@phdthesis{,
    author = {Vijayakumar, Vijesh},
    title = {Development of a Quality Management System for a Semiconductor Research Institute},
    editor = {},
    booktitle = {},
    series = {},
    journal = {},
    address = {},
    publisher = {},
    edition = {},
    year = {2015},
    isbn = {},
    volume = {},
    number =  {},
    pages = {},
    url = {},
    doi = {},
    keywords = {Quality management, SPC, DOE, Cornerstone, Content management system, Plone},
    abstract = {Manufacturing processes in semiconductor industries are performed on a large scale to keep the production cost of every manufactured chip as low as possible. Process parameters are seldom varied when manufacturing is performed on a large scale. However, the situation is different in a semiconductor research institute wherein multiple processes are performed simultaneously, which require frequent changes in the process parameters and operating conditions. Due to continuous changes in the process parameters, higher variability in the output can be observed. The goal of this thesis is to develop a quality management system (QMS) to reduce the variations in the output and hence improve the overall quality of the manufactured devices at research institutes. This QMS consists of a content management system to store and organize the equipment and process data of the institute. It also consists of experimental design and data analysis systems that are essential to make a fully functional QMS for a research institute. The efficient usage of the components of the QMS helped to improve the processes performed at the Institute for physics (EIT2) at UniBw. The content management system improved the organization of the data associated with the maintenance history of the equipment and infrastructural issues concerning the laboratories and cleanrooms. Design Of Experiments (DOE) techniques were used to systematically vary the input factors to obtain the necessary output. DOE helped to predict the input parameters for a user defined output value prior to performing the actual test on the equipment resulting in a reduction of variability for the actual experiment. The data analysis tool provided the information regarding the reliability of the equipment and presented the guidelines to follow while making changes to the process parameters for performing the experiment. Usage of the data analysis tool ensured that the output variations are minimized even with frequent changes in process parameters. The experimental results for processes performed at EIT2 before and after the implementation of the QMS were compared. It was observed at EIT2 that using a QMS helped to reduce the variability and continuously improve the process quality.},
    note = {},
    
    school = {Universität der Bundeswehr München},
    
}