Assembly Manufacturing Process Research Articles

Framework design of distributed P2P2G energy transaction considering photovoltaic power and dispatch of manufacturing facilities

In this paper, a distributed peer-to-peer-to-grid (P2P2G) energy transaction framework considering photovoltaic generation and dispatch of manufacturing facilities is designed to increase the penetration of renewable energy resource. The factory with typical manufacturing assembly production task, photovoltaic panels and battery is regarded as a micro-grid (MG) to participate in the energy transaction market. The designed framework contains two levels. In the upper level, each MG determines the scheduling of manufacturing facilities and battery and the quantities of P2P2G energy transactions based on the given P2P energy transaction price and distribution locational marginal price (DLMP), in which the complex typical manufacturing assembly process is formulated as a kind of deferable load and the DLMP is updated according to the optimal power flow (OPF) of the network. In the lower level, peer-to-peer (P2P) energy transaction prices are updated by non-cooperative games and the homologous Rosen-Nash equilibrium points are obtained by using Nikaido-Isoda relaxation and alternating direction method of multipliers (ADMM) algorithm. The efficacy of the designed framework is demonstrated by a case study, and the results indicate the designed framework can improve the utilisation rate of renewable energy.

Isolated industrial micro-grid demand response with assembly process based on distributionally robust chance constraint

In this paper, demand response for isolated industrial micro-grid is investigated, in which the typical manufacturing assembly process, battery, conventional generator and PV generation are contained. The typical manufacturing assembly process is modelled by fully considering the coupling relationships between tasks and buffers. On the other hand, the uncertainty for PV generation is taken into account, where the data-driven distributionally robust chance constraints are designed and the error between day-ahead forecast and real-time operation is dealt with by the reserve capacity of conventional generator. In addition, the distributionally robust chance constraints and the expectation operator are reformulated as linear constraints, which can be solved by commercial solver directly. Finally, a case study using lithium-ion battery factory is presented to prove the superiority and effectiveness of the proposed model.

Statistical Methods for Detecting Recycled Electronics: From ICs to PCBs and Beyond

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Globalization of semiconductor industry has led to unprecedented challenges in design, verification, test, security and trustworthiness of contemporary electronics. With parts sourced from various suppliers across the globe, who are beyond the auspices of the original designers and system integrators, serious concerns arise regarding integrity and trustworthiness of electronic circuits, which can be compromised by malicious actors at any stage of the component manufacturing and system assembly process. Among the variety of such concerns, recycled electronics sold as new by malicious suppliers/vendors pose a key threat to mission-critical end applications such as military systems, financial institutions, transportation security, and poser distribution infrastructure. Recycled electronics may experience performance degradation due to aging and, more importantly, may have shorter-than-expected lifetime, thereby raising serious reliability and safety issues. To combat this problem, statistical methods have been proposed in the past decade as a time-efficient and cost-effective approach to identify recycled electronics sold as new. Initially demonstrating in the context of detecting recycled Integrated Circuits (ICs), such methods are based on using statistics and machine learning to outline the parametric signatures of known brand-new ICs and, thereby, weed out ICs that do not fit the expected profile. This article summarizes the current state of knowledge in recycled IC detection schemes and discusses how these methods have inspired, over time, the development of similar solutions in a plethora of domains, including identification of recycled Field Programmable Gate Arrays (FPGAs), recycled hardware components in a network, and recycled Static Random-Access Memories (SRAMs)/Flash memories</i> .

Simulation and Analysis of Welding Spot Failure of PCB Based on ABAQUS

In the manufacturing process, the welding spot of PCB may lose efficacy because of the strain and stress impact. The reason for the occurrence of high-stress zones is the effect of the load brought by the manufacturing and assembly process. It is a giant challenge for the industry community to solve the problem of welding spots losing efficacy.In this paper, the manufacturing techniques and assembly process will be analyzed first. With the analysis result, the main impact of load would be checked. Then, with the confirmed allowable stress by calculation, the value of input stress, which may cause the welding spot to lose efficacy, would be obtained. Finally, the result of this study would be confirmed by the simulation result generated by the finite element analysis software.

Evaluation of Internal Flow Path of two Module Scramjet Combustor Through Sectional Measurement

The Internal flow path of a scramjet combustor consists a gradual varying cross sectional area along the combustor axis. The performance evaluation and prediction of combustor are based on Computational Fluid Dynamics (CFD) and Structural Analysis simulations which are carried out on a designed 3D CAD model. Due to manufacturing process constraints and assembly process there can be deviation in the hardware from the designed internal flow path of combustor. Thus it is necessary to determine the actual internal flow path of combustor, which in turn can be used for CFD and structural analysis simulations for better performance evaluation and predictions. The paper presents the methodology developed for evaluation of cross-sectional areas along the combustor axis and generation of 3D surface CAD model of actual internal flow path using CNC Coordinate Measuring Machine (CMM) and design CAD software. It also includes the methods adopted for CMM probe compensation while measuring slopes on the combustor surface and for the measurement of inaccessible surfaces by Ultrasonic Thickness Measuring Instrument.

