Abstract

During the past few years, statistical process control and experiment design concepts have taken a prominent place within the industry. The use of such tools within the Motorola, GEG manufacturing environment, has grown to the point where reflow and wave solder process development and optimisation has significantly benefited. The ability to evaluate statistically and model various known and unknown phenomena has provided GEG's manufacturing technology with a series of very powerful tools to aid in process control and development. The primary purpose of this paper is to present the various approaches used by GEG to implement the previously mentioned statistical tools, with respect to the development of infra‐red (I‐R) reflow solder processes and enhancement of certain quality characteristics associated with wave soldered printed wiring boards (PWBs). Beyond specific GEG applications, the paper discusses the role of statistically designed experiments and process control methods as a vehicle for providing answers to complex manufacturing problems. In addition, a discussion of the mathematical and graphical methods underlying the interpretation of quantitative data is presented. Perhaps the most important benefit derived from the use of statistics to solve manufacturing and quality problems is related to decision making. When experiments are conducted to isolate unwanted sources of process and product variation, decisions must be made to determine whether or not certain experimental effects are important. Through the application of statistics, the researcher can ascertain the mathematical probability associated with the random chance occurrence of various experimental effects. With this knowledge, the researcher can make decisions with known degrees of risk and confidence. Without such knowledge, an organisation might possibly expend valuable resources and derive no direct benefit. Ultimately, the principal reason for applying statistical methods and procedures is to increase quality and yield, while simultaneously reducing costs.

Full Text
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