Ford Motor Company was simultaneously manufacturing a car model with transmissions made in Japan and the United States - Essay Example

Download file to see previous pages With the advent of software applications the SPC is now simpler to implement. Concept: To understand the concept behind the technique of Statistical Process Control, it is necessary to revise some basics of normal distribution and approximate confidence intervals. SPC specifically addresses the processes that exhibit natural variations. These variations are also called as common cause variations. These variations when plotted on a graph as data points represent a bell-shaped curve distribution which is known as Normal Distribution sometimes referred to as natural distribution. Some of the examples of normally distributed data are heights of people or weights of people. According to the same concept; any data which is bell shaped symmetrical in nature and has a tendency to follow the Normal Distribution usually approximately follows the following set of theorems: 1- That approximately 68% observations shall be covered within one standard deviation around its arithmetic mean. i.e. µ±? 2- That approximately 95% observations shall be covered within two standard deviations around its arithmetic mean. i.e. µ±2? 3- That approximately 99.98% observations shall be covered within three standard deviations around its arithmetic mean. i.e. ...
Statistical Process Controls enables the users to frame the correct and incorrect variations in a process. Based on the above mentioned concepts; we can create a process monitoring system which can assure us to observe the whole process running under two tolerance limits namely upper control limit and lower control limit. These limits are obtained by the same concept of approximate confidence intervals. So after setting the limits (which are also termed as pre-alarm) we can run the process and monitor each observation through a Process Control Chart. Therefore we can set the following definition of SPC: Statistical Process Control is a process that uses statistical concepts based Control Charts to analyze and monitor the behaviors of processes by assessing the variations in them. The main strength of Statistical Process Control lies within its Control Charts which furnish an easy and simple way to conclude whether the variations in a process are in the controlled limits or not. These charts are simple time based graphical representations of data that is related to a process. On an x-y axis graph, the time is generally represented on x-axis. The data points plotted are usually the individual readings, averages of subgroups or values representing ranges. There are additional horizontal lines used to represent the control limits. Multiple types of control charts are used to serve their respective purposes. Control charts are used not only to monitor the performance of a process but they can also help identify the factors that hamper the process’s peak performance. The output variance over time is considered out of control when it crosses the specific control limits that represent the normal levels of variations. The control limits are ...Download file to see next pagesRead More