Scrap production of extruded aluminum alloys by direct extrusion

• Autor(a) principal: Ferrás, A.F.
• Data de Publicação: 2019
• Outros Autores: Almeida, F. De, Silva, E. Costa e, Correia, A., Silva, F.J.G.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/15922
• topic: Aluminium Extrusion; Scrap; Extrusion Variables; Multivariate Linear Regression

The growing globalization of the different types of market requires that companies invest, in a recurrent way, to optimize and improve all the processes inherent to their activities. Aluminium extrusion is the main industrial process used to create profiles of a fixed cross-section. This process requires appropriate processing parameters to be used, in order to produce diverse profiles and high-quality products. The company’s ability to adapt and improve the productive process are differentiating factors against the competition. Thus, understand the main operations and dynamics of the companies is crucial. This work presents an empirical study concerning the extrusion process of a Portuguese company in the aluminium sector. By analysing a real data base provided by the company, the main objective is to model the aluminium extrusion process. Taking into account the variables that most influence the extrusion of different profiles, the aim is to minimize the production of scrap. First, by studying the literature in the subject, the variables that most contribute to scrap production were identified. Since the database provided by the company did not present all the variables described in literature, proxy variables were considered. Next, a multivariate linear regression model for explaining the amount of scrap taking as explanatory the identified variables was estimated. With this analysis, it was possible to identify levels of significance of the variables under study, and therefore understand how each of the variables contributes to the increase or decrease of the amount of scrap on the production of aluminium profiles. The results show that variables concerning with extrusion temperature, time, speed, pressure and die geometry are crucial to improve and control the scrap production. The obtained model will be improved, in future work, by including further variables of the extrusion process. Furthermore, factor analysis and GHML methodologies will also be considered for explaining the production of scrap and therefore improve the production process.