Section outline

  • Course Duration: 30 hours


    Course objectives:

    Information technology systems can improve quality and increase productivity. In addition to software different statistical methods can be used to evaluate critical processes in order to control production procedures and performances. The course in Information Technologies for Statistical Analysis and Quality Control includes basic issues of mathematical statistics and its application for the needs of the textile and clothing industry. The training will be carried out mainly with universal and, if necessary, with specialized software products.


    Learning outcomes:
    Knowledge Skills Responsibilities/autonomy
    • To understand the basics of the quality control tools
    • To aware and understand the essentials of QFD
    • To comprehend the elements of FMEA method
    • To understand different probability distribution, parameters and properties related to textile variables
    • To apprehend how to treat random variables in order to consider them in the quality control process
    • To adopt different kind of hypothesis testing to support your decisions
    • To comprehend variance and regression analysis principles
    • To solve problems using the quality control tools
    • To respond to the needs and expectations of the customers using QFD
    • To take actions to eliminate or reduce failures using FMEA
    • To represent test results using different methods
    • To use specialised software for data analysis to support quality control
    • To apply statistical hypothesis tests in Statistical Process Control (SPC) and Acceptance Sampling (AS)
    • To apply variance and regression analysis to concrete cases both for forecasting and control purposes
    • To assure and manage the quality control process by using the quality control tools
    • To bring new and improved products to market while reducing development time
    • To documents current knowledge and actions about the risks of failures
    • To optimize the regression model in order to get to the best possible hypothesis considering data variables- To support the quality control process by applying relevant statistical models


    Syllabus:

    The course in Information Technologies for Statistical Analysis and Quality Control includes basic issues of mathematical statistics and its application for the needs of the textile and clothing industry.

    The training will be carried out mainly with universal and, if necessary, with specialized software products, through lessons:

    1. The Seven Basic Quality Control Tools

    2. The Seven Management and Planning Tools

    3. Quality function deployment (QFD)

    4. Failure modes and effects analysis (FMEA)

    7. Testing of non-parametric statistical hypothesis

    8. Testing of parametric statistical hypothesis

    10. Analysis of variance (ANOVA)

    11. Regression analysis

    12. Design of experiments