Automatic Assembly Machine Research Articles

Feasibility Study of an Automated Assembly Process for Ultrathin Chips.

This paper presents a feasibility study of an automated pick-and-place process for ultrathin chips on a standard automatic assembly machine. So far, scientific research about automated assembly of ultrathin chips, with thicknesses less than 50 µm, is missing, but is necessary for cost-effective, high-quantity production of system-in-foil for applications in narrow spaces or flexible smart health systems applied in biomedical applications. Novel pick-and-place tools for ultrathin chip handling were fabricated and a process for chip detachment from thermal release foil was developed. On this basis, an adhesive bonding process for ultrathin chips with 30 µm thickness was developed and transferred to an automatic assembly machine. Multiple ultrathin chips aligned to each other were automatically placed and transferred onto glass and polyimide foil with a relative placement accuracy of ±25 µm.

Robust position control and disturbance rejection of an industrial plant emulator system using the feedforward-feedback control

An important class of electromechanical system known as the industrial plant emulator system which represents the many practical systems used in the industry. The motion control of the emulator system is challenging and important one as it mimics the system class of conveyors, machine tools, spindle drives, and automated assembly machines. In this paper, a new quantitative feedback-feedforward approach is proposed to address both tracking and the disturbance (measurable, uncertain) rejection problem. The proposed methodology is centered on the design of feedback controller with the inversion based feedforward control. The proposed method converts the problem on the uncertain system into a nominal sensitivity problem which is simple, less conservative and easier to solve for a large number of uncertain parameter system such as the emulator plant. The unknown dynamic of the disturbance (motor) is identified practically by a step response (three parameter model) for integrating system. The proposed feedforward/feedback control is experimentally demonstrated to meet the tracking and reject the disturbance with the less demand on the feedback control as compared to the existing methods under different loading condition.

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Detection of Visually Cued Faults in High Speed Automation

Manufacturers are experiencing ever greater pressures to meet a multitude of business demands: boost production rate, increase yield, improve quality and reduce operating costs, etc. One important measure of success is the ability of automated manufacturing processes to run fault free for extended periods of time. When faults do occur, they must be detected, diagnosed and corrected quickly. High speed automated assembly machines typically employ many different types of sensors to monitor machine health and feedback faults (both cautionary and reactionary) to a central controller for review by a technician or engineer. This paper describes progress with a project whose goal is to examine the effectiveness and feasibility of using machine vision to detect ‘visually cued’ machine faults in high speed automation equipment. Machine vision is commonly used in manufacturing to perform a ‘process’ role such as part quality inspection. Machine vision systems use cameras to capture images of parts in a manufacturing process. Computer software packages use custom algorithms to analyze these images, and determine the quality (or even presence) of the part based on physical characteristics including part geometry and colour. If machine vision were successfully applied as a fault monitoring system, it could effectively reduce the amount of sensors needed to monitor the machine’s operation, as a single camera could monitor several locations where known faults occur. The intent is to not only reduce the amount of sensors required to effectively monitor a machine, but to make the machine ‘smarter’ by enriching the data used for fault detection.

MOGA-Based Optimization Design of Core Portion of Press-Fit Assembly Machine in Car Radiator

For the overweight of automatic car radiator core assembly machine crimping part, the structure was optimized and designed based on ANSYS Workbench to satisfy the double objective about reducing weight and decreasing the impact of the amount of deformation of the core assembly components. Multi-objective genetic algorithm was carried out to search the Pareto optimal solution set for optimal and design problems. It shows that the weight of crimping part reduces by 5.34% compared with the previous part, the assembly flatness of core reduces by 13.43%, and the total deformation affecting mainboard press-fit and positional accuracy of the flared reduces by 6.89%, which all meet the requirements of multi-objective optimization design.

Integrating ergonomics and lean manufacturing principles in a hybrid assembly line

Lean manufacturing is a production method that was established in the wake of the Japanese Toyota Production System and rapidly established in the worldwide manufacturing industry. Lean characteristics combine just-in-time practices, work-in-progress and waste reduction, improvement strategies, defect-free production, and standardization. The primary goal of lean thinking is to improve profits and create value by minimizing waste. This study introduces a novel mathematical model to design lean processes in hybrid assembly lines. The aim was to provide an effective, efficient assembly line design tool that meets the lean principles and ergonomic requirements of safe assembly work. Given the production requirements, product characteristics and assembly tasks, the model defines the assembly process for hybrid assembly lines with both manual workers and automated assembly machines. Each assembly line solution ensures an acceptable risk level of repetitive movements, as required by current law.This model helps managers and practitioners to design hybrid assembly lines with both manual workers and automated assembly machines. The model was tested in a case study of an assembly line for hard shell tool cases. Results show that worker ergonomics is a key parameter of the assembly process design, as other lean manufacturing parameters, e.g. takt time, cycle time and work in progress.

