Title of article
May, G. and Spanos, C. (2006). Statistical Process Control. New York: NY: Wiley-IEEE Press. Pgs. 181-227.
Summary and Synopsis
Statistical Process Control is a paradigm for enhancing efficiency in the manufacturing industry, as well as other pertinent sectors where statistical averages and analysis is required. The article presents a blueprint whereby Statistical Process Control can be used to increase efficacy in the manufacturing of semiconductor components. Using the Statistical Process Control, it shows how variations in output can be corrected using charts such as the runs and shewhart to analyze the median and mean, respectively. The problem analysis and data gathering is performed using pareto charts, flow diagrams, scatter plots and other types of controls to plot the variables in a manner that is comprehensible and articulate. This Statistical Process Control when applied to the semiconductor industry provides an avenue to instigate a lean system within the organization to enhance its modus operandi and productivity.
Application to Course Content
The value of the reading is essential in providing an avenue to apply different course concepts into an industrial framework to resolve issues. The use of charts, diagrams and statistical data to effect and plot a series of variables is one of the core principle that Statistical Process Control relies on to achieve its objectives. For instance, the use of flow diagrams and pareto charts was essential in providing the reader with details on the industry’s productivity, expected solutions, barriers to industry, and methodologies for resolving issues. Additionally it provided statistical data that showed the successes and failures of different techniques employed to different problems.
The article provides a general, albeit complex presentation of data using a variety of Statistical Process Control techniques. This may be too engrossed that they seem to contradict each other and make the use of Statistical Process Control seem intricate, incomprehensible, and difficult to accomplish.