Impact of FCBGA substrate stack-up on BLR performance

Board level reliability (BLR) temperature cycling is a metric for FCBGA field performance, where it is imperative to understand process variation holistically covering both substrate and / or assembly manufacturing process and its impact to product margin. This study focuses on technical reasoning a common FCBGA design manufactured with an identical substrate material set (i.e. core, dielectric, solder mask), assembly bill-of-materials (i.e. underfill, lid, etc.) and assembly site demonstrated different cycles to first failure during BLR testing. Although results far exceeded JESD22-A104 condition G requirements, BLR performance based on identical substrate designs (manufactured at different points in time) proved TV1 (test vehicle 1) performed ~2x better than its TV2 (test vehicle 2) counterpart. To elucidate the primary factor of the disparity in BLR performance, supplier feedback as well as a detailed package construction analysis ensued to compare build-up substrate layer thickness dimensions between TV1 and TV2. Discovery demonstrated a slightly larger volume of a specific layer in the build-up stack within TV2 that generated a higher degree of out-of-plane displacement as compared to TV1. Reproducing the cycles to first failure with the superior TV1 device via the TV1a and impact of substrate warpage was investigated as a factor in the BLR findings driving root cause.

Improvement of Assembly Manufacturing Process through Value Stream Mapping and Ranked Positional Weight: An Empirical Evidence from the Defense Industry

This study aims to improve the assembly manufacturing process to solve the workload imbalances by combining value stream mapping (VSM) and ranked positional weight (RPW). An empirical study was conducted in a defense manufacturing firm located in Indonesia. The study specifically focused on 155 components and 56 tasks distributed among 43 assembly workstations in one weapon product. The results of the analysis showed a significant reduction in the total cycle time, from 5121 s (85.35 min) to 3620 s (60.33 min), or a decrease of 29%. Additionally, the study found improvements in the balance of the assembly line as measured by balance delay, line efficiency, and smoothness index performance indicators. The application of VSM and RPW in this study is unique in the context of the defense industry, as it provides empirical analysis on cycle time and assembly line balance, which is rarely studied. The results of this study contribute to the advancement of literature in the field and provide valuable insights for other organizations in the defense industry and other manufacturing industries. By improving the efficiency and balance of the weapon assembly line, this study has the potential to increase productivity and reduce waste.

Efficient Development of Applied Technology Innovation Through Design For Manufacture and Assembly

The conventional product design process and the design results from the designer need to be evaluated and optimized in terms of the manufacturing process and assembly process by the manufacturing department. In this process, it is sometimes necessary to make design changes that must be consulted with the designer to make it more efficient. This can be seen from three aspects of the product, namely quality, cost, and production time. A very applicable method to meet the needs of these 3 aspects of the product is the design method for manufacturing. One solution that can be applied is the design for manufacture and assembly (DFMA) method. DFMA is a method to evaluate the design of a product so that it can be easily assembled and manufactured. This paper will explain the application of the DFMA method to several applied technology product designs. As a case example for the application of the DFMA method, the development of a post-stroke bicycle frame from the initial design to the final design step, namely prototyping, is observed. A prototype was also evaluated with the help of the DFMA method and the evaluation results showed that the application of the DFM method provided significant improvements, where the total components of the bicycle frame at the beginning of the design were 53 pieces, in the final design could be reduced to 29 pieces (45%), with design efficiency increasing by 1.04%.

Automatic Detection of Chip Pin Defect in Semiconductor Assembly Using Vision Measurement

Abstract With the development of semiconductor assembly technology, the continuous requirement for the improvement of chip quality caused an increasing pressure on the assembly manufacturing process. The defects of chip pin had been mostly verified by manual inspection, which has low efficiency, high cost, and low reliability. In this paper, we propose a vision measurement method to detect the chip pin defects, such as the pin warping and collapse that heavily influence the quality of chip assembly. This task is performed by extracting the corner feature of the chip pins, computing the corresponding point pairs in the binocular sequence images, and reconstructing the target features of the chip. In the corner feature step, the corner detection of the pins using the gradient correlation matrices (GCM), and the feature point extraction of the chip package body surface using the crossing points of the fitting lines are introduced, respectively. After obtaining the corresponding point pairs, the feature points are utilized to reconstruct the three dimensional (3D) coordinate information in the binocular vision measurement system, and the key geometry dimension of the pins is computed, which reflects whether the quality of the chip pins is up to the standard. The proposed method is evaluated on the chip data, and the effectiveness is also verified by the comparison experiments.

