Statistical Process Control whilst primarily a manufacturing quality Essay

Statistical Process Control whilst primarily a manufacturing tonicity technique can be usefully applied in service industries - Essay ExampleAccording to above lines, delivery of service is being compared in context to expectation of customers and contrariety of expected service quality from delivered quality creates the gap. Ladhari (2009) stated that four characteristics of service standardized intangibility, heterogeneity, perishability and inseparability make it different from manufacturing offering. . Markovic (2006) argued that manufacturing domain should not be compared with service sector because customers might act as co-producer in service delivery surgical procedure while customer involvement is negligent in manufacturing process. In such context, caravansary (2003) stated that intangibility and inseparability make it difficult to control service quality while there are statistical procedures available to manage quality of manufacturing process. In such context, Chak rabarty and Tan (2007) found that unlike the manufacturing sector, it took time for service sector to realize the importance of Statistical Process Control (SPC) in managing quality. Sulek (2004) argued that most of the communal statistical control mechanism can also be used in service sector to manage quality but little position recalibration of the statistical model is needed in order to utilize it accu localize manner in service environment. Discussion Six Sigma & Control Chart Antony (2006) delimitate the term Sigma as the expiration from service performance characteristics mean while objective of deploying Six Sigma in service sector is to reduce the scope of transmutation and subsequently improve quality. In order to control variation in the service performance, specific control limit is being assigned (SLupper). Aim of the service performance would be not to cross the upper control limit or the maximum tolerance zone (Yilmaz and Chatterjee, 2000). In case of Six Sigma, aloofness between SLupper and service process mean is equal to six standard deviations and in this way term Six Sigma has been arrived. In case of six sigma process, deviation in service performance caused by external uncontrollable influences would not exceed the limit of 3.4 parts per million or 3.4 times the service process will show defect out of 1 million times (Antony, 2006). Antony (2006) and Hoerl (2001) stated that Six Sigma process can be applied to service processes like order entry, invoicing, shipping, baggage handling, payroll processing etc. On the other hand, Yilmaz and Chatterjee (2000) measured that defect rate in service sector is less than 3.5 sigma quality level which means 23,000 times the service process will show defect out of 1 million times. In such context, applying Six Sigma as SPC would improve the service performance level to 99.38 per cent. Hoerl and Snee (2002 and 2003) identified benefits of deploying Six Sigma in service sector as 1- decrease in ser vice defect rate which would automatically increase cost efficiency in the service process, 2- management decision would be guided by data driven statistical abstract which would decrease the scope of assumption bases errors and 3- decrease in service defect would significantly decrease customer complaints. Some practical examples can be cited in order to highlight usefulness of Six Sigma model in service sectors. Table 1 Practical Evidences of Implementation of Six Sigma in Service presidential terms Organization Benefits J P Morgan Chase (Global Investment Banking) Applying Six Sigma model has helped the company to reduce flaws in service delivery