Course Overview

With the growth of the globalization and new opening markets, the concern of the companies to monitor the quality of the products and/or services has increased as quality becomes a decisive factor to guarantee its permanence in the market. Consequently, companies are increasingly driven to invest in the management and technologies to intensify their market competitiveness and provide an increase in the quality and cost /benefit of your products and/or services. In this scenario, statistical methods, mainly the control charts, have become an indispensable tool when they are used to monitor the quality of products and/or services. Control charts was proposed by Walter Shewhart at 30s and traditionally they have been used to monitor production process but recently been employed to monitor other types of process like service, surveillance of diseases. The control charts can be classified in different manners. They may be according to the number of quality characteristics as univariate control chart when there is a single quality characteristic of interest or multivariate control chart when more than one quality characteristic is monitored. Or according to the nature of quality characteristic we have attribute control chart (when the nature is qualitative) and variable control chart (when involves measurement). Or if the monitored statistic takes into account the previous observations (as the CUSUM type control chart or EWMA type control chart) or not (only the current observation, called Shewhart type control chart). Motivated by the increase of the number of the contributions on this subject and the relevance of this tool in the monitoring of industrial process, the new control charts and improvement in the existed ones have been continuously proposed by many researchers. The aim of this course is to present the main types of control charts and how design them adequately in order to meet desirable performance metrics.

Learning Achievement

The aim of this course is to present the main tools used to monitor statistically a process.

Competence

Course prerequisites

Grading Philosophy

The students will be required to take two tests and to present a seminar; exercises using the Free R statistic software program

Course schedule

Development of statistical concepts and theory underlying procedures used in quality control applications: error of type I and II; run length; average run length. Process improvement strategies, univariate control charts for process monitoring: Shewhart type control chart, Cumulative sum type control chart, EWMA type control chart, adaptative type control chart, multivariate process monitoring, profile monitoring, health-related surveillance, Markov chains: steady state, zero state, the use of basic time series models.

Course type

Online Course Requirement

Instructor

Linda Lee Ho, Celma de Oliveira Ribeiro

Other information

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