A Problem of Particulate Contamination in an Automated Assembly Machine Successfully Solved by CFD and Simple Experiments

Assembly of hard disk drives (HDDs) needs to be done in an automated assembly machine (AAM) virtually free of particulate contamination that can cause them to malfunction. Fan filter units (FFUs) are installed above the AAM to reduce the number of suspended particles in the recirculating air flowing over and around them. At one time, several HDDs were found to be defective. To find out the root cause of this problem, computational fluid dynamics (CFD) was used to investigate the airflow over and around the AAM. It was found that the cause of the high particle counts was improper air speed from the FFUs. The optimal FFUs air speed needed to be in the range of 0.35–0.65 m/s in which the airflow would block out nearby airborne particles and purge away particles generated by the AAM effectively which would, in effect, reduce the particle counts down below the threshold level of class 100 clean room. A few available measurement tools at the factory were then used to perform validating measurements against the simulation results, and the validation was positive. This optimal speed range was implemented at the factory after which the level of contamination was reduced to an acceptable level.

Fault detection and classification in automated assembly machines using machine vision

Automated assembly machines operate continuously to achieve high production rates. Continuous operation increases the potential for faults such as jams, missing parts, and electromechanical failures of subsystems. The goal of this research project was to develop and validate a machine vision inspection (MVI) system to detect and classify multiple faults using a single camera as a sensor. An industrial automated O-ring assembly machine that places O-rings on to continuously moving plastic carriers at a rate of over 100 assemblies per minute was modified to serve as the test apparatus. An industrial camera with LED panel lights for illumination was used to acquire videos of the machine’s operation. A programmable logic controller (PLC) with a human-machine interface (HMI) allowed for the generation of faults in a controlled fashion. Three MVI methods, based on computer vision techniques available in the literature, were developed for this application. The methods used features extracted from the videos to classify the machine’s condition. The first method was based on Gaussian mixture models (GMMs); the second method used an optical flow approach; and the third method was based on running average and morphological image processing operations. In order to provide a single metric to quantify relative performance, a machine vision performance index (MVPI) was developed with five measures of performance: accuracy, processing time, speed of response, robustness against noise, and ease of tuning. The MVPI for the three MVI methods is reported along with the significance of the results.

An unsupervised artificial neural network versus a rule-based approach for fault detection and identification in an automated assembly machine

Artificial neural networks (ANNs) are suitable for fault detection and identification (FDI) applications because of their pattern recognition abilities. In this study, an unsupervised ANN based on Adaptive Resonance Theory (ART) is tested for FDI on an automated O-ring assembly machine testbed, and its performance and practicality are compared to a conventional rule-based method. Three greyscale sensors and two redundant limit switches are used as cost-effective sensors to monitor the machine's assembly process. Sensor data are collected while the machine is operated under normal condition, as well as 10 fault conditions. Features are selected from the raw sensor data, and data sets are created for training and testing the ANN. The performance of the ANN for detecting and identifying known, unknown and multiple faults is evaluated; the performance is compared to a conventional rule-based method using the same data sets. Results show that the ART ANN is able to achieve excellent fault detection performance with minimal modeling requirements; however, the performance depends on careful tuning of its vigilance parameter. Although the rule-based system requires more effort to set up, it is judged to be more useful when unknown or multiple faults are present. The ART network creates new outputs for unknown and multiple fault conditions, but it does not give any more information as to what the new fault is. By contrast, the rule-based method is able to generate symptoms that clearly identify the unknown and multiple fault conditions. Thus, the rule-based method is judged to be the most feasible method for FDI applications.

