Design and Optimization of the Solder Jet Bonding Process in Head Gimbals Assembly Manufacturing (original) (raw)
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20100066_Design and Optimization of SJB Process in HGA Manufacturing.pdf
Solder Jet Bonding (SJB) is the most important process for bonding a circuit of a slider of a head gimbals assembly to a circuit of suspension on a drive arm in the head gimbals assembly manufacturing process. The major problem encountered in the SJB process is that production lines experienced high defective product rates, resulting in longer machine downtime and lower productivity. This in turn leads to higher production costs and to delays in shipping dates. This paper was aimed at studying factors affecting the performance of the SJB process and to determine the optimal performance settings. Based upon the Six Sigma techniques, data collection and analysis were conducted. Potential Key Process Input Variables (KPIVs) that may effect the performance of the SJB process were then explored using several Six Sigma Tools. Such tools include process mapping, cause and effect analysis, prioritization, Failure Modes, and Effects Analysis (FMEA). The control limits of the KPIVs were then set and the Design of Experiment (DOE) methodology was utilized to identify significant KPIVs. The optimal conditions for improving the performance of the SJB process at the lowest defective rate were thereafter determined using Central Composite Design (CDD). The study found that the variables significantly affecting process performance are alignments of bond height, laser focus, amount of current supplied to laser (called laser current), laser pulse width, solder ball quality, nitrogen pressure, and capillary hole diameter. Due to time and cost considerations for studying external uncontrollable variables and for experiments associated with some internal variables, three variables were selected for optimization of machine parameters using CCD. These included laser current, nitrogen pressure, and laser focus height. The optimal defective rate is 0.54%. Production costs were reduced by 45.59% by the optimal settings, achieving a savings of approximately 4.37 million US dollars per year.
This paper presents various techniques and a management approach to improve yield of the Solder Jet Bonding (SJB) process in Head Gimbals Assembly manufacturing (HGA). The SJB is the most important process for bonding a circuit of a slider of a HGA to a circuit of suspension on a drive arm in a HGA manufacturing process. The most commonly encountered problem in the SJB process is that the yield of the processes is low, resulting from failures during HGA production. The failures lead to high machine downtime and delay in product delivery. The SJB process was monitored and analyzed based upon the Six Sigma tools including a process map, cause and effect analysis, prioritization, and Failure Mode and Effect Analysis (FMEA). There are several external and internal key factors affected the performance of the SJB process. Some of those variables are known variables which can be measured and analyzed using a descriptive statistical method and the Six Sigma approach. Thereafter design of experiment and response surface optimization is employed to determine the optimal conditions for the Solder Jet Bonding in HGA production. However, some are unknown factors and are unable to detect through a statistical method. An expert review survey technique is thus applied to explore such unknown factors that affect the performance of SJB. Finally, a management policy model for SJB process was proposed to improve the performance of the SJB process in HGA manufacturing.
Laser Beam Forming: A Sustainable Manufacturing Process
Procedia Manufacturing, 2018
Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected, information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization goes beyond the traditional aim of capacity maximization, contributing also for organization's profitability and value. Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of maximization. The study of capacity optimization and costing models is an important research topic that deserves contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical model for capacity management based on different costing models (ABC and TDABC). A generic model has been developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization's value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity optimization might hide operational inefficiency.
Sensitivity Analysis of Process Parameters in Laser Deposition
2005
Zhiqiang Fan, Kaushik Phatak and Frank Liou Department of Mechanical and Aerospace Engineering, University Of Missouri–Rolla 1870 Miner Circle, Rolla, MO 65409 573-341-4603, liou@umr.edu Reviewed, accepted August 30, 2005 Abstract: In laser cladding with powder injection process, process output parameters, including melt pool temperature and melt pool dimensions, are critical for part quality. This paper uses simulation and experiments to investigate the effect of the process input parameters: laser power, powder mass flow rate, and scanning speed on the output parameters. Numerical simulations and experiments are conducted using a factorial design. The results are statistically analyzed to determine the significant factors and their interactions. The simulation results are compared to experimental results. The quantitative agreement/disagreement is discussed and further research is outlined.
Procedia Manufacturing
Additive manufacturing (AM) of laser-based technological solution is developing at an exponential rate and is stepping towards industrialisation. The value and possibilities it bring to modern design and manufacturing tasks specifically for metallic products cannot be undermined. Amongst its significant benefits are; manufacturability, materials, part quality, production and economics. In spite of the benefits, uncertainties within the processes and high investment costs deter firms from implementing and adopting this technology. As such, getting to know about the technical and economic analysis model is necessary for sustainability and competitiveness of manufacturers. Consequently, while many papers in the literature provide cost estimation models for additively manufactured parts, there does not exist a thorough indicator towards decision making. Hence, a concurrent decision tool using techno-economic analysis that helps justify the implementation of laser additive manufacturing systems, and realisation performance efficiencies is explored in this study.
