### 统计代写|决策与风险作业代写decision and risk代考|Case Study

statistics-lab™ 为您的留学生涯保驾护航 在代写决策与风险decision and risk方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写决策与风险decision and risk方面经验极为丰富，各种代写决策与风险decision and risk相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|决策与风险作业代写decision and risk代考|Observed Manufacturing Plant

The observed manufacturing plant in which we performed the case study application is located in Germany. It makes plastic production by injection molding. The production includes several processes: Recycled plastic in crushed form is supplied from the supplier in the form of the bale. The bales are divided into pieces for homogenization. Thus, filling material can be added to the mixture. The raw material is brought to the shredder section to reduce the grain size. Raw material with reduced grain size is brought to the grinder. Large particles are removed from the system, and fine particles are brought to the centrifugal washing section. Here, at high temperature, solid plastic particles are melted to become liquid. Liquidized raw material is taken to the silo. Necessary additives are added to the molten raw material in the silo. With the help of the feeder, the raw material is brought to the extrusion section. In this section, the raw material is extracted in strip form. To prevent distortions in the product and achieve homogeneous cooling, the extruded strips are taken into the cooling pool. The extruded raw material is crushed in the grinder and brought to the silo. The final product is produced in the determined mold by sending the raw material with reduced particle size to the injection machine.

## 统计代写|决策与风险作业代写decision and risk代考|Analysis of the Result

The failure prioritization of six failure modes is $F M 5>F M 1>F M 2>F M 4>$ $F M 3>F M 6$. The failure mode of FM5 (