A Comparative Study of Machine Vision Based Methods for Fault Detection in an Automated Assembly Machine

Fault detection and classification in an automated assembly machine using machine vision (MV) based inspection methods is the subject of this paper. A high speed automated assembly machine is used as the test apparatus. The machine is designed to assemble circular O-rings, from a bulk supply, onto continuously moving carriers at a rate of over 100 assemblies per minute. Video data was collected for both normal and abnormal machine conditions, and in particular transfer track jams. Three MV classification methods were adapted to this application and subsequently tested: 1) Gaussian Mixture Models (GMMs) with blob analysis, 2) optical flow and 3) running average. The methods are compared with a previously developed fault detection method based on spatiotemporal volumes (STVs). It is observed that the new methods require less training and processing time and are able to detect faults faster than the STV method. Amongst the three new methods, the running average method is shown experimentally to be the best in terms of having the lowest processing time per frame and the fastest response time. The work continues in order to see how the methods perform as different machine faults are introduced.

Developing of High-Power Sandwich Type Piezoelectric Transducer Automatic Assembly Machine

This paper discusses the basic parts of the assembly machine,calculate the relationship between torque and axial force,torque and voltage of the piezoelectric transducer.It also analysis the mechanical structure of mechanical.It introduces the motor’s control method .the successful assembly machine is used to assemble the piezoelectric transducer,the experiment indicates that with the increase of voltage, the resonance frequency increases,the impedance is on the decline,the static capacitance remains unchanged basically.And comparison of the assembled and the first assembly piezoelectric transducer,the latter has better performance.

Development and Applications of the SCARA Robot

In the 1980s, when the author worked for Seiko Epson Corporation as a wristwatch production engineer, consumer needs had become so diversified that wristwatches had to be assembled on the same automated assembly line in small lots of about 10,000 pieces per month. Most of the robots available in those days were for processing purposes such as spot welding and were not applicable in practical terms to automated assembly lines for wristwatches in precision, speed, ease of use or cost. The prototype SCARA robot developed by the SCARA Study Group led by Dr. Hiroshi Makino, a professor at the Department of Precision Engineering at Yamanashi University, was found to be the most suitable for automated watch assembly lines. We reviewed assembly work procedures and succeeded in limiting the number of simultaneous control axes to four at a maximum and in cutting assembly costs to 60% of those of conventional processing robots. As the term “selective compliance” suggests, SCARA robots possess all of the functions necessary for stable assembly and for precision and speed. Development team members, including the author, made the most use of previous experience in developing dedicated automated assembly machines for in-house use and succeeded in developing practical SCARA robots by creating a robot language based on workers’ voice. In applications of SCARA robots, this paper introduces just two of many possible examples. One is for oiling work on manual assembly lines and the other is the TAF-M mixed-models wristwatch assembly line. In the oiling work application example, SCARA robots used for infinitesimal oiling work on a manual assembly line for small lots of luxury wristwatches have been found to be very cost-effective and useful for training operators and/or programmers for robots. The TAFM application example represents the assembly line built based on the original Seiko-Epson purpose for introducing SCARA robot development, which consists of both robots and of 52 newly developed “assembly robot cells” where most assembly work should be done. An assembly robot cell includes a SCARA robot, a main conveyor, a multiple-parts feeder, an automatic hand changer, an assembly detection unit, etc. At present, one such assembly line automatically assembles more than 100 models of wristwatches. Use of such automated assembly lines has reduced the human workforce by about 40 workers, cut costs by over 60%, and shortened delivery time by about 50%.

Condition Based Maintenance Optimization of an Aircraft Assembly Process Considering Multiple Objectives

The Commercial Aircraft Cooperation of China (COMAC) ARJ21 fuselage’s final assembly process is used as a case study. The focus of this paper is on the condition based maintenance regime for the (semi-) automatic assembly machines and how they impact the throughput of the fuselage assembly process. The fuselage assembly process is modeled and analyzed by using agent based simulation in this paper. The agent approach allows complex process interactions of assembly, equipment, and maintenance to be captured and empirically studied. In this paper, the built network is modeled as the sequence of activities in each stage, which are parameterized by activity lead time and equipment used. A scatter search is used to find multiobjective optimal solutions for the CBM regime, where the maintenance related cost and production rate are the optimization objectives. In this paper, in order to ease computation intensity caused by running multiple simulations during the optimization and to simplify a multiobjective formulation, multiple Min-Max weightings are used to trace Pareto front. The empirical analysis reviews the trade-offs between the production rate and maintenance cost and how sensitive the design solution is to the uncertainties.

