Determination of optimum time of dressing process using times series to the statistical process control (SPC)

Alessandra Querino da SILVA [1]

Marcelo Silva de OLIVEIRA[2]

Thelma SÁFADI2

§    ABSTRACT: Aiming an improvement of the performance in industrial processes, the manufacturing companies employ Statistical Process Control (SPC) to control the variability of the process. Thus, it is possible to intervene in the special causes that are acting in the process, improving continuously the product quality. In the manufacturer rods of shock absorbers, the rugosity is an important characteristic of the quality, which is determined by engineering specifications.The used equipment to take care of these specifications is called dressing machines "centreless". The operation of the process, break off this machines demanding, therefore, an intervention of the operator called dressing process. To proceed the adjustment from the grinding machines, the operator must determine the period of time that must command the interventions, so that they do not have nor more interventions of that the necessary number, nor less. In this work, the behavior of data from the operations system of the company TECNO was analyzed with the objective to determine was the optimum time of dressing process of such machines. As the data are auto correlated in the time, was used the methodology of times series. The optimum time of dressing process was approximately 73 minutes. This fact generates a significant reduction of the time wastefulness, efforts of the operator and the solution of pendency in the audits of norms of the quality management.

§    KEYWORDS: Statistical process control; quality management; time series

 



[1] Instituto de Agricultura e Ambiente – IAA, Universidade Federal do Amazonas - UFAM, Rua 29 de agosto, 786 CEP: 69800-000, Humaitá, AM, Brasil. E‑mail: alessandraquerino@yahoo.com.br

[2] Departamento de Ciências Exatas, Universidade Federal de Lavras - UFLA, Caixa Postal 37, CEP: 37200-000, Lavras, MG, Brasil. E‑mail: marcelo.oliveira@ufla.br / safadi@ufla.br