Study of industry 4.0 pillars and their uses in increasing productivity and reducing logistics defects

In the view of growing interconnectivity and interdependence in the modern globalized economies, it has become essential to understand and apply the concepts of Industry 4.0. It is essentially the 4th industrial revolution Industry 4.0 applied. Modern advances in the fields of IoT, IIoT, AI, Cloud computing, Data analytics, Machine Learning, Systems Biology etc. These in turn have been supported with advances in sensors, actuators, and computerization and validated with various quality tools. A thorough understanding of all these are necessary in implementing the evolving concepts and to facilitate the same with use of various technological advancements. In this paper an effort has been made to understand these concepts. Study and application of RFID based kit call off systems is done at CNH Industrial after Paint line for increasing the productivity of the smart manufacturing assembly process.

Ontology-Based Analysis of Manufacturing Processes: Lessons Learned from the Case Study of Wire Harness Production

Effective information management is critical for the development of manufacturing processes. This paper aims to provide an overview of ontologies that can be utilized in building Industry 4.0 applications. The main contributions of the work are that it highlights ontologies that are suitable for manufacturing management and recommends the multilayer-network-based interpretation and analysis of ontology-based databases. This article not only serves as a reference for engineers and researchers on ontologies but also presents a reproducible industrial case study that describes the ontology-based model of a wire harness assembly manufacturing process.

RSOB Shorting Defect Resolution through Looping Optimization and Ball Placement at Wirebond Process

Wirebonding process is one of the most challenging assembly manufacturing process in semiconductor packaging industry. This paper discussed the wirebonding challenge and the solution to resolve the wire to die shorting on reverse stitch on ball (RSOB) and prevent irregular looping height for the substrate land grid array (LGA) device. Comprehensive parameter optimization was done particularly on the wirebond looping to ensure that no wire depression and no capillary hitting would occur wirebonding setup. Ultimately, the optimized wirebonding parameter prevented the occurrence of looping issues during the lot process. For future works, the configuration and technique could be applied on packages with similar situation.

Intelligent Matching Assembly: System Design Based on Reuse of Ultra-Difference Parts

As the industrial digitalization has been recently leaping forward, high-efficiency production processes emerge, and assembly integration technologies are being progressively developed. For high-tech industries (e.g., aerospace manufacturing), however, unprecedented challenges are imposed on the conventional assembly manufacturing process technology. To be specific, the shallow digitizing and intelligent technologies fail to satisfy the rising requirements for efficiency, pass rates and cost; in particular, the way to down-regulate the unqualified rate and assembly cost of parts production remains unclear. In the present study, an intelligent matching assembly system was designed for reapplying out-of-tolerance parts. In addition, the concept of the mating base is proposed. Next, the fit relation between parts is quantified by employing the functional expression of dimension data, and such a relation is characterized as a function constraint with a variable of dimension. Moreover, the designed intelligent matching system was introduced into the existing assembly process to reemploy a number of unqualified parts and determine the matching parts most suitable for the original unqualified parts. On that basis, the most suitable parts are enabled to be involved in the assembly activities, as an attempt to satisfy the design requirements. To efficiently find the optimal matching scheme in the database of the unqualified parts and most effectively employ the unqualified parts, a set of optimal matching algorithms are proposed, thereby significantly down-regulating the production cost. Lastly, Monte Carlo method was adopted to simulate the actual production data, and the optimal matching scheme determined by the intelligent matching system was analyzed and assessed, which verified the effectiveness and practicability of the system.

Non-Conformance Time As The Component Of Time Loss Measures In Assembly Processes

Hidden Time Loss (HTL) occurs along the production processes that have a big implication on productivity. Overall Equipment Efficiency (OEE) is one of the most popular performance measurement tool used in the production line. The HTL has been provided by quality as one of the measure components of OEE. However, OEE doesn’t really suitable in measuring operation performance of assembly processes mainly in the semi-auto assembly and the manual assembly processes. There would be the amount of HTL have occurred along the semi-auto assembly and manual assembly processes that become crucial when to achieve high product variety at the same production assembly line. Therefore, the purpose of this paper is to introduce the Non-conformance Time (NCT) as one of the part of Hidden Time Loss Measures (HTLM) in assembly processes. Literature study on manufacturing assembly processes had been used to derive the structure of NCT. Then, two selected automotive manufacturing companies had been used as a case studies in order to validate the NCT structure. Based on semi-auto and manual assembly processes, the results show that the NCT is one of the parts of HTLM.

