Discussing The Manufacturing Industry Process Improvement With Seven Quality Control Tools

Quality control benchmark to improve education quality

Question:

Discuss About The Manufacturing Industry Process Improvement?

A particular measuring scale must be used that determines the quality of education provided by the schools. The knowledge absorption level of each student needs to be evaluated for his or her benefit as well as for the benefit of the schools. Every student is unique and the structure of the education must be centred on that concept. However, each teacher has his or her own teaching style and ability. The education structure must not put a limitation on that. The purpose of this report is to develop some quality control benchmark by studying the seven quality control tools. These tools will facilitate the development of a continuous improvement plan that could be utilized to improve the quality of education. This report contains elaborations on seven basic quality control tools, their descriptions and the two best tools among those that can be used to accomplish the expected goal. A well-structured improvement plan is also provided in this report along with a detailed implementation plan.

David can use Root Cause Analysis for cause determination of the problems associated with the quality of education (Geerling, Chernofsky and Pratt 2014). This type of analysis can be used to determine the primary cause or the root cause associated with a problem. The cause is termed as root if the removal of the cause would solve the problem associated with the case (Raghavan 2015). David must evaluate the process and not just the people. This technique will help David to identify the flaws underlying the process where the students rates the performance of the teachers and the absence of any student attendance database.

Seven quality control tools can be used to determine, assess and analyse the different quality control scenarios.

Cause-and-effect diagram: This diagram is primarily used for product designing and prevention of any defect in the manufactured products. The causes are generally categorized into different groups that would aid in identifying and classifying different sources of cause variation (Dirnagl 2016). Categorising causes means that their identification is simplified in the event of any problem occurrence. The cause-and effect diagram is also known as fishbone diagram due to the utilization of the categorising concept.

Check Sheet: Real-time data is collected at the data generating location in this scenario. The collected data can be either qualitative or quantitative (Sharma and Suri 2017). The person collecting the data, the collected data, the place and time of data collection and the reason for data collection are all implicated in the check sheet. The sheet is also known as tally sheet if it contains only quantitative data. The check sheet can be used to identify defects and understand the source of their occurrence by identifying the causes. Every problems and their respective causes are marked on the sheet and at the end of the assessment, the problem with the most marks are evaluated with the most priority.

The role of root cause analysis in determining the quality of education

Control Chart: It is a type of chart where a graph is created based on the statistical findings where a chart is developed based on the process and the behaviour values (Magar and Shinde 2014). This tool can be used to determine and control any business or manufacturing process. Standard deviation is calculated using the data collected. The deviation would show any abnormality in the production or business process. This information can then be used to implement different methods that would help to control the operations and the processes.

Histogram: This is a bar graph that helps to visualize the collected numerical data. A histogram is basically used for plotting continuous data (Arnold and Tilton 2015). Such graphs can be used to give precise reflection upon the data collected. The flaws in the processes can be rectified based on the data collected.

Pareto Chart: This chart is a combination of a bar graph and a line graph. A Pareto chart can be used to specify the most common set of factors in quality control (Magar and Shinde 2014). The defects that occurs most commonly are identified and then the cause that primarily causes these defects. The causes are stated in decreasing order to show the defect that is commonly encountered. Since more than two graphs and three axes are used together to demonstrate the data, various aspects can be covered that could be utilized to analyse any number of flaws and their sources.

Scatter Plot: A scatter plot can be used to map out data that is related either to one independent variable or between two independent variables. The data is seen as positively correlated if the dot pattern starts at the lower left side of the graph and ends at the higher right side (Manly and Alberto 2016). The data is seen as negatively correlated if the pattern of the dots starts at the upper left side and slopes down to the lower right side of the graph. This type of plot is generally used for quality control when the collected data has a non-linear relationship between them.

Stratified Sampling: This type of quality control tool can be used where one sample is divided into multiple mutually exclusive homogeneous subgroups. Such a tool is used for population estimation (Jing, Tian and Huang 2015).

A histogram can be used to analyse and evaluate the ratings given by the students to their teachers. As discussed, a histogram can be used to gather a huge collection of data. The data gathered from the students can then be used to determine the root cause of the problem (Latino, Latino and Latino 2016). The teachers must be interviewed separately to determine the authenticity of the collected data. The data collected through this technique must be anonymous in nature and should never be revealed by the school management under any circumstances.

Seven basic quality control tools and their descriptions

A Pareto Chart can be used to collect attendance information and examine the results of the analysis. The chart, as discussed, can depict attendance information in the line graph and the reasons for absence can be depicted in the bar graph. The most common reason can be viewed and a precise solution can be provided depending on the scenario and the reason of absence.

A continuous improvement plan is thus given in this section of the report that would help David to improve on the flaws of the school system.

Organizational Approval:

• The key stakeholders are identified (Lawrence and Weber 2014).
• They are presented with the ideas of quality control and the need for the application of the quality control tools.
• Approval of the implementation plan.

Committee Development:

• David and some members from the management body of the school who would process.

Data Needed:

• The feedback of the students regarding their teachers.
• The attendance of the students.