Characterization of Process Efficiency Improvement in Laser Additive Manufacturing
Physics Procedia
Laser additive manufacturing (LAM) enables production of complex parts with good mechanical properties. Nevertheless, part manufacturing is still relatively slow and the process efficiency could be improved to achieve total breakthrough into series production. In this study, the process efficiency improvements via higher laser power and thicker powder layers are studied. Effect of the building parameters must be understood when increasing build rate. Track-wise and layer-wise manufacturing strategy involves different independent and dependent thermal cycles which all affect part properties. Effects of the processing parameters such as speed and power on single-track formation are examined, since the part quality depend strongly on each single-track and layer. It was concluded that heat input has important effect on the penetration depth and possibility to melt thicker powder layers. These were noticed to be crucial for improving process efficiency.
Technological particularities of laser manufacturing
MATEC Web of Conferences, 2017
The paper presents some investigations about the influence of the Nd:YAG laser welding parameters on the penetration and metal evaporation of single and dual pass weld in the case of thin sections of stainless steel sample. The metal loss during welding process was measured in order to establish the optimal values of welding parameters. The geometric size of the welded zone was measured using an SEM microscope in order to establish the correlation between the penetration and with at different values of welding parameters.
2007
While previous iNEMI projects have focused on lead free joints soldered by the use of convection reflow ovens, since 2004, only a limited number of comprehensive investigations have taken place 1,2,3 . As a result, the lead free wave soldering project was developed in order to characterize and quantify the impact caused by the transition to lead free solder on the wave process itself as well as the impact on the performance and reliability of lead free solder joints. Within the board assembly chapter of the 2007 iNEMI roadmap the technology forecast 4 continues to provide consistent data on the nature of the wave soldering landscape. The issues today continue to be led by the enduring changes in materials and their maturity combined with a significant effort to minimize cost. Alloys containing silver adversely affect cost thus pressuring assembly houses to find alternative cheaper materials. Another pressure is the complexity of board technology. This results in an overall situation where materials are pushed to the limits of their respective specifications in terms of exposure to elevated temperature for extended times. The lead free wave soldering project focused on three critical areas: Materials selection, process optimization and solder joint performance. In order to achieve these goals the project participants developed a two-phase approach. The companies supporting this project during the execution of phase I are Cisco Systems, Cookson Electronics, Delphi Corporation, Foxconn, IBM, ITW Kester, Jabil, Microsoft, Nihon Superior, Plexus, Solectron and Vitronics Soltec. The first phase of the project focused on characterizing processrelated challenges and optimization of a lead free wave soldering process for various factors including: Fluxes, alloys, and board thicknesses. Characterizing the window of opportunity for various materials specifically designed for lead free assembly and its impact on wave soldering process is based on the quantification and analysis of specific defects. The findings provide insight into the optimization of the wave soldering process for given material combinations. Confirmation of the data analysis was achieved by soldering boards utilizing the optimized parameter settings for the respective material combinations. The focus of this latter effort was to provide a data driven solution for the optimized wave soldering process which is an essential part of a robust and reproducible lead free assembly process. The goal of the iNEMI lead free wave project is to ultimately characterize solder joint performance. Phase I provides the optimized settings that result in IPC class 3 acceptable through-hole fill for specific material combinations. Phase II of the project focuses on standardizing the lead free wave assembly process based on the phase I process development and optimization so that only solder joint performance will be evaluated. The intent of phase II is to provide the electronics assembly industry with timely and statistically backed understanding of lead free wave soldered joints. In order to achieve this goal, the team designed and fabricated a test vehicle that aims to understand future assembly requirements and consequently develop new standards and best practices for lead free wave soldering assembly. The board's name is GTLO (Get the lead out!). As shown in figure 1.
Building a Quality Cost Model for Additive Manufacturing
International Journal of Engineering Applied Sciences and Technology
Additive manufacturing (AM) is the technology used to manufacture products directly by layering the material, so no special tools are needed to produce the parts. AM is favoured by the producers since it is costeffective when it is used for small production volumes, leading to ease in the customization of products. Previous attempts had been made to develop a cost model for AM. However, most of these attempts did not consider the quality cost. The model developed by Schmid and Levy was the first cost model focusing on the quality cost of AM, they found that quality cost of AM may reach up to 16% of total manufacturing cost. The current research made a further investigation on quality cost. As a result, a detailed cost model for all AM technologies was made. The developed model considered all quality aspects along the AM process chain. The developed model was then used to calculate the quality cost when building several copies of a part; it was found that quality cost was about 20% of the total manufacturing cost. The work then focused on investigating the effect of making replacements for defect parts; this investigation revealed that it was better always to make replacements than just dispose of the defects. Finally, the study recommends the study of the exact effect of applying quality control activities on the percentage of defects, so a precise prediction for the quality cost may be attained. Another recommendation is to extend the detailed cost model for all AM technologies, considering the specific variables in each one.