Improvement of Material Flow in the Production and Supply Chain of ...

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3.3 Main assembly line data analysis Because the bottleneck of the main assembly line is station eight, data of Time to Failure and Time to Repair are gathered from this station. Data gathered from week thirty to week fifty in 2007. (See data show in Appendix A, Table 2) The analysis methods are similar to the preassembly line. 3.3.1 Primary data analysis for main assembly line The results of Excel are shown in Figure 3.5. The left one the time between failures data and the right one is the time to repair data. It is evident the equations or functions offered by Excel neither suit to describe the trend of TTF nor the trend of TTR. All of the data are stochastic. Because the limited sample and the complex practical situations it is hard to say which of them are normal data. But the data for week fifty can be deleted because this is the vacation week for all of the employees and the production line stopped. TTF/sec. 450.0 400.0 350.0 300.0 250.0 200.0 150.0 100.0 50.0 0.0 30 32 TTF of Main Assembly Line 34 36 38 40 week 42 44 47 49 TTR of Main Assembly Line Figure 3.5 TTF & TTR of Main Assembly Line In order to get the parameters of Triangular Distribution the descriptive statistics used to analysis the data. And the method has been introduced in the process of analyzing the data of preassembly line. The results of descriptive statistics for TTF and TTR of main assembly line are shown in Table 3.3. The parameters of Triangular Distribution are maximum data, minimum data and most likely data. The values are maximum data and minimum data are show directly and the most likely value, which is the mode value, is still the estimation value. Table 3.3 Descriptive Statistic of TTF and TTR of Main Assembly Line TTF of Main Assembly Line TTR of Main Assembly Line Mean 276.32 Mean 187.32 Standard Error 15.71 Standard Error 16.08 Median 278.07 Median 179.33 Mode 320 Mode 130 TTR/sec. 350.0 300.0 250.0 200.0 150.0 100.0 50.0 0.0 30 32 34 36 38 40 week 42 44 47 49 16
Standard Deviation 68.49 Standard Deviation 70.07 Sample Variance 4690.93 Sample Variance 4909.82 Kurtosis -0.41 Kurtosis -0.57 Skewness 0.54 Skewness 0.61 Range 236.87 Range 224.05 Minimum 186.65 Minimum 99.49 Maximum 423.52 Maximum 323.53 Sum 5250.15 Sum 3559.17 Count 19 Count 19 3.3.2 Further data analysis for TTF of main assembly line As the method used to analysis the TTF of preassembly line, in this section also assume the TTF data following the Exponential Distribution. And then test the hypothesis by One-Sample Kolmogorov-Smirnov. The results of One-Sample Kolmogorov-Smirnov Test for main assembly Line’s Time to Failure are shown in Table 3.4. The probability of two-tailed test value of the Exponential Distribution is smaller than 0.05, so the Exponential Distribution satisfy the data trend. And the Exponential parameter: mean is 276.3210 seconds. Table 3.4 Results of One-Sample Kolmogorov-Smirnov Test for Main Assembly Line’s TTF N One-Sample Kolmogorov-Smirnov Test TTF 19 Exponential parameter.(a) Mean 276.3210 Most Extreme Differences Absolute .491 Positive .216 Negative -.491 Kolmogorov-Smirnov Z 2.141 Asymp. Sig. (2-tailed) .000 a Test Distribution is Exponential. b Calculated from data. 3.3.3 Further data analysis for TTR of main assembly line The data of Time to Repair of the final assembly is analyzed by the same method: P-P Plots. Still select Lognormal Distribution to analyze the TTR data. The results of P-P Plots of main assembly line’s Time to Repair are shown in Figure 3.6. The mean and standard deviation are 187.3263 seconds and 70.0659 seconds separately. 17
Page 1 and 2: ROYAL INSTITUTE OF TECHNOLOGY Impro
Page 3 and 4: Needs to be pointed out is that in
Page 5 and 6: TABLE OF CONTENTS ABSTRACT.........
Page 7 and 8: List of Tables Table 3.1 Descriptiv
Page 9 and 10: CHAPTER 1 INTRODUCTION OF THE RESEA
Page 11 and 12: 1.2 Present problems Haldex faces i
Page 13 and 14: CHAPTER 2 RESEARCH THEORY AND METHO
Page 15 and 16: mindset simply does not accurately
Page 17 and 18: the customers. Both of them are pri
Page 19 and 20: processing in station 5b. In the re
Page 21 and 22: After deleting the un-normal data i
Page 23: data of preassembly line accords wi
Page 27 and 28: Table 3.6 Values of Parameters of T
Page 29 and 30: line. In order to simplify the mode
Page 31 and 32: Table 4.3 Output Date Come From the
Page 33 and 34: Table 4.5 Current Production Volume
Page 35 and 36: Table 4.7 listed the simulation res
Page 37 and 38: 4.3.3 Increasing the operation time
Page 39 and 40: ottlenecks. Obviously, from the poi
Page 41 and 42: the first one. For the third soluti
Page 43: and unforeseen events by keeping sa
Page 46 and 47: separately and the supply chain emp
Page 48 and 49: 5.2.1 Current distribution of suppl
Page 50 and 51: Table 5.2* Delivery Information of
Page 52 and 53: ecause this only gets from experien
Page 54 and 55: 5.3.2 Inventory and suppliers’ se
Page 56 and 57: Table 5.3 Integrative Estimation of
Page 58 and 59: CHAPTER 6 INVENTORY REDUCTION AND D
Page 60 and 61: How to get the best value from a su
Page 62 and 63: calculation, 420 pallets can be suc
Page 64 and 65: each day. The maximum load of one t
Page 66 and 67: and can also overworking during wee
Page 68 and 69: CHAPTER 7 CONCLUSION AND FUTURE WOR
Page 70 and 71: Reference Books and papers • Ahma
Page 72 and 73: y Chapman&Hall. • Vickery, Shawne
Page 74 and 75:
Appendix A Table 1 TTF & TTR Data o
Page 76 and 77:
Table 5.1 Suppliers & Suppliers’
Page 78 and 79:
Appendix B Figure 1 Assembly line M
Page 80 and 81:
Figure 3 Current Assembly Line Mode
Page 82 and 83:
Figure 5 Assembly Line Model in Sol
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