A.There are different rationales for using SPC, including control variation, con

Question

A.There are different rationales for using SPC, including control variation, continual improvement, predictability of processes, elimination of waste, and product inspection. Discuss the importance of these rationales.


B.An organization has decided to evaluate how two different computer programs are being accepted by the market and how they are used for businesses. Based on this evaluation, the organization will determine which product will be manufactured and which product will no longer be manufactured. Discuss how the various rationales of SPC can be used to analyze and solve this business problem.

Explanation / Answer

Statistical process control (SPC) is the application of statistical methods to the monitoring and control of a process to ensure that it operates at its full potential to produce conforming product. Under SPC, a process behaves predictably to produce as much conforming product as possible with the least possible waste. While SPC has been applied most frequently to controlling manufacturing lines, it applies equally well to any process with a measurable output. Key tools in SPC are control charts, a focus on continuous improvement and designed experiments. Much of the power of SPC lies in the ability to examine a process and the sources of variation in that process using tools that give weight to objective analysis over subjective opinions and that allow the strength of each source to be determined numerically. Variations in the process that may affect the quality of the end product or service can be detected and corrected, thus reducing waste as well as the likelihood that problems will be passed on to the customer. With its emphasis on early detection and prevention of problems, SPC has a distinct advantage over other quality methods, such as inspection, that apply resources to detecting and correcting problems after they have occurred. In addition to reducing waste, SPC can lead to a reduction in the time required to produce the product or service from end to end. This is partially due to a diminished likelihood that the final product will have to be reworked, but it may also result from using SPC data to identify bottlenecks, wait times, and other sources of delays within the process. Process cycle time reductions coupled with improvements in yield have made SPC a valuable tool from both a cost reduction and a customer satisfaction standpoint. n mass-manufacturing, the quality of the finished article was traditionally achieved through post-manufacturing inspection of the product; accepting or rejecting each article (or samples from a production lot) based on how well it met its design specifications. In contrast, Statistical Process Control uses statistical tools to observe the performance of the production process in order to predict significant deviations that may later result in rejected product. A main concept is that, for any measurable process characteristic, the notion that causes of variation can be separated into two distinct classes: 1) Normal (sometimes also referred to as common or chance) causes of variation and 2) assignable (sometimes also referred to as special) causes of variation. The idea is that most processes have many causes of variation, most of them are minor, can be ignored, and if we can only identify the few dominant causes, then we can focus our resources on those. SPC allows us to detect when the few dominant causes of variation are present. If the dominant (assignable) causes of variation can be detected, potentially they can be identified and removed. Once removed, the process is said to be stable, which means that its resulting variation can be expected to stay within a known set of limits, at least until another assignable cause of variation is introduced. For example, a breakfast cereal packaging line may be designed to fill each cereal box with 500 grams of product, but some boxes will have slightly more than 500 grams, and some will have slightly less, in accordance with a distribution of net weights. If the production process, its inputs, or its environment changes (for example, the machines doing the manufacture begin to wear) this distribution can change. For example, as its cams and pulleys wear out, the cereal filling machine may start putting more cereal into each box than specified. If this change is allowed to continue unchecked, more and more product will be produced that fall outside the tolerances of the manufacturer or consumer, resulting in waste. While in this case, the waste is in the form of "free" product for the consumer, typically waste consists of rework or scrap. By observing at the right time what happened in the process that led to a change, the quality engineer or any member of the team responsible for the production line can troubleshoot the root cause of the variation that has crept in to the process and correct the problem check the details:- http://goldpractice.thedacs.com/practices/spc/index.php http://www.moresteam.com/toolbox/statistical-process-control-spc.cfm

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