Total Quality Management in Education

Question: Discuss about the Total Quality Management in Education. Answer: Introduction Lego is a well-known toy manufacturer located in Billund, Denmark. Their product specially designed for the children, so to maintain the quality of the product it has to follow a strict quality management process (Lego.com, 2016). Because there are many criteria that have to be maintained, otherwise the product may be rejected. So here, to meet those criteria Lego should take the help of the C chart. C chart helps the company to control the number of nonconforming items in the product. Developing Control chart: It is mainly used to see the total number of events that occurring in a given unit of time (Sallis, 2014, p.67). It accounts for the possibility of more than one non-conformity per inspection unit and in this case, it requires the fixed sample size (Goetsch et al. 2014,p.45). The advantage of C chart is that it helps to distinguish between two items, which fails in inspection because each contains one fault. C chart will give here ten faults, which is more specific rather P chart, np chart. UCLc and LCLc values of the data: Statistically the control chart needs the control limits. So upper control limit(UCLc) and lower control limit (LCLc) is needed, here UCLc indicates maximum value that is statistically reasonable and lower limit indicates the minimum reasonable value(Wang et al 2012 p.129). There are some formula, which is needed to find UCLc and LCLc. UCLc=xÃÅ'†¦ +z x LCLc =xÃÅ'†¦ +Zx Sample Number of Defects (X-xÃÅ'†¦)=x 1 4 2.066666667 2 5 3.066666667 3 8 6.066666667 4 9 7.066666667 5 3 1.066666667 6 4 2.066666667 7 2 0.06666666667 8 1 -0.9333333333 9 1 -0.9333333333 10 2 0.06666666667 11 1 -0.9333333333 12 1 -0.9333333333 13 6 4.066666667 14 2 0.06666666667 15 1 -0.9333333333 16 0 -1.933333333 17 0 -1.933333333 18 1 -0.9333333333 19 1 -0.9333333333 20 0 -1.933333333 21 1 -0.9333333333 22 1 -0.9333333333 23 0 -1.933333333 24 1 -0.9333333333 25 1 -0.9333333333 26 0 -1.933333333 27 1 -0.9333333333 28 1 -0.9333333333 29 0 -1.933333333 30 0 -1.933333333 Total 58 0 mean 1.933333333 x 0 UCL 1.933333333 LCL 1.933333333 Table 1: Calculation for UCLc and LCLc (Source: Self-developed) Constructing the control chart and the plot of data: Figure 1: Control Chart (Source: Self-developed) Here, in the control chart there are four segment like sample, number of defect, UCLc and LCLc (Oakland, 2014, p.56). Calculation saying that it in this case there is no difference in upper control limit and lower control limit so in the companys control chart the UCLc and LCLc are coincide with each other. Here company cannot able to show differently UCLc and LCLc. Whatever C chart here is using to find out the defect item in the product (Gimenez-Espin, 2013, p.692). Developing recommendations According to the C chart, now the companys UCLc and LCLc are same but here in the data must be some error so this type of disaster is happening. Now to resolve this problem the company should check the data. C chart is very much important to control the quality of the product so the company must be conscious while providing the data. If the company follow this C chart then the company cannot find out the properly defect item and the nonconforming items will not be able to achieve the criteria. The product will be rejected then and the quality of the product will be declined. Figure 2: Control Chart (Source: Self-developed) Here in this C chart the control process is going on as here the upper limit control and the lower limit control are different so it will helpful for the company. LEGO can take the help from this Control chart to meet the criteria of rejection. It will be helpful for the company to identify the nonconforming item of the product (Talib et al. 2013, p.318). Every fifth product is inspected in case of control chart process. This control chart is showing that particular process so it will be too much helpful to control the quality of the product (Benavides-Velasco et al. 2014, p.87). The first control chart faces some disaster because there may be some error in the provided data. Therefore, the company should carefully check the data before applying the control chart process. The company check the data through the over viewing the defected items. As the control chart is the most authentic process so there is no error in the control chart process. To make the control chart process error free the company should identify the error of data. The second control chart may be better because there the difference between upper control limit and lower control limit so company may follow the second control chart and it will help the company to find out the appropriate defected item of the product. This second control chart may help the company to control the quality of the product properly rather first control chart. There in the data where the sample and the defected item is given there may be some errors. Error can happen because of the adaption of wrong process of collection. As in the data some defected items are missing for some sample (Ellis, 2014, p.45). The company should careful about that the samples may have the defected items, which is not identified. Another thing can happen that some samples have one defective item, which can have more defected item. Conclusion: Based on this analysis to make a fresh control chart the company should follow the careful process. The company should check that all the sample carefully and confirm that all samples have defected item or not. If the entire sample does not consist with error then recheck process will be preceded. In order to maintain the quality of the product an error free control chart is needed so to make a error free control chart the company should be careful about the process. Reference List Benavides-Velasco, C.A., Quintana-Garca, C. and Marchante-Lara, M., (2014). Total quality management, corporate social responsibility and performance in the hotel industry. International Journal of Hospitality Management, 41, pp.77-87. Ellis, R.,( 2014). Quality Assurance for University Teaching.Pearson Gimenez-Espin, J.A., Jimnez-Jimnez, D. and Martnez-Costa, M., (2013). Organizational culture for total quality management. Total Quality Management Business Excellence, 24(5-6), pp.678-692. Goetsch, D.L. and Davis, S.B., (2014). Quality management for organizational excellence. Pearson. Lego.com. (2016).About Us - About Us LEGO.com. Available at: https://www.lego.com/en-us/aboutus [Accessed on 3 Aug. 2016]. Oakland, J.S., (2014). Total quality management and operational excellence: text with cases. Routledge. Sallis, E., (2014). Total quality management in education. Routledge. Talib, F., Rahman, Z. and Qureshi, M.N., (2013). An empirical investigation of relationship between total quality management practices and quality performance in Indian service companies. International Journal of Quality Reliability Management, 30(3), pp.280-318. Wang, C.H., Chen, K.Y. and Chen, S.C., (2012). Total quality management, market orientation and hotel performance: The moderating effects of external environmental factors. 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