Printed Circuit Board Assembly Process Research Articles

A cooperative iterated greedy algorithm for the serial distributed permutation flowshop scheduling problem

This paper addresses a serial distributed permutation flowshop scheduling problem (SDPFSP) inspired by a printed circuit board assembly process that contains two production stages linked by a transportation stage, where the scheduling problem in each production stage can be seen as a distributed permutation flowshop scheduling problem (DPFSP). A sequence-based mixed-integer linear programming model is established. A solution representation consisting of two components, one component per stage, is presented and a makespan calculation method is given for the representation. Two suites of accelerations based on the insertion neighbourhood are proposed to reduce the computational complexity. A cooperative iterated greedy (CIG) algorithm is developed with two subloops, each of which optimises a component of the solution. A collaboration mechanism is used to conduct the collaboration of the two subloops effectively. Problem-specific operators including the NEH-based heuristics, destruction, reconstruction and three local search procedures, are designed. Extensive computational experiments and statistical analysis verify the validity of the model, the effectiveness of the proposed CIG algorithm and the superiority of the proposed CIG over the existing methods for solving the problem under consideration.

Federated-Learning-based Decision Support for Industrial Internet of Things (IIoT)-based Printed Circuit Board Assembly Process

Federated-Learning-based Decision Support for Industrial Internet of Things (IIoT)-based Printed Circuit Board Assembly Process

Developing Predictive Engineering Analytics to Formulate the Closed-Loop Management for Achieving Re-Industrialisation

Regarding the process of printed circuit board assembly (PCBA), existing failure location methods are reactive in nature, while process parameters and performance cannot be predicted to achieve a high level of operational excellence. Designated PCB designs are not customized for specific manufacturing sites, while process performance becomes uncertain to clients and manufacturers. In this paper, an intelligent manufacturing performance predictive framework (IMPPF) is proposed in this paper, which structures the predictive engineering analytics for the smart manufacturing. First, the data collection from the PCBA process is structured by means of multi-responses Taguchi method, which guarantees the data reliability and quality. Second, the artificial neural network is adopted to learn from the existing operational data so as to provide the prediction on machine settings and process performance at the Gerber drawing stage. The contribution of this study is mainly to establish a closed-loop framework to facilitate the predictive engineering analytics for achieving re-industrialization.

An intelligent approach for improving printed circuit board assembly process performance in smart manufacturing

The process of printed circuit board assembly (PCBA) involves several machines, such as a stencil printer, placement machine and reflow oven, to solder and assemble electronic components onto printed circuit boards (PCBs). In the production flow, some failure prevention mechanisms are deployed to ensure the designated quality of PCBA, including solder paste inspection (SPI), automated optical inspection (AOI) and in-circuit testing (ICT). However, such methods to locate the failures are reactive in nature, which may create waste and require additional effort to be spent re-manufacturing and inspecting the PCBs. Worse still, the process performance of the assembly process cannot be guaranteed at a high level. Therefore, there is a need to improve the performance of the PCBA process. To address the aforementioned challenges in the PCBA process, an intelligent assembly process improvement system (IAPIS) is proposed, which integrates the k-means clustering method and multi-response Taguchi method to formulate a pro-active approach to investigate and manage the process performance. The critical process parameters are first identified by means of k-means clustering and the selected parameters are then used to formulate a set of experimental studies by using the multi-response Taguchi method to optimize the performance of the assembly process. To validate the proposed system, a case study of an electronics manufacturer in the solder paste printing process was conducted. The contributions of this study are two-fold: (i) pressure, blade angle and speed are identified as the critical factors in the solder paste printing process; and (ii) a significant improvement in the yield performance of PCBA can be achieved as a component in the smart manufacturing.

