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Capability Performance Improves Productivity
December 31, 1969 |Estimated reading time: 7 minutes
SMT manufacturing equipment performance can be optimized through machine capability measurements with a significant impact on manufacturing profitability.
By Michael Sivigny
Although a quick upturn in the industry is desired, efforts will continue to cut costs and streamline manufacturing operations for the foreseeable future. Every company concerned with maintaining a strategic position in the electronics market is in search of new methods to reduce defects, improve machine utilization and ultimately improve profitability. Productivity enhancements can be achieved through statistical evaluation and optimized adjustment of SMT equipment.
Electronics assembly automation reduces process variability by minimizing the significance of human intervention. A reliance and expectation is set for SMT production equipment to run around the clock and continually produce high-quality product. Dependence on automation benefits requires machines to perform to their intended function. Whether new or used, equipment must continue to assemble product within the original quality specifications set forward by each manufacturer. Manufacturers design equipment to meet specific accuracy and repeatability specifications during operation. Quality attributes that measure machine and process performance include Cp and Cpk indices. These values, based on an operation specification, can predict theoretical defect losses.
With Six Sigma quality initiatives underway at most major corporations, the knowledge base for implementing statistical process control (SPC) in SMT manufacturing is escalating. Quality control techniques specific to electronics assembly now allow process and quality engineers to observe defect contribution at each process step. Methods to measure and reduce defects per million opportunities (DPMO) in each process using quantitative data allow the evaluation of individual processes.
Measuring and validating machine performance means executing capability studies on the desired equipment. Statistical evaluation of intended machine function is the only way to determine that a machine will perform as the manufacturer and customer expects it to. Although each manufacturer has their own verification method, customers can seek independent, objective validation services that certify equipment based on manufacturers' specifications.
Capability Analysis
It is important to have a basic understanding of statistics for capability analysis before beginning to calculate indices on equipment. A few assumptions need clarification; the first being that collected data typically are distributed under a normal distribution curve. Secondly, statistical significance is attained through adequate data measurement and collection, which allows accurate machine adjustment. Quality attributes such as standard deviation, mean value and operating specification limits are necessary for the Cp and Cpk index calculation. To reduce measurement variation, quality-certified glass plates and glass component slugs are designed and manufactured to accuracy specifications of less than 2 µm (0.00008"). A suitable measurement system must be specified and used for competent measurement of such small accuracies. The methodology behind such measurement is that solder, adhesive or component deposits are measured with relation to local targets on a glass plate. The resulting X, Y and Theta positional deviations are measured against the desired deposit location. In the case of each major process step, a measurement plan determines the layout of measurement locations. Depending on the configuration of a particular machine, the plan can be customized to exercise specific functions and completely diagnose the capability of the equipment.
Screen printers require statistical evaluation of two important machine functions. The first is to analyze its vision alignment accuracy and repeatability. A machine capability analysis (MCA) is performed to validate the machine as it works under its own load. During this type of test, the machine exercises its mechanical function in each of its vision alignment and table motion axes. Specifically, X, Y and Theta-axis motion are analyzed statistically and directly through a period of time and designated number of machine cycles. Pre-examination through diagnostic test cycles indicate current performance condition. When pre-examinations fail to meet expected results, further investigation is required to fix the problem. Once adjustments are completed, the printer is ready for a statistically significant extended-term capability test.
