Mold surface temperature

MOTE (x9) 70°C 65°C to 75°C

Experimental design and methodology

This section presents how to design the experiment as well as  the   procedure   to   determine   the   efficient   frontier of

The setting in Moldflow to simulate production of the parts is described below.

Figure 2 shows the finite element model of the plastic part, and Figure 3 is the runner system with the cooling channel. The material used in this paper is GE Cycoloy C2950 PC/ABS (Gardena, CA, USA), and the simulating molding machine used is Roboshot 330i (330 tons, 8.90 oz, 44 mm) high speed/pressure (Milacron, Cincinnati, OH, USA). Table 1 lists the main properties of the material.

This paper discusses nine key process parameters which are suggested in the literature (Chen and Turng 2005; Chen et al. 2010) because these parameters are most likely

process parameters. In the ‘Experimental design’ subsection, the experimental design will be addressed.  To effectively find the efficient frontier, ANOVA  will be firstly  executed to determine the significant process parameters out of the original nine process parameters in ‘Finding significant process parameters by ANOVA’ subsection. The complete design of experiment with four significant process parame- ters is again executed on Moldflow to have better accuracy of the following regression equations. Then, response re- gression model will be established in which only significant process parameters are considered in ‘Setting up the re- gression  response  model  to  create the  complete dataset’

COTI COTE MOO MET MOTE

subsection. This subsection will also present how to create the complete dataset for finding the efficient combina- tions. Finally, ‘Determining the efficient frontier of process parameters by DEA’ subsection will discuss how to find the efficient frontier by DEA.

Experimental design

The Taguchi experimental  design  with  orthogonal array is an efficient experimental design for fraction factorial design (Rose 1989; Montgomery 2005). Be- cause there are nine process parameters considered in this research, complete experimental design is just too expensive to execute. Therefore,  this  research  adopts the Taguchi experimental  design  with  orthogonal array, L27, to perform the  experiment  on  Moldflow. The experimental results of L27 is shown in Appendix A. Three levels of each process parameters are assigned to lower bound, mid-point, and upper bound of the range of operation listed in Table 2; for example, levels 1, 2 and 3 of injection time x1 are 0.5, 1 and 1.5 s, respectively.

Finding significant process parameters by ANOVA

In order to simplify the regression equations (and thus simplify the following procedure), ANOVA is firstly exe- cuted to find significant process parameters to affect the parts’ three quality indices which will only be considered in the regression equations. The results are shown  in Table 3. Each node represents the warpage at this node, each edge means the shrinkage at this edge, and the volume is the volumetric shrinkage at ejection in Table   3.

The  symbol  ‘◎’  means  the  corresponding  process  par-

ameter significantly affects the quality index under the significant level 0.05 in the figure. The last column of Table 3, U, is remarked by ‘●’ if  the  corresponding process parameter significantly affects at least one qual- ity index. From Table 3,  only  four  process parameters are  significant  to  affect  at  least  one  quality  index, and