMOS circuit board of star sensor

Information process-system modelling for Circular Economy of manufacturing systems

Recent push towards sustainable development have lead machine tool builders to begin adopting novel business models which are usually peculiar in product-service-systems. In particular, business models as ‘pay-per-use’ introduced the issue of rental of production capacity integrated with the management of the life cycle of assets in a Circular Economy perspective. However, when it comes to machine tool builders, the high degree of customization of capital goods and in particular of multi-stage automated assembly systems that are strongly linked to the characteristics of the final product make this solution more difficult. Hence, the implementation of such business models represents a clear challenge for machine tool builders and manufacturing system suppliers from technological perspective. This work discusses preliminary results in the technological implications of such strategy. A real industrial case related to cross-sector multi-stage automated assembly systems is presented to highlight the technological challenges and potential research directions.

Development of an industrial robot based automated assembly system

Nowadays, industrial robots are increasingly being used in all areas of human life. For each specific application, it requires students the knowledges of mechanical design, electrical engineering and motion programming. This paper presents the steps to build a model of an automated industrial robot that installs RAM modules on a mainboard of computer for educational purposes at the University of Transport Technology. The assembly system using a 6 degrees of freedom industrial robot with the type of KUKA KR6 R900-2 helps student to practice their thinking to design systems, self problem-solving skills.

Ergonomic Design of an Adaptive Automation Assembly System

Ergonomics is a key factor in the improvement of health and productivity in workplaces. Its use in improving the performance of a manufacturing process and its positive effects on productivity and human performance is drawing the attention of researchers and practitioners in the field of industrial engineering. This paper proposes an ergonomic design approach applied to an innovative prototype of an adaptive automation assembly system (A3S) equipped with Microsoft Kinect™ for real-time adjustment. The system acquires the anthropometric measurements of the operator by means of the 3-D sensing device and changes its layout, arranging the mobile elements accordingly. The aim of this study was to adapt the assembly workstation to the operator dimensions, improving the ergonomics of the workstation and reducing the risks of negative effects on workers’ health and safety. The case study of an assembly operation of a centrifugal electric pump is described to validate the proposed approach. The assembly operation was simulated at a traditional fixed workstation and at the A3S. The shoulder flexion angle during the assembly tasks at the A3S reduced between 18% and 47%. The ergonomic risk assessment confirmed the improvement of the ergonomic conditions and the ergonomic benefits of the A3S.

Automatic Assembly Technology of Dense Small Screws for Flat Panel Parts

Screw assemblies of radar are characterized by numerous densely distributed small screws of various types, rendering their manual assembly difficult and inefficient. To improve the assembly quality and efficiency, an automatic assembly system was developed. First, the position and attitude relationships among the workpiece, camera, and base coordinate systems of the manipulator were obtained using three-point location and nine-point calibration methods. Second, a visual servoing strategy is designed for guiding the manipulator such that its position can be adjusted adaptively to achieve the high-precision positioning of threaded holes. Third, a method for evaluating assembly quality is developed. The templates of angle–torque curves of various screws were produced by fitting experimental data. Furthermore, the assembly quality was determined by calculating the similarity between the angle–torque curves and templates based on the Fréchet distance. Finally, the feasibility was verified using a flat plate component with five threaded holes.

Optimal design of automatic assembly system for bolts and nuts in sets

Due to the slow assembly speed, large consumption of compressed air, and low qualification rate, the automatic assembly system for bolts and nuts in sets needs to be optimized urgently. The performance requirements of the system were analyzed, and the evaluation indexes of the system were proposed. Since the efficiency of the system mainly depends on the pneumatic components, the optimization work focuses on the pneumatic circuit. Parameters of the pneumatic circuit and pipeline were obtained through modeling and simulation. After parameter optimization, prototype test results have shown that the assembly speed and qualification rate of the optimized system is increased by 47.83% and 7.77%, respectively, while the air consumption is reduced by 23.39% compared with the original system.

Experimental Tests in Production of Ready-to-Drink Primitive Wine with Different Modes of Circulation of the Fermenting Must

Energy efficiency is an increasingly important issue in the wine industry worldwide. The focus on quality in wine production has led to increased attention being paid to the product at all stages of processing. The interaction with mechanical components is considered one of the possible critical points in the vinification process, and it becomes fundamental to optimize specific points in the wine production line using the best extraction technique. Therefore, in this work, experimental monitoring of two types of product circulation systems in fermentation was carried out in a winery in Puglia (Italy). In particular, the functional performance and energy consumption of two identical vinification lines were monitored, in which the only variables were two types of circulating systems for the fermenting must: pump-over and pneumatic cap breaking. During the trials, a homogeneous batch of Primitivo grapes was processed, hand-picked and taken to the winery within 1 h of harvesting, where a “ready-to-drink” wine production line was set up. A net quantity of 1000 hL of destemmed grapes was placed in two identical vertical steel tanks. Both wine tanks were monitored and equipped with an automated assembly system and a pneumatic marc breaker. Once both tanks were filled, a first break of the cap was carried out using a pneumatic system in one tank and an automatic pump-over in the other. For the grapes and type of wine studied, the pneumatic system showed better functional performance in terms of vinification speed and energy consumption; on the other hand, the pump-over system performed better in analytical terms. Finally, the results obtained highlight the need for further studies on equipment design to obtain significant benefits in terms of wine production costs while maintaining the quality standards required for “ready-to-drink” wines.