Wirebond Process Optimization through Stitch Relocation on QFN Package

One of the most challenging assembly manufacturing process in semiconductor industry is wirebond process using a wire as direct material. With this new technology, some issues were encountered during the first trial of a quad flat no-leads (QFN) package. This paper is focused on the heal crack seen on the stitch formation during second bond. A comprehensive improvement was done by relocating the stitch formation on the second bond. Ultimately, heal crack occurrence was successfully eliminated.

Wire Shorting Elimination through Wirebond Process Optimization of Semiconductor Sensor Device

New and upcoming semiconductor devices and technologies are getting more challenging in assembly manufacturing process due to many factors such as complex package layout, process capability and critical bill of materials. This paper focused on the mitigation of the top major assembly reject of a semiconductor sensor device, that is the wire-to-wire shorting issue at wirebonding process. Parameter optimization particularly the looping segment 1 parameter, as well as using a reverse stitch on ball (RSOB) were employed to eliminate the wire-to-wire defect in wirebonding process. Finally, with the process optimization and improvement, a reduction of 98 percent wire-to-wire shorting occurrence was attained.

Grey Wolf production scheduling for the capital goods industry

The capital goods industry produces physical assets used for current and future production. Capital goods are highly customised. Production scheduling aims to synchronise material supply, component manufacturing, sub-assembly and final assembly processes to minimise the total costs of earliness and tardiness, whilst satisfying finite capacity, machining and assembly precedence constraints. This paper presents the first application of Grey Wolf Optimisation (GWO) together with modified and hybridised versions for solving the capital goods scheduling problem. A novel GWO-based production scheduling tool was developed and validated using four realistic case studies obtained from a collaborating company. The first experiment identified appropriate parameter settings for the GWO. The performance of the GWO was then evaluated and compared with a modified GWO and a hybridised GWO. The computational results obtained from the proposed methods were statistical analysed. The outperformed other metaheuristics.

Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning

Intelligent automation, including robotics, is one of the current trends in the manufacturing industry in the context of “Industry 4.0”, where cyber-physical systems control the production at automated or semi-automated factories. Robots are perfect substitutes for a skilled workforce for some repeatable, general, and strategically-important tasks. However, this transformation is not always feasible and immediate, since certain technologies do not provide the required degree of flexibility. The introduction of collaborative robots in the industry permits the combination of the advantages of manual and automated production. In some processes, it is necessary to incorporate robots from different manufacturers, thus the design of these multi-robot systems is crucial to guarantee the maximum quality and efficiency. In this context, this paper presents a novel methodology for process automation design, enhanced implementation, and real-time monitoring in operation based on creating a digital twin of the manufacturing process with an immersive virtual reality interface to be used as a virtual testbed before the physical implementation. Moreover, it can be efficiently used for operator training, real-time monitoring, and feasibility studies of future optimizations. It has been validated in a use case which provides a solution for an assembly manufacturing process.

Accurate estimation of prediction models for operator-induced defects in assembly manufacturing processes

The presence of defects in industrial manufacturing may compromise the final quality and cost of a product. Among all possible defect causes, human errors have significant effects on the performances of assembly systems. Much research has been conducted in recent years focusing on the problem of defect generation in assembly processes, considering the close connection between assembly complexity and human errors. It was observed that the relationship between the average number of defects introduced during each assembly phase and the related assembly complexity follows a power-law relationship. Accordingly, many authors proposed a data logarithmic transformation in order to linearize the mathematical model. However, as has already been discussed in literature, when the model is retransformed in the original form a significant bias may occur, leading to completely wrong predictions. In this paper, the bias due to the logarithmic transformation of models for predicting defects in assembly is analyzed and discussed. Two alternative methods are proposed and compared to overcome this drawback: the use of a bias correction factor to the retransformed fitted values and a power-law nonlinear regression model. The latter has proved to be the best approach to predict defects with few non-repeated data and affected by high variability, such as in the case under study.

Digital twin of composite assembly manufacturing process

Industry is facing the management of geometrical deviations along the entire lifecycle of the product. It is helped by digital twin tools that may minimise the geometrical deviations from nominal of products. The new digital twin tools allow to manage geometrical variations through a set of steps fully related by modern information and communication technologies that establish a continuous and unambiguous flow of information among the different steps of this digital process along the whole product lifecycle. They are based on data coming from manufacturing, assembly and inspection. The available large data sets from manufacturing and inspection allow to develop new and more accurate simulation models that realistically consider form deviations and process signature, i.e. the pattern left by the manufacturing process on the produced part surfaces. The present work introduces a digital twin tool to support the lightweight design of assemblies in composite material. It establishes a continuous and unambiguous flow of variation information from the part design to assembly, passing through manufacturing by considering the manufacturing signature. It was applied to a case study and the obtained results agree with the experimental ones.