Application of an improved Spider Monkey Optimization algorithm for component assignment problem in PCB assembly

This paper presents a new optimization method for printed circuit board assembly (PCBA) process based on improved spider monkey optimization (SMO) algorithm, and a production model for PCBA is created. The proposed method proves to be suitable for product-service system(PSS). PCBA process mainly consists of three parts. First is the assignment of PCB, second is the assignment of machines, the last is the component assignment problem. In this research, the SMO algorithm is applied on optimization of component assignment which is divided into two stages: local leader phase (LLP) and global leader phase (GLP). In the first stage, the electronic components are assigned to the feeders by GLP. In the second stage, the component placement sequence, which is apparently known as a travelling salesman problem (TSP), is determined by LLP. Numerical experiments are performed to compare the performance of SMO algorithm with others under various experimental settings, the results show that the proposed method is more effective than other traditional methods. A production model is created with the proposed method, which is calimed to be able to increase the efficiency of the product services.

Multi-Level Planning and Scheduling for Parallel PCB Assembly Lines Using Hybrid Spider Monkey Optimization Approach

Printed circuit board (PCB) assembly lines are significant to produce a variety of electronic products. PCB manufacturing industries tend to move towards automated and complex manufacturing system due to an increase in the customer demand for more sophisticated products. PCB assembly process involves highly interrelated levels of planning and scheduling problems. Therefore, the current research investigates multi-level planning and scheduling of PCB assembly lines, which include line assignment to the PCB models, component allocations to machines, and component placement sequencing by machines on PCB boards. A mixed integer-programming model is developed to integrate the planning and scheduling problem of parallel PCB assembly lines to maximize the net profit. A hybrid spider monkey optimization (HSMO) algorithm is proposed to solve the multi-level planning and scheduling problem. The performance of the proposed HSMO algorithm is compared to artificial bee colonial (ABC), genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA) algorithms. Moreover, the proposed HSMO algorithm is validated against ABC, GA, PSO, and SA algorithms with the case problem taken from well-reputed PCB manufacturing industry in China. The computation experiments indicate that the proposed HSMO algorithm can achieve good near-optimal solutions when compared with the other-mentioned four algorithms based on performance and efficiency for benchmark problems and real case problem.

Scalable Manufacturing of Solderable and Stretchable Physiologic Sensing Systems.

Methods for microfabrication of solderable and stretchable sensing systems (S4s) and a scaled production of adhesive-integrated active S4s for health monitoring are presented. S4s' excellent solderability is achieved by the sputter-deposited nickel-vanadium and gold pad metal layers and copper interconnection. The donor substrate, which is modified with "PI islands" to become selectively adhesive for the S4s, allows the heterogeneous devices to be integrated with large-area adhesives for packaging. The feasibility for S4-based health monitoring is demonstrated by developing an S4 integrated with a strain gauge and an onboard optical indication circuit. Owing to S4s' compatibility with the standard printed circuit board assembly processes, a variety of commercially available surface mount chip components, such as the wafer level chip scale packages, chip resistors, and light-emitting diodes, can be reflow-soldered onto S4s without modifications, demonstrating the versatile and modular nature of S4s. Tegaderm-integrated S4 respiration sensors are tested for robustness for cyclic deformation, maximum stretchability, durability, and biocompatibility for multiday wear time. The results of the tests and demonstration of the respiration sensing indicate that the adhesive-integrated S4s can provide end users a way for unobtrusive health monitoring.

RETRACTED ARTICLE: Solder Selection for Reflowing Large Ceramic Substrates During PCB Assembly

Large substrates are prone to warpage issues during reflow due to Coefficient of Thermal Expansion (CTE) mismatch with Printed Circuit Board (PCB) material subsequently affecting solder joint quality and reliability in the form of cracks and interface dislocations. This paper describes best solder paste alloy for reflowing larger dimension ceramic substrates during PCB assembly process to improve solder joint quality by minimizing CTE differences. Experiments have been carried out using various commercially available solder alloys for reflowing larger substrates (80 mm × 80 mm). Solder joint quality was inspected using scanning electron microscope and X-ray for multiple reflow runs using different alloy combinations. Results showed Bismuth-based solder (Bi58/Sn42) to have minimal cracking and improved CTE over other solder alloys. Advantages include reduced costs and improved reliability for applicable devices.

