Department: Supply Chain and Information Management

Programme: Bachelor of Business Administration (Honours) in Supply Chain Management

Project Title: Determining Decision Strategies of Applying Additives Manufacturing in Automotive Supply Chain

Supervisor: Dr Helen MA

Students: CHAU Pak Chai, CHUI Shing Him, FUNG Sze Ching, IP Shing Yan Henry, TSANG Hang Ni


Additive manufacturing (AM) has been developed for 40 years in order to enhance the cost-effectiveness of the manufacturing process. Some studies mentioned hat less than 20% of manufacturing industries applying AM, however, it has various benefits. In the aerospace industry, there is a large scale of research and development regarding additive manufacturing. Boeing, Airbus, GE Aviation, and NASA are the best illustration of applying AM. For building construction, many countries like Italy, Mexico, India, etc. started to print tiny houses to solve the housing issues. In the automotive industry, Ford, Audi and Volkswagen are successful examples in using 3D-printed parts. It is believed that advanced technology in future brings advantages to the supply chain. Especially for the automotive industry, there is a potential development—this research paper aimed at evaluating the effect of applying additive manufacturing in the automotive industry. A decision-making model has been developed using Body-in-White production as a sample by considering its relevant costs on the materials, transportation and inventory. Also, the mathematical model has further broken down the costs as mentioned above into more complex components and taken the reference of related mathematical models such as the economic order quantity (EOQ) model and decision-making models for in-depth cost analysis. In recent studies, inventory and supply chain costs have been discussed and how to simplify the supply chain. Worse still, fewer researchers studied the Body-in-White process, which is an essential part of the automobile. A number of literature focused on the technology side, and this paper emphasizes the effect on the supply chain regarding additive manufacturing.

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