Handling of Customers Satisfaction and Assessment of Service Qualities on Commercial Bank of Ethiopia in Addis Ababa at East District

Banking sector in Ethiopia is dominant and it is a dense competent area.Due to this the bank managements tend to continually found the strategies that enables them to be competent in this dense competition.These strategies often focus on handling of customers satisfaction to be strongly compete and pooling more customers.Because,service quality is relevant to keep up their competitive advantage and improve customer satisfaction.So,this study examine the handling of customers satisfaction and assessment of service qualities on Commercial Bank of Ethiopia(CBE)in Addis Ababa at East District by applying SERVQUAL model.This study used convenient and random sampling technique to select the sample respondents and 400 respondents were selected branches of CBE in Addis Ababa at east district.The data sources for this study are primary and secondary data sources.The questionnaires are used as primary data source,which are contained SERVQUAL model and the agreements were measured by applying the five Likert point scales.The correlation result revealed that all dimensions of service quality have a strong and significant statistical relationship with customer satisfaction.The quality of service offered by CBE no meets with the expectation of customer(customers satisfied in somewhat quality service).So,the bank needs to reform service quality for satisfy and attract unsatisfied customers.

A Bayesian Based Process Monitoring and Fixture Fault Diagnosis Approach in the Auto Body Assembly Process

The auto body process monitoring and the root cause diagnosis based on data-driven approaches are vital ways to improve the dimension quality of sheet metal assemblies. However, during the launch time of the process mass production with an off-line measurement strategy, the traditional statistical methods are difficult to perform process control effectively. Based on the powerful abilities in information fusion, a systematic Bayesian based quality control approach is presented to solve the quality problems in condition of incomplete dataset. For the process monitoring, a Bayesian estimation method is used to give out-of-control signals in the process. With the abnormal evidence, the Bayesian network(BN) approach is employed to identify the fixture root causes. A novel BN structure and the conditional probability training methods based on process knowledge representation are proposed to obtain the diagnostic model. Furthermore, based on the diagnostic performance analysis, a case study is used to evaluate the effectiveness of the proposed approach. Results show that the Bayesian based method has a better diagnostic performance for multi-fault cases.