Manual Assembly Workstation Redesign Based on a New Quantitative Method for Postural Comfort Evaluation

Main purpose of this work is to show how easy and economics an ergonomic/comfort based approach, in re-design a manual assembly workplace, can be; authors, using a new comfort/ergonomic evaluation criterion, analyzed a workstation and identified the critical issues under ergonomic/comfort point of view and finally gave several guidelines to re-design the workplace, implementing minor modification, and improve work-safety, work-quality and productivity. The postural analysis was performed by non-invasive and especially inexpensive methods, based on cameras and video-recorder use and by photogrammetric analysis; DELMIA® DHM software has been used to perform all simulations; comfort analysis was performed by the software developed by researchers of Departments of Industrial Engineering of Salerno: CaMAN®. The test case is an automatic assembly machine that has been modeled and used for virtual postural analysis. Main results of this work can be found in a very good numerical/experimental correlation between acquired/simulated postures and real ones, and on the powerful use of an objective comfort evaluation method, based on biomechanics and posture analysis, for giving to designers the guidelines to re-design a workplace and a work-cycle. This kind of approach seemed to be very powerful in re-designing the work-place and in re-scheduling the work time-sheet because it allowed to improve an ergonomic corrective action with minor costs for company. Obtained results demonstrated the validity of re-design hypotheses through the increase of all comfort indexes and the improvement of workstation/operator productivity.

Fine Tuning of Automated Assembly Machines Using Video Analysis

Human/machine interaction is of still importance in the age of automation. Automated assembling devices are customizable products that need basic settings before installation. Capabilities of operators have to be taken into consideration in this process. This paper presents a procedure based on video recording to determine time data for machine settings. It allows the engineers to forecast the expected capacity of individual workstation and the entire production line. A case study from industry is used to illustrate the application of the system.

The Technology of Positional Detection in Automatic Wheelset Assembly Machine

This paper introduces a kind of position measurement and control systems in automatic wheelset assembly machine. This system adopts direct close-loop position control in the process of pressing and real time monitor position of wheel and axle with high accuracy. Compared with traditional wheelset assembly machine, it can improve production efficiency and ensure the quality of pressing through control the distance between backs of wheel flange and the position difference of two wheels accurately.

Measurement and Calibration of the Displacement and Pressure in Automatic Wheelset Assembly Machine

This paper introduces the measurement systems of the oil cylinder in automatic wheelset assembly machine, theoretically analyzes the error of the displacement measurement system by curve fitting, and gets verification the error analysis in practice. This paper also calibrates pressure sensor from zero drift, slope of the output of the pressure sensor to guarantee the system pressure, and compensated pressure sensor value consistent.

Design of a New Structure for Anti-Upsetting of Axle-End in Wheelset Disassembly and Assembly

This paper presents a new type of anti-upsetting equipment, which is used to avoid upsetting of axle-end in wheelset disassembly and assembly. The special structure of the equipment can transmit the cylinder’s pressure to the axle-end rationally and eliminate eccentric-loaded or partial stress concentration on the section of the axle-end. The anti-upsetting equipment has been analyzed and verified with the finite element software. This new type of anti-upsetting equipment is applied on an automatic wheelset disassembly and assembly machine to ensure the anti-upsetting on axle-end.

Design of Electric Connector’s Automatic Assembly System

For improving assembly quality and automation of electric connectors, a solution of automatic assembly is discussed in this paper. With the machinery vision system, defects of the parts to be assembled can be real-time surveyed. By using the complex image recognition technology, the recognizing accuracy and reliability can be achieved. The designs of NC dividing head and smart positioning unit can make the process of transmission and assembly more perfect and effective. The optimal design of the mechanical structure has been made by virtual prototype technology. The designs of PLC control system and pneumatic system which are used in the automatic assembly machine have also been discussed. The control strategies of assembling process are quite challenges. The control profile of three stages has been used in the pressing assembly process, which can punch the parts assembled properly and smoothly without any surface damage. Also the application shows that the design is effective.

Monitoring System Design of Fuse Automatic Assembly Machine Based on WinCC

Structure and function of assembly machine were introduced on the background of engineering project-“research and development of fuse automatic assembly machine”. The control system was realized by protocol communication between S7-300 PLC as on-site control unit and industrial personal computer(IPC). The IPC monitoring system was developed by WinCC V6.0 configuration software and the work process of assembly machine,which includes real monitoring, voice alarm, operation permission setting, data archiving,etc.,was implemented by combining VB and C script. The assembly machine met production requirements by testing.