The Development of an Automatic Test Assembly System for a Formative Assessment in Mastery Learning Instruction: Case of the SQL Mastery Course

The Development of an Automatic Test Assembly System for a Formative Assessment in Mastery Learning Instruction: Case of the SQL Mastery Course

Inventive redesign for automatic assembly in the household appliances industry

PurposeIn the redesign process of assembly components that need adaptation to robotic assembly, designers can find support from structured methodologies for innovation, such as the theory of inventive problem solving (TRIZ). This paper aims to illustrate the authors’ methodology for redesigning gas hobs components for adaptation to robotic assembly.Design/methodology/approachA designer approaching a redesign task of an assembly component of any kind for adaptation to robotic assembly must consider, first of all, the features and limitations of existing robotic assembly systems; the generation of new design ideas that best fit the requirements may result to be a very challenging task. Here, the TRIZ methodology has proven useful for generating design ideas and finding the best solution.FindingsThe authors’ methodology approaches the challenges of redesign tasks for robotic assembly adaptation, which exploits knowledge of automatic and robotic assembly systems and the TRIZ method for innovation; it has proven useful in the redesign, checks and prototyping of gas hobs components.Originality/valueThis paper shows how the TRIZ methodology can be integrated into the redesign process and its impact on an industrial environment. The work’s main value is to provide a set of steps to help the designers change their design components approach that is necessary but not still implemented to optimize the use of the automation.

Autonomous Obstacle Avoidance Path Planning for Grasping Manipulator Based on Elite Smoothing Ant Colony Algorithm

Assembly robots have become the core equipment of high-precision flexible automatic assembly systems with a small working range. Among different fields of robot technology, path planning is one of the most important branches. In the present study, an elite smoothing ant colony algorithm (ESACO) is proposed for spatial obstacle avoidance path planning of the grasping manipulator. In this regard, the state transition probability and pheromone update strategies are improved to enhance the search capability of path planning symmetry and the convergence of the algorithm. Then a segmented B-spline curve is presented to eliminate path folding points and generate a smooth path. Finally, a manipulator control system based on the Arduino Uno microcontroller is designed to drive the manipulator according to the planned trajectory. The experimental results show that the performance of the ESACO algorithm in different scenarios has symmetry advantages, and the manipulator can efficiently complete the simulation trajectory with high accuracy. The proposed algorithm provides a feasible scheme for the efficient planning of manipulators in equipment manufacturing workshops.

Design of Mobile Phone Automatic Assembly System Based on Machine Vision

In the four links of mobile phone production, assembly employees account for 60%. In order to improve the assembly efficiency of mobile phone, this paper designed a mobile phone automatic assembly system based on machine vision. The system mainly includes PLC control system, mechanical arm, vision system and touch screen. SIMATIC S7-1200 CPU 1214C is used as PLC controller, and control program is designed.The mobile phone shell, mobile phone chip and screen panel are captured and assembled by DOBOT MG400 four-axis mechanical arm of Yuejiang Technology. Hikvision’s products are selected as the hardware of the vision system, and vision program is designed using DobotVisionStudio algorithm platform of Yuejiang Technology. Vellon’s MT6071IP/MT8071IP (800×400) is the touch screen for the system, and through it, the system can be manually controlled and monitored. Practice has proved that the mobile phone automatic assembly system designed in this paper can perfectly complete the whole process of mobile phone assembly, and the success rate is more than 99%.The mobile phone automatic assembly system based on machine vision has high success rate, high stability, labor saving and long-term operation, which has a certain practical reference significance.

Error compensation of industrial robot based on deep belief network and error similarity

• A error estimate model is established and verified by testing to predict the pose error of the robot. • Combines the advantages of deep nerual network and error similarity, the statistical feature of robot error similarity can improve the robustness and prediction accuracy of the error estimate model. • Cross contrast training can extract the contrast information and enlarged the sample size. • The proposed scheme doesn't depend on the kinematic parameters of the robot and needs neither retrofitting with the robot's control system and massive measurements. • The proposed scheme can effectively reduce the maximum positional errors and orientation errors of the robot. Abstract With the advantages of the high degree of freedom and large action space, industrial robots are gradually widely used in high-end large-scale equipment automatic assembly fields such as aerospace. It is very important to improve the absolute pose accuracy of the robot. This paper presents a deep learning scheme for the compensation of absolute pose errors for industrial robots. A mapping model of the robot's theoretical pose coordinates and actual pose errors is established based on the deep belief networks and error similarity, the pose error prediction is realized. Combined with the offline feedforward compensation method, the scheme has been verified on a 6-DOF serial industrial robot KUKA KR500-3 of robot automatic assembly system. The proposed scheme combines the feature expression of deep learning with statistical interpretability of error similarity, does not depend on the specific kinematic model of the robot, and without retrofitting with high-end encoder. After compensation, that the maximum absolute positional error and orientation error of the robot end-effector was reduced by 83.99% from 1.524 mm to 0.244 mm and reduced by 54.88% from 0.082 deg to 0.037 deg respectively, which can meet the accuracy requirement of the robotic automatic assembly system.

