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  • Author or Editor: Hamid Ali x
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Abstract

Over the recent years metallic foams have become a popular material due to their unique characteristics like low density coupled with beneficial mechanical properties such as good energy absorption, heat resistance, flame resistance, etc. However, their production processes (foaming) is highly stochastic which results in an inhomogeneous foam structure. Hybrid aluminum foam with closed-cell has been manufactured using direct foaming method coupled with the Taguchi Design of Experiments (DOE). Image analysis has been carried out to determine the average porous area and pore size. The influence of the production parameters (amount of foaming agent added, mixing speed and temperature) on the pore size and the porous area has been analyzed using the statistical Taguchi technique. From the experiments it was seen that the most important control factor for both the pore size and the porous area is the amount of the foaming agent added, followed by temperature and stirring speed. Furthermore, the statistical significance of these manufacturing parameters on the response was also investigated by performing analysis of variance (ANOVA) statistical method.

Open access

Abstract

Supply chain management intends to integrate supply chains' activities such as material flow, information flow and financial issues. Material flow management is the most significant issue since the inventory level in the whole supply chain could be optimized by an integrated plan. In other words, when one member of the supply chain plans to reduce its inventory level solely, despite reducing inventory in this node the inventory will be stocked in other partners' warehouses. Therefore, in this paper a new mathematical model has been developed to facilitate the process of finding the optimum solution in economic production, purchase and delivery lots and their schedules in a three-echelon supply chain environment; including raw material in suppliers, manufacturer and assembly facility as a customer. The manufacturer with a flow shop system provides its requirements from supplier, assemble multiple products, and delivers products to the customer (automotive OEM alike) on an optimum multiple delivery points. The delivery cycles would be identified through the production common cycle regarding the supply chain flexibility. Finally, a modified real-valued Genetic Algorithm (MRGA), and an Optimal Enumeration Method (OEM) are developed, and some numerical experiments have been done and compared as well.

Open access