Balanceamento de Linha como Estratégia para Melhoria do Desempenho de Produção em uma Empresa de Artigos Eletroeletrônicos de Sergipe

Given the operational difficulties encountered in circuit board production process in a company printed electronics items in Sergipe, there is the following problem situation: how to reduce losses and increase productivity in this process? Because of this, this study aims to evaluate the efficiency of line balancing tool as a proposal for reducing losses and increasing productivity of the printed circuit board assembly process. As theoretical basis the study deals with the production and line balancing for production systems. The methodology applied was exploratory and field research. By collecting times and details of each activity performed to assemble the product, the activities were redistributed and equalized tasks in jobs. After the line balancing has been proposed new distribution of activities, showing positive results with significant gains for the process under study.

Solving Feeder Assignment and Component Sequencing Problems for Printed Circuit Board Assembly Using Particle Swarm Optimization

Printed circuit board assembly (PCBA) is a process of connecting various electronic components through printed circuit boards (PCBs). Due to the need to assemble a lot of components and PCBs at the same time, the PCBA process tends to become the bottleneck in an assembly line. Many assembly firms have thus introduced automated PCBA machines to expedite this process. However, to best operate these machines, effective PCBA planning is still required. Some nature-inspired metaheuristics such as simulated annealing and genetic algorithm (GA) have been increasingly used for the PCBA planning. Also, we find that particle swarm optimization (PSO) has never been employed to deal with the feeder assignment problem (FAP) and component sequencing problem (CSP) at the same time, though it has been regarded as a good competitor to GAs. In this paper, we developed two PSO-based approaches to deal with the two problems simultaneously for a chip shooter machine. In addition, we have conducted experiments to compare the two PSO-based approaches with two GA-based approaches. The experimental results showed that PSO2, the PSO-based approach with sigmoid functions, outperformed others in terms of assembly cycle time. The comparison with an exact approach further shows that PSO2 has a high rate to find the optimal/near-optimal solution.

Evaluation of process influences on surface chemistry of epoxy acrylate based solder mask via XPS, ToF-SIMS and contact angle measurement

Epoxy acrylate based solder mask formulations were conditioned by different printed circuit board (PCB) manufacturing and PCB assembly process stages. Depending on these different influences the chemistry of the solder mask surface was investigated regarding adhesion to possible adhesion partners. The combination of X-ray photoelectron spectrometry (XPS), time-of-flight secondary ion mass spectrometry (ToF-SIMS) and the contact angle method, for surface energy determination, provided a detailed understanding of the surface near region up to the topmost monolayer, which forms the contact zone in which adhesion takes place. The combination of ToF-SIMS and XPS provided molecular information of surface components comprising quantitative information. The influences of all process steps, like UV, chemical and thermal treatment, on the chemical surface composition and appearance were identified. Based on the results a chemical surface model could be created regarding the different adhesion mechanisms. It has been shown that an enrichment of siloxanes at the surface is generated by different mechanisms that were distinguished based on ToF-SIMS. Even though an oxidation process in the surface near region (10 nm) was indicated by XPS, no increase of the surface polar groups and thus no polarity increase could be observed within the first monolayer. A surface model derived from the analysis results shows generation and occupation of free sites at the surface through all stages of the process. An occupation of free sites by siloxanes from additives in the solder mask formulation results in a siloxane dominated topmost monolayer.

PCB Assembly Process Optimization based on Constraint Model

The structure and assembly process of Chip Shooter (CS) machine are studied. The factors of engineering practice such as the component size and machine structure etc. are considered. The assembly optimization model of Printed Circuit Board (PCB) on CS machine is formulated. A hybrid genetic algorithm (HGA) which combine with Polychromatic Sets (PS) and Genetic Algorithm (GA) is presented. A binary piece-wise coding method is proposed. In the individual chromosome, feeder arrangement and component placement sequence is described simultaneously. Constraint model is used to consider the impact of component size on the assembly speed and the feeder arrangement of CS machine. Meanwhile the constraint model improved the quality of initial population, ensured the effectiveness of GA operation and narrowed the search space of GA obviously. Calculation example indicated that HGA optimize the component sequence and feeder arrangement simultaneously and achieve excellent practicability. The assembly efficiency of CS machine is improved obviously.

