An unsuitable industrial process parameters setting can cause many product defects and unstable product quality during the process. In literature many works determine the optimal process parameters settings for a production process in which the response variables are measured considering a quantitative and continuous scale. In this paper the authors use design of experiment in order to optimize control parameters for production process considering attribute responses. The paper combines engineering and statistics to provide improvement in cost and quality. This is accomplished by optimizing process design. The parameters are balanced against each other to provide a optimum where the process will be robust with no defects. The case study is relating to plastic injection molding that is one of the most complex manufacturing processes due to the strong nonlinearities, even though numerous people regard it as a simple and common manufacturing process.
Cesarotti, V., DI SILVIO, B., Introna, V. (2008). Optimizing control parameters of industrial processes with attribute response through Design Of Experiments: a case study of an injection molding process. In Proceedings of the 10th International Conference on The Modern Information Technology in the Innovation Processes of the Industrial Enterprises (MITIP 2008) (pp.32-37). Prague (Czech republique) : Jan Hán, Pavla Holejšovská.
Optimizing control parameters of industrial processes with attribute response through Design Of Experiments: a case study of an injection molding process
CESAROTTI, VITTORIO;DI SILVIO, BRUNA;INTRONA, VITO
2008-11-01
Abstract
An unsuitable industrial process parameters setting can cause many product defects and unstable product quality during the process. In literature many works determine the optimal process parameters settings for a production process in which the response variables are measured considering a quantitative and continuous scale. In this paper the authors use design of experiment in order to optimize control parameters for production process considering attribute responses. The paper combines engineering and statistics to provide improvement in cost and quality. This is accomplished by optimizing process design. The parameters are balanced against each other to provide a optimum where the process will be robust with no defects. The case study is relating to plastic injection molding that is one of the most complex manufacturing processes due to the strong nonlinearities, even though numerous people regard it as a simple and common manufacturing process.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
