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The study investigates the impact of build orientation policies on the production time in additive manufacturing (AM) for mass customisation business models. Two main orientation policies are considered: (1) Laying Policy (LP) that focuses on reducing the height of parts; and (2) Standing Policy (SP) that aims to minimise the projection base plane of parts to reduce the number of jobs. While LP minimises the build time per job since parts have low height, it could increase the total completion time as the number of parts increases. On the other hand, SP takes longer build time per job due to the high height of parts, where it could lead to a fewer number of jobs. Several numerical experiments have been conducted based on Stereolithography (SLA). The results show that, when the number of parts is experimentally about 40, SP could be more preferred than LP for minimising the completion time where the shape tendency of parts is likely to affect the extent of preference for the policies. When 40 parts with long and flat shape are considered, SP reduces the completion time by 15.7% over the default policy, the initial orientation of a part, while LP reduces by only 6.6%.
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Production Planning for Mass Customization in Additive Manufacturing: Build Orientation Determination, 2D Packing, and Scheduling
The efficient production planning of Additively Manufactured (AM) parts is a key point for industry-scale adoption of AM. This study develops an AM-based production plan for the case of manufacturing a significant number of parts with different shapes and sizes by multiple machines with the ultimate purpose of reducing the cycle time. The proposed AM-based production planning includes three main steps: (1) determination of build orientation; (2) 2D packing of parts within the limited workspace of AM machines; and (3) scheduling parts on multiple AM machines. For making decision about build orientation, two main policies are considered: (1) laying policy in which the focus is on reducing the height of parts; and (2) standing policy which aims at minimizing the projection area on the tray to reduce the number of jobs. A heuristic algorithm is suggested to solve 2D packing and scheduling problems. A numerical example is conducted to identify which policy is more preferred in terms of cycle time. As a result, the standing policy is more preferred than the laying policy as the number of parts increases. In the case of testing 3,000 parts, the cycle time of standing policy is about 6% shorter than laying policy.
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- Award ID(s):
- 1727190
- PAR ID:
- 10071641
- Date Published:
- Journal Name:
- Proceedings of the ASME 2018 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2018 August 26-29, 2018, Quebec, Canada
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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