Personalized design of part orientation in additive manufacturing. Issue 10 (11th November 2019)

• Record Type: Journal Article
• Authors: Yu, Cong; Qie, LongFei; Jing, ShiKai; Yan, Yan
• Is Part Of: Rapid prototyping journal. Volume 25:Issue 10(2019)
• Page Start: 1647
• Page End: 1660
• Publication Date: 2019-11-11
• Subjects: Decision-making -- TOPSIS -- Additive manufacturing -- Feedback control -- PID controller -- Orientation determination; Engineering design -- Periodicals; 620.004205
• DOI: 10.1108/RPJ-12-2018-0309
• Languages: English
• ISSNs: 1355-2546

Abstract

Abstract : Purpose: Orientation determination is an essential planning task in additive manufacturing (AM) because it directly affects the part quality, build time, geometric tolerance, fabrication cost, etc. This paper aims to propose a negative feedback decision-making (NFDM) model to realize the personalized design of part orientation in AM process. Design/methodology/approach: NFDM model is constructed by integrating two sub-models: proportional–integral–derivative (PID) negative feedback control model and technique for order preference by similarity to an ideal solution (TOPSIS) decision-making model. With NFDM model, a desired target is first specified by the user. Then, the TOPSIS decision model calculates the "score" for the current part orientation. TOPSIS decision model is modified for ease of control. Finally, the PID controller automatically rotates the part based on the error between the user-specified target and the calculated "score". Part orientation adjustment is completed when the error is eliminated. Five factors are considered in NFDM model, namely, surface roughness, support structure volume, geometric tolerance, build time and fabrication cost. Findings: The case studies of turbine fan and dragon head indicate that the TOPSIS model can be perfectly integrated with the PID controller. This work extends the proposed model to different AM processes and investigates the feasibility of combining different decision-making models with PID controller and the effects of including various evaluation criteria in the integrated model. Originality/value: The proposed model innovatively takes the TOPSIS decision-making model and the PID control model as a whole. In this way, the uncontrollable TOPSIS model becomes controllable, so the proposed model can control the TOPSIS model to achieve the user-specified targets.