外文翻譯--聚氨酯反應(yīng)注射成型工藝的分析和優(yōu)化（英文）

1、Analysis and optimization of a polyurethane reaction injection molding (RIM) process using multivariate projection methodsF. Yacoub, J.F. MacGregor*Chemical Engineering Department, McMaster University, 1280 Main Street W

2、est, JHE-374, Hamilton, ON, Canada L8S 4L7Received 13 April 2002; received in revised form 20 August 2002; accepted 25 August 2002AbstractPrincipal component analysis (PCA) and projection to latent structure (PLS) method

3、s are used with industrial data to successfully diagnose several different problems arising in the manufacturing of rigid polyurethane foam insulation panels. The PCA and PLS models are used to reveal the spatial variati

4、on of quality variables throughout the foamed product, and their relations with the process variables. Designed experiments are performed in the key process variables identified from the PCA studies and the results are u

5、sed to optimize the process. D 2002 Elsevier Science B.V. All rights reserved.Keywords: Polyurethane; Reaction injection molding; Projection method1. IntroductionIn the last two decades, chemical processes, like many oth

6、er industries, have been going through a revolution in their data collection systems. Machine intelligence, immense data storage capacity, and high throughput data acquisition systems have driven the cost per data point

7、down to a very low level. Masses of data are now available by measuring process variables as well as quality variables either on line or in quality control labs. Projection methods such as principal component analysis (P

8、CA) and projection to latent structure(PLS) provide a way to handle the highly correlated data collected by these systems. In addition, they deal effectively with multiple response variables and with missing data, and th

9、ey provide a good tool to extract and highlight the systematic variation in these multi- variate data sets. The most important property of projection methods is the capability to reduce the multivariate dimension of a pr

10、oblem into a low-dimensional space, usually con- sisting of three to four dimensions. The SIMCA_P 8.0 software of Umetrics was used for the PCA/PLS analyses performed in this work. The focus of this study is the applicat

11、ion of the multivariate projection methods for the diagnosis and analysis of a polyurethane reaction injection process. The main objectives of this research are to understand the spatial variation in the process, correct

12、 the causes of this variation, and optimize the quality variables.0169-7439/02/$ - see front matter D 2002 Elsevier Science B.V. All rights reserved. PII: S0169-7439(02)00088-6* Corresponding author. Tel.: +1-905-525-914

13、0; fax: +1-905- 521-1350. E-mail address: macgreg@mcmaster.ca (J.F. MacGregor).www.elsevier.com/locate/chemometrics Chemometrics and Intelligent Laboratory Systems 65 (2003) 17–33polyurethane foam mix-head carriages. Eac

14、h carriage foams a different door.2.1. Problem descriptionThe instability of the foaming process and the complexity of controlling the quality variables created the need and motivation for this work. Two problems on this

15、 process are discussed separately as they arose at different times. The first project was to optimize the functionality of the polyurethane foam panels expressed by the spatial variation of its thermal conductivity and d

16、ensity. The insulation function of the foam, measured by thermal conductivity (k-factor), is considered as a vital variable to be controlled. It has a direct effect on the refrigerator performance and energy consumption.

17、 In theory, when the master batch is mixed with the isocyanate at a cer- tain temperature, the blowing agent boils, and creates a vapor that blows the foam and reduces the density. In rigid foam, the cells formed by the

18、blowing agent redu- ce the transmission of heat. The lower the k-factor is, the better the insulation and the refrigerator performance. Density, which is an indication of foam strength, is important in keeping the struct

19、ural rigidity of the refrigerator. It is a result of the pressure that the vapor from the blowing agents exerts in the cell. The cell gas pressure causes the foam to resist shrinkage. In order to reduce the scrap rate of

20、 this process, unacceptable voids and leaks have to be minimized. The objective of the second project treated in this paper is to minimize the distortion phenomena in the foamed panels known as Outer Bow (OB). Outer Bow

21、is mainly caused by the movement restriction of the steel and ABS plastic panels. The panels are unable to expand or contract relative to each other since the distance separating them is relatively small. If move- ment i

22、s to occur, it will result in the warping of the panels or shear deformation.2.2. Quality measurementsQuality variables are measured off-line on a weekly basis in quality control labs. The upper specification limit of th

23、e thermal conductivity is based on energy calculations, and the lower specification limit of den- sity is defined as the minimum density to maintain structural strength. All measurements are performed ateight locations a

24、round the foamed panels. The criterion is to have all samples within the specified control limits. Thermal distortion is measured using a Coor- dinate Measuring Machine (CMM) by defining a plane that passes through point

25、s located in the corners of the panel and measures the deviation from this plane at several points across the panel surface to determine the shape and magnitude of surface bow. The following quality variables are measure

26、d:2.3. Process variablesProcess variables were selected and retrieved from the database. The analysis was performed on six differ- ent fixtures from production to understand the variation between fixtures and the effect

27、of changes in the process variables. A summary of process variables used in the analysis and the corresponding nomencla- ture presented in the paper is given as follows:Time to test T_T Ambient temperature A_T Master bat

28、ch density MB_D Master batch flow MB_F Isocyanate flow I_F Ratio between Master batch and isocyanate MB/I Isocyanate pressure I_P Master batch pressure MB_P Mix-head pressure MH_P Shot size SS Isocyanate temperature I_T

29、Master batch temperature MB_T Isocyanate temperature at mix-head I_T_MH Master batch temperature at mix-head MB_T_MH Surfactant type S Blowing agent type B Fixture core temperature Core_T Fixture sidewall temperature Sid

30、ewall_T Fixture preheat temperature Preheat_TK* K-factor values at various spatial locations (1–8) D* Density values at various spatial locations (1–8) Voids Identified by sink marks in the outer steel Leaks Identified v