Review Plan:

• Analysing the collected data and preparing the solution based on the sole discretion of the committee members.
• Positive result must be ensured. In case of any unfavourable results, the process can be scrutinized for execution errors (Soeanu 2016).

The difficulties that might be faced during the implementation of the proposed plan:

• Teachers have a strong influence on students especially those belonging to the junior classes. They can easily manipulate the feedback process. Some of the teachers might raise objections against the anonymous feedback process. Getting bad reviews would mean that their appraisals might be hindered and even their promotion in some cases.
• The individual teacher interview process follows the feedback system. This interview process is time consuming and thus some teachers might view it as a waste of time.
• The documented attendance system would mean that the students would not be able take any unauthorized leave of absence. The student and their respective parents might find that a problem and can create objections during the plan implementation process.

The proposed continuous improvement plan would significantly benefit the school and its students in the long term. The benefits are as follows:

The anonymous feedback system would help to improve the performance of the teachers significantly. The teachers would not be able to manipulate the feedback of the students. All the feedback would be accurate. The students would feel at ease while giving the reviews as it is anonymous. This would drive the teachers to provide quality education to the students (Southerland, Gadsden and Herrington 2014). Any form of incentive to manipulate the feedback process is pointless, as the management would never share the details of the review. The students might or might not give positive feedback even after receiving the incentive. The interview process after the feedback system would also be beneficial as the teachers would be able to state justification to any bad feedback from the students. There can also be times where the student might give false bad review. This can be easily highlighted and scrutinized in the interview process. The student can even be penalized depending on the severity of the false review. Quality control in the education sector is of prime importance and an efficient review system would definitely help to boost the system.

A documented attendance system would also be productive for the school system. The students would be punctual and would not be absent without any authentic reason. Regular attendance by the students would mean that they would not be missing any important lectures. Thus, the quality of the education is improved too. The students are involved in continuous lectures in sequence and thus their understanding of the subjects improve drastically.

Conclusion

Thus, it can be concluded that the concerns of David regarding the school education system is justified. The quality of education has been gradually going downhill due to lack of teacher-student involvement and enthusiasm for the process. The teachers are not motivated enough to provide the sufficient quality of education. Thus, they fail to motivate the students to be interested in the education process. Due to this, the students lose interest in coming to schools and get the fundamental education needed. The continuous improvement plan discussed in the report would definitely help to improve the education quality. However, it is a long-term process and must be treated as one. The implementation plan also included in the report would be helpful in applying the improvement plan. The problems that might be faced by the school committee while implementing the quality control plans is provided in the report. The report finally concludes with the long-term benefits of the implemented plans and the gradual improvement in education quality. 

Reference List

Arnold, T. and Tilton, L., 2015. EDA I: Continuous and Categorical Data. In Humanities Data in R (pp. 25-46). Springer International Publishing.

Dirnagl, U., 2016. Quality Control and Standard Operating Procedures. Rodent Models of Stroke, pp.291-300.

Geerling, J., Chernofsky, M. and Pratt, S.D., 2014. Root Cause Analysis. ASA Newsletter, 78(6), pp.46-49.

Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B., Vehtari, A. and Rubin, D.B., 2014. Bayesian data analysis (Vol. 2). Boca Raton,

Jing, L., Tian, K. and Huang, J.Z., 2015. Stratified feature sampling method for ensemble clustering of high dimensional data. Pattern Recognition, 48(11), pp.3688-3702.

Latino, R.J., Latino, K.C. and Latino, M.A., 2016. Root cause analysis: improving performance for bottom-line results. CRC press.

Lawrence, A.T. and Weber, J., 2014. Business and society: Stakeholders, ethics, public policy. Tata McGraw-Hill Education.

Magar, V.M. and Shinde, V.B., 2014. Application of 7 Quality Control (7 QC) Tools for Continuous Improvement of Manufacturing Processes. International Journal of Engineering Research and General Science, 2(4), pp.364-371.

Magar, V.M. and Shinde, V.B., 2014. Application of 7 Quality Control (7 QC) Tools for Continuous Improvement of Manufacturing Processes. International Journal of Engineering Research and General Science, 2(4), pp.364-371.

Manly, B.F. and Alberto, J.A.N., 2016. Multivariate statistical methods: a primer. CRC Press.

Raghavan, A., 2015. Root cause analysis. In Management and Leadership–A Guide for Clinical Professionals (pp. 105-121). Springer International Publishing.

Sharma, H. and Suri, N.M., 2017. Implementation of Quality Control Tools and Techniques in Manufacturing Industry for Process Improvement. Work, 4(05).

Soeanu, A., Debbabi, M., Allouche, M., Bélanger, M. and Léchevin, N., 2016. Hierarchy aware distributed plan execution monitoring. Expert Systems with Applications, 43, pp.66-81.

Southerland, S.A., Gadsden, V.L. and Herrington, C.D., 2014. Editors’ introduction: What should count as quality education research? Continuing the discussion. Educational Researcher, 43(1), pp.7-8.

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