This Month in SMT007 Magazine—Continuous Improvement: As Simple as X = Xc – 1


Reading time ( words)

X=Xc– 1 is a conceptual equation for continuous improvement. You define X and work to reduce it by a factor of 1. This could be one work hour, one process step, one day less in a cycle, and so on. We recently met with Ronald Lasky, Ph.D., PESr. Technologist, Indium Corp. and Professor of Engineering at Dartmouth College, to discuss the concept of X=Xc – 1 and get his advice on generating enthusiasm among readers and the next generation about continuous improvement. As this discussion illustrates, many process improvements are small in scale, not yearlong, major efforts.

Nolan Johnson: Continuous improvement is not a new idea, but we would like to shine a light on the idea of “X=Xc – 1.” To do this, first, you define what X is, and then you make an action plan to reduce it by one. It could be reducing your design spins, the number of steps in your process, or the number of gates in manufacturing. It could be any approach where you can incrementally improve, take something out, and get it done with fewer steps and iterations.

Happy Holden: It’s the concept of solid base hits rather than going for the home run all the time.

Ron Lasky: It’s sort of a formulaic approach, but maybe that’s better. Continuous improvement is the essence of Lean Six Sigma. There is a term in Lean Six Sigma called DMAIC (define, measure, analyze, improve, and control), assuming you want to improve something. You define what it is that you want to improve (D). You measure where you are (M). You collect some data and analyze it (A). Then, you improve it (I), usually with a designed experiment. Once that’s all set up, you must develop a plan to control it (C). That’s statistical process control.

For example, let’s say a small mom-and-pop shop collected the data for the year 2020, and they found that at the end of the line before repair, they had 2% fallout: 2% of the boards had to be repaired. They collected the data in a Pareto chart. If they made 100,000 boards, they had about 2,000 boards that were defective, and they found that the primary defect was shorts. That was 1,200, and then the second defect was a missing component and on down the list. Usually, you would want to attack the most significant defect mode. That was shorts. They started to look at what typically causes shorts. Two-thirds of end-of-line defects can be attributed to stencil printing, so that is good place to start.

This mom-and-pop shop may hire a local college student as an intern, who has a Lean Six Sigma Green Belt, and they teach the intern about electronic assembly. The company may also have pictures of all 2,000 defects. They analyze those images and decide that the main reason they had too many shorts is that there’s too much solder paste on the pads. When the component is placed, excess solder paste spills over the pad that occasionally, when it melts, creates a solder bridge to an adjacent pad. They do some more work and decide that maybe they should make all of their stencil apertures a little tighter, or maybe they should get a different solder paste. They call their current solder paste vendor and discuss some of these issues.

To read this entire interview, which appeared in the January 2021 issue of SMT007 Magazine, click here.

Share

Print


Suggested Items

Excerpt—The Printed Circuit Assembler’s Guide to... SMT Inspection: Today, Tomorrow, and Beyond, Chapter 3

04/22/2021 | Brent Fischthal, Koh Young America
Initiatives like the IPC Connected Factory Exchange (CFX) and IPC-Hermes-9852 underpin efforts within the industry to develop standards and help create a smart factory. These M2M communication standards, guided in part by Industry 4.0, are altering the manufacturing process by improving metrics such as first pass yield and throughput by applying autonomous process adjustments.

Excerpt: The Printed Circuit Assembler’s Guide to… Smart Data, Chapter 2

04/21/2021 | Sagi Reuven and Zac Elliott, Siemens Digital Industries Software
Companies have been collecting data in large volumes. Highly varied data from manufacturing operations comes in quickly that needs to be validated, and its value prioritized so that it can be turned into something useful—transformed from big data to smart data. The amount of data available has grown exponentially into big data. Twenty years ago, a PCB work order resulted in 100 data records, megabytes of data; today, it is 10 billion records, terabytes of data. The investment in collecting this data and storing it is high. However, without a way to analyze the data, without analytics, it will not result in ROI.

A New Captive PCB Facility in the U.S.

04/19/2021 | I-Connect007 Editorial Team
Diane Maceri and Jessi Hall discuss how Schweitzer Engineering Laboratories (SEL) has been working with Alex Stepinski of GreenSource Fabrication to build their own captive PCB facility in Moscow, Idaho; the thought process behind that decision; and their involvement in the Managers Forum at IPC APEX EXPO 2021.



Copyright © 2021 I-Connect007. All rights reserved.