Integrated Modeling and Optimization of Printed Circuit Board Assembly Process Planning and Scheduling

Aiming at the integrated optimization problem of printed circuit board(PCB) assembly process planning and scheduling,an integrated optimization model is built,and an new optimization method by combining polychromatic set(PS) with genetic algorithm(GA) is presented.On the basis of logical contour matrix and numerical contour matrix of PS,a constraint model of PCB assembly process planning and scheduling is built.which is combined with GA genetic coding,genetic operation and fitness value calculation,so as to guarantee the GA to search always in an effective solution space.The efficiency and effectiveness are improved significantly.Moreover,PS model holds unified standard form,it can help to dynamically describe various uncertain events such as machine fault and urgent order and improve the adaptability of PSGA.The calculation results indicate that PSGA can achieve the integrated optimization of PCB assembly process planning and scheduling efficiently.The completion time for PCB assembly is shorten,the delay of delivery date is reduced,and the workloads of machines are balanced.

The quadratic assignment problem in the context of the printed circuit board assembly process

The sequencing of placement and the configuration of the feeder is among the main problems involved in printed circuit board (PCB) assembly optimization. In some machine architectures, the latter problem can be formulated as the well known NP-hard quadratic assignment problem (QAP). In this study, a search is made among those metaheuristics that have recently found widespread application in order to identify a heuristic procedure that performs well with the QAP in the PCB assembly context. To this end, specific algorithms reflecting implementations of Taboo Search, Simulated Annealing and Genetic Algorithm-type metaheuristics were tested and compared using real PCB assembly data. The same set of algorithms was also tested on general QAP problems and it was observed that algorithms which performed successfully in the PCB context could perform poorly in the general situation. In the light of this, it can be concluded that ascertaining the best performing heuristic is complicated by the fact that the performance of a heuristic depends on the context of the problem, which determines the structure and relationships of problem parameters.

CAPP for Electronics Manufacturing Case Study: Fine Pitch SMT Laser Soldering

The trend to high-density packaging in surface mount assembly has highlighted inherent difficulties in the assembly line of these very fine pitch devices. A variety of defects is still common in printed circuit board assembly (PCBA) technology despite all the improvements made, and rework of PCBA is inevitable and performed manually in PCBA manufacturing floors since the cost of each component and PCB itself may be hundreds of dollars. In the last few years, the number of rework stations available on the market has grown considerably including the automated ones, but there has still been no significant reduction in the number of the defects. In electronics manufacturing, rework is defined as the activity that replaces defective components with those that are acceptable such that the populated board performs to the specifications. Increasing product complexity, decreasing component size, and using double sided boards have made rework more difficult and the economic reworking of PCBAs is one of the main problems facing PCB manufacturers. PCBA manufacturing has been relatively improved with fully automated, accurate assembly machines and the use of robots. Although significant improvement in automated rework has also been made by the author, it has been shown that the outcomes of the automated rework line have not produced a high enough level of the reliable yield percentage. The objective of this research project is to make a contribution towards this surface mount rework by creating a Computer Aided Process Planning (CAPP) system of circuit board defects so that the defects that necessitate rework operation can be detected through the electronics manufacturing assembly line. With the development of CAPP tool, the rework will be removed from the PCBA line and PCBA process parameters which cause joint level reliability problems will be troubleshot with the help of the developed system.