AI-enhanced vision system for dispensing process monitoring and quality control in manufacturing of large parts

Assembly is one of the cornerstones of today’s manufacturing; thus, efficient automated assembly systems have become a necessity in the recent past. Challenges that have traditionally been present in such systems involve positioning accuracy, stable gripping, accommodation of several variants by the same resources and prevention of error aggregation. In robot-based applications the detection of parts and their components is a common task, but when it comes to large objects which cannot be portrayed in single camera frames, the complexity becomes significantly larger. This paper presents an AI based perception system which employs a 3D vision sensor to implement a smart dispensing application and perform online process quality control of large parts assembly. The aim of the system is to provide execution autonomy for a robotic manipulator that is responsible for glue dispensing on different types of aluminium profiles of varying cross-sections, length, and associated glue patterns. By using an eye-in-hand RGB-D camera and employing deep learning methods (Yolov3 algorithm), the framework recognizes the type of profile that is going to be processed, and depth information is used to extract the profile’s points (starting-ending points) on which glue must be dispensed. Point Cloud manipulation (DBSCAN clustering, plane segmentation) and 2D image-based processing were tested during the quality inspection, in order to validate the success and accuracy of the process (detection of glue discontinuities, calculation of the glue volume level). The system has been deployed on a case study involving the assembly of components on buses and the results indicate that a robust recognition and adhesive application can be obtained throughout each operation cycle.

A method to assess design complexity of modular automatic assembly system in design phase

PurposeTo find the system with minimum investment and best quality performance that is capable of producing all of the product variants, assessing the complexity of designing assembly system at the early concept stage is an essential step, which helps and instructs a designer to create a product- and system-oriented assembly solution with the least complexity. The purpose of this paper is to propose a quantifying measurement of complexity in the design of a modular automated assembly system.Design/methodology/approachThe configurable assembly system is becoming a trend, which enables companies to quickly respond to changes caused by different product variants but without a large investment. One of the enabling factors is the availability of modular solutions of assembly modules that can be configured according to different technical requirements. This paper develops a methodology using fuzzy evaluation to calculate the design complexity in the design phase for a modular automatic assembly system. Fuzzy linguistic variables are used to measure the interaction among the influence factors, to deal with the uncertainty of the judgement. The proposed method investigates three matrices to present how the function-based assembly modules, design complexity factors, part attributes and product components, which are regarded as the main influence factors, complicate the construction of a modular assembly system. The design complexity is derived and quantified based on these assessments.FindingsThe proposed approach presents a formal quantification to evaluate the design complexity with regard to a modular assembly system from beginning, which can be identified and used as criteria to indicate the quality of performance and investment cost in advance. A mathematical model based on the fuzzy logic is established to provide both theoretical and practical guidance for the paper. To validate the predictive model, the statistic relationships between the assessed system design complexity, real assembly defect rate and investment cost are estimated based on regression analysis. The application of the presented methodology is demonstrated with regard to a traditional rear drive unit in the automotive industry.Originality/valueThis paper presents a developed method, which addresses the measures of complexity found in the design of a modular assembly system. It would help to run the design process with better resource allocation and cost estimation in a quantitative approach.

A novel vision-based method for 3D profile extraction of wire harness in robotized assembly process

Automating stages for deformable objects in the production line, in which assembling a wire harness into a predefined position is a complex task owing to the specialized characteristics of the objects. Besides a few automatized systems proposed in the other studies to implement this task under simplified setup conditions, a significant portion of this process remains to be completed manually in industrial environments. To construct an automatic wire harness assembly system, the development of a method that can automatically detect the wire harness profile in a 3D environment and, consequently, guide robot arms to implement assembly tasks is indispensable. Therefore, this study presents an approach that satisfies this requirement, which not only proposes a deep learning-based system to detect the wire profile, but also improves the accuracy of the detected results through a correction method according to the depth values of contiguous areas. The verification of the approach in a robot system that highlights its usefulness and practicality demonstrates the potential of the proposed method to replace people and consequently, reduce labour costs in factory environments.

Systematic Research on Auto Assembly and Disassembly of Small Engine in Aircraft

The engine is one of the key core components in aircraft, in order to enhance automation and efficiency in the process of installation and disassembly for current small engine, using automatic control technology, a set of automatic disassembly and assembly system for aircraft engines is developed to replace the traditional mechanical installation vehicle. Corresponding for small engine to study the automatic disassembly system, the system uses laser sensors to locate the engine disassembly and assembly. Servo motors are used to drive the walking mechanism, lifting mechanism, and fine-tuning mechanism to realize multi-degree-of-freedom adjustment during engine disassembly and assembly. And the digital video is used to monitor the gap collision. Finally, the paper realizes the automatic high-precision disassembly and assembly of small engines. Through verification, the efficiency of the disassembly and assembly system has increased by more than 70%, the work efficiency has been greatly improved.