The second important printer evaluation is to execute a process capability analysis (PCA) that examines the machine under process load. A few variables included in print process dynamics are board clamping, squeegee force, print speed and stroke direction, where each one of these attributes can have a measurable impact on print process capability performance. PCA execution first optimizes print process parameters for printing on highly accurate glass plates using a calibrated stencil. Numerous plates are printed and stroke direction is tracked for each print. Each stroke direction is grouped statistically so that an evaluation can determine a mean displacement (offset) for each direction. As sufficient data is collected and measured, appropriate adjustments are implemented into the machine and realized in subsequent cycles. As adjustments are finished, the machine prints a specific number of plates without any parameter or setup changes, indicating its print process capability performance. Generally, the fail-safe method is to carry out MCA tests prior to same machine PCA tests because a machine could statistically pass a PCA and fail an MCA due to wider specification limits for the process test. Adhesive dispensers use a PCA technique to determine the ability of a machine to accurately dispense dots in an ASCII-generated pattern on glass plates. Process characteristics such as dot X/Y positional accuracy are measured on each dispensed plate whereas machine functions such as board location and fiducial recognition also must be considered because each can directly influence the dispenser's capability performance. Dispensers are adjusted in a similar manner to printers.
Placement machines are evaluated with PCA measurements because the machine function will be measured for capability. Although chip and QFP tests are executed in the same manner, each will use its typically intended type of component in a highly accurate package. A measurement plan specifically for placement machines can diagnose even the most complex placement machines, from systems with 24-head stationary turret style shooters to dual-axis multi-camera systems. After components are placed and measurements completed, adjustments can be implemented .
Figure 1. Dual-head placement machine with angle of rotation problem.
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Calculated standard deviations for each axis determine which type of correction is required when exhibiting a failure mode. For instance, a basic scenario yields an axis with very low standard deviation (meaning high Cp performance) but fails Cpk requirements due to a high mean displacement (deviation) result. In this particular case, the problematic axis is adjusted in a global alignment software file, which would correct for the displacement during the next test cycle. Alternatively, an axis fails Cp and Cpk specifications, yielding a high standard deviation. The problem initially indicates that the axis requires maintenance, part replacement or calibration. The X-Y Scatter Plot shown in Figure 1 is a depiction of results showing that there is an angle of rotation issue on Head 1 of this particular dual-head placement machine. The red lines indicate USL and LSL. Head 2 is clearly out of specification and requires mean displacement adjustment in the software.
Figure 2. Result of optimized placement machine adjustments.
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Figure 2 shows the result of calibration and deviation correction into the mechanical and software aspects of the machine. Adjustment into a machine does not necessarily indicate the machine is bad but that it requires optimization. Each axis must exhibit acceptable minimum Cp and Cpk values before returning to production.
Figure 3. Weekly percentage of defects from one OEM.
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A closer look can examine long-term advantages through regular maintenance and production equipment optimization. Immediately, the following advantages can be realized: Defect reduction, increased yield, minimized repair cost and time, reduced operator invention, and preventive maintenance (PM) validation before production startup. When machines are set to perform as originally intended, defects are reduced. Optimized printers align stencils and PCBs more accurately, creating fewer off-pad prints. Dispensers dispense dots in the exact intended location and not partially on pads, causing subsequent reflow defects. Placement machines operate more efficiently with reduced tombstoning, less bridging (shorts) as assisted with better printing, and decreased missing or skewed components. In Figure 3, weekly defects from an anonymous top OEM report that PCA was performed in week 39 with optimized adjustments into the equipment. The following two weeks indicate significant positive defect reduction. Minimized in-process defects have an upward spin of positive effect, specifically creating less rework, increased end of line yield and reduced customer returns. Following the defect reduction graph with a fixed number of product units, the following cost savings calculation is simply stated: 86,000 units with defects reduced by 0.007 percent yields 602 less defects. Assuming an average defect repair cost of $15 x 602 defects = $9,030 savings in a two-week period.
Conclusion
Surface mount manufacturing equipment performance can be optimized through machine capability measurements and impacts manufacturing profitability. With productivity causing such a penetrating effect on profitability, systems offering these characteristics and benefits offer a four-month return on investment.
Michael Sivigny, solutions manager and Six Sigma quality black belt, may be contacted at EAGLE-EYED ONE Sales & Service, 20 River Rd., Suite B, Hudson, NH 03051; (603) 883-7843; Fax: (603) 484-8478; E-mail: msivigny@eagle-eyed-one.com.