1105 需要同期化生産システムへの適用を目指した自律実装セル

It is called the time of cashflow management, and e-business in recent years. A customer's needs are strengthening the tendency of diversification and the formation of short time for delivery increasingly. In a manufacturing industry, curtailment of much more stock, curtailment of an overhead cost, and short time-for-delivery correspondence are required, and conversion to the production system which for that can synchronize with demand is pressing need. This paper describes synchronization of the printed circuit board assembly process which is one of the necks of the present production process.

Optimizing the performance of a surface mount placement machine

Process planning is an important and integral part of effectively operating a printed circuit board (PCB) assembly system. A PCB assembly system generally consists of different types of placement machines, testing equipment, and material handling equipment. This research develops a new solution approach to determine the component placement sequence and feeder arrangement for a turret style surface mount-placement machine often used in PCB assembly systems. This solution approach can be integrated into a process planning system to reduce assembly time and improve productivity. The algorithm consists of a construction procedure that uses a set of rules to generate an initial component placement sequence and feeder arrangement along with an improvement procedure to improve the initial solution. An industrial case study conducted at Ericsson, Inc., using a Fuji CP4-3 machine and actual PCB data, is presented to demonstrate the performance of the proposed solution approach. The solutions obtained using the proposed solution approach are compared to those obtained using state of the art PCB assembly process optimization software. For all PCBs in the case study, the proposed solution approach yielded lower placement times than the commercial software, thus generating additional valuable production capacity. This research is applicable for both researchers and practitioners in printed circuit board assembly systems.

Component Partitioning Under Demand and Capacity Uncertainty in Printed Circuit Board Assembly

This paper considers the problem of configuring a printed circuit board (PCB) assembly line experiencing uncertainty in demand and capacity. The PCB assembly process involves a single line of automatic placement machines, a variety of board types, and a number of component types. The line is set up only once, at the beginning of a production cycle, to eliminate setups between board types. Using this strategy, the line therefore can assemble all different types of PCBs without feeder changes. The problem then becomes to partition component types to the different machines in the hope of processing all boards quickly with a good workload balance. In this paper, the board demands and machine breakdowns are random but follow some probability distribution, which can be predicted from past observations of the system. We formulate this problem as a stochastic mixed-integer programming formulation with the objective of minimizing the expected makespan for assembling all PCBs during a production cycle. The results obtained indicate significant improvement over the existing methods. We hope that this research will provide more PCB assembly facilities with models and techniques to hedge against variable forecasts and capacity plans

Optimal Component Assignment and Board Grouping in Printed Circuit Board Manufacturing

We consider operation assignment problems arising from a printed circuit board assembly process. The research was inspired by an application at Hewlett Packard where hundreds of types of printed circuit boards require the insertion of a number of components. The components can be inserted manually or by semiautomated insertion machines. The machines are limited in terms of the number of different component types that they can hold. We investigate how to assign the boards and components to the machines and manual process so as to minimize cost. An optimal solution technique is developed for the single-machine case and for the multiple-machine case where boards are not allowed to be set up on more than one process. In addition, a heuristic is developed which gives near-optimal solutions (within 0.3%) with much less computational effort. Although the problem this paper specifically addresses is that of partially automated PC board assembly, the results apply to a more general set of problems. Other applications include completely automated PC board assembly, flexible manufacturing systems, and general operation assignment problems.

A profile identification system for surface mount printed circuit board assembly

Reflow soldering using InfraRed (IR) and/or convection is a popular method used to attach surface mount components to the Printed Circuit Board (PCB). The quality of the solder joints produced by reflow soldering is a function of the temperature parameters set for the operation. Identifying the appropriate thermal profile for an IR radiation/convection oven for a specific PCB assembly is a complex problem in which several variables and control parameters need to be considered. The complete understanding of the interrelationships among the various domain parameters is required to obtain high yields for the processes requiring heating (reflow soldering and/or curing) in the PCB assembly process. A knowledge based approach was used to design and implement a profile identification decision support system for the surface mount PCB assembly domain. This system can help a process engineer determine the thermal profile for reflow soldering and/or for the curing of adhesive and/or conformal coats.