1


The Case Study: Performance Network Analysis of Nylon
Filaments Processes.
Performance Measurement Management (222531)...
2


III. Performance Network

The Network has three steps; started from (Revenue / Total) Cost is separated into
three net...
F             F                          F F
                                                                             ...
4



IV. Regression Analysis

According to raw data in table1, the regression equations are generated by the Minitab.
The ...
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Performance Network Analysis of Nylon Filaments Process

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Performance Network Analysis of Nylon Filaments Process

  1. 1. 1 The Case Study: Performance Network Analysis of Nylon Filaments Processes. Performance Measurement Management (222531) By. Tanprasert T. I. Nylon Filament Processes. Nylon filament is the one of three processes of TTS’s company. The Input of the process is Capro-lactam. The Capro-lactam comes from the upstream petrochemical processes. The process of nylon is started from Polymerization process. The plastic nylon chip is produced from this process and sent to next process called Spinning process. The chip is melted and pressed through the tiny holes (spinneret) and drawn in to the filaments. The process need to consume a lot of raw materials and energy that are the main cost of the process. The Output of nylon process is nylon filament and chip. The main customers are apparel, fishing and automotive industry. II. Input - Output Analysis and Ratio Selection The Inputs and Outputs factors choose are relating to cost of production as shown in fig. 1. Figure1. The Input - Output Analysis The Revenue to Total Cost ratio is selected for this analysis to find the relationship between among factors.
  2. 2. 2 III. Performance Network The Network has three steps; started from (Revenue / Total) Cost is separated into three networks. There are (Revenue / Utility) Cost, The (Utility Cost / Variable Cost), and (Variable Cost / Total Cost). The detail of each step is represented in fig2, 3, and 4 below, Performance Network #1 (PN#1) F FF F F Figure2. Performance network #1 F FF F F F F FF F Revenue / Utilities Cost F F F F F X1 - Revenue / Material Cost X2 - Material Cost / Total Cost X3 - Utilities Cost / Total Cost Performance Network #2 (PN#2) Figure3. Performance network #2
  3. 3. F F F F 3 F F F F F F F F F Utilities Cost / Variable Cost F F F F X4 - Utilities Cost / Fixed Cost X5 - Fixed Cost / Labor Cost X6 - Labor Cost / Variable Cost Performance Network #3 (PN#3) F F F F Figure4. Performance network#3 F F FF F F F F F Variable Cost / Total Cost X7 - Variable Cost / Operation Cost X8 - Operation Cost / Total Cost Table1: Ratio Data for Regression Analysis Y X1 X2 X3 X4 X5 X6 X7 X8 Mat. Utility Utility Fixed Labor Var. Operate Revenue Revenue Cost Cost Cost Cost Cost Cost Cost Total Mat. Total Total Fixed Labor Var. Operate Total Cost Cost Cost Cost Cost Cost Cost Cost 0.90 1.19 0.76 0.06 0.45 7.67 0.02 4.85 0.18 1.03 1.36 0.76 0.06 0.41 7.40 0.02 4.30 0.20 1.24 1.48 0.84 0.06 0.49 7.69 0.02 5.02 0.19 1.22 1.49 0.82 0.07 0.50 7.21 0.02 4.80 0.19 0.92 1.15 0.80 0.07 0.53 7.30 0.02 4.78 0.19 1.06 1.37 0.78 0.07 0.60 6.95 0.02 4.76 0.19 0.96 1.30 0.74 0.07 0.51 8.98 0.02 4.50 0.19 1.05 1.35 0.78 0.07 0.50 9.59 0.02 4.61 0.19 1.11 1.51 0.74 0.08 0.54 9.46 0.02 4.35 0.20 1.02 1.37 0.74 0.08 0.52 10.02 0.02 4.42 0.19 1.12 1.59 0.70 0.08 0.55 9.71 0.02 4.09 0.20 1.10 1.71 0.64 0.08 0.47 8.07 0.03 3.43 0.22 Remark: Data on 12 months period, 2005
  4. 4. 4 IV. Regression Analysis According to raw data in table1, the regression equations are generated by the Minitab. The results are shown in table 2 below, Table2: Regression equation and Adjusted R-square value Multiple Regression Equation for All Factors Adj.-R2. Y= - 0.755 + 0.790 X1 + 1.60 X2 + 0.057 X3 - 0.0337 X4 + 0.00087 X5 - 99.7% 1.66 X6 - 0.0391 X7 - 1.51 X8 V. Conclusion • The PN#1 has a significant interrelationship to Revenue/Total Cost ratio more than PN#2, and PN#3 as 99.3% R-Sq (adj). • The Raw material has a most significant effect in PN#1. • The PN#2, PN#3 has no significant to Revenue/Total Cost, because the factors are not appropriate ratio selected to form a network. • From the overall regression equation, the R-Sq (adj) is 99.7%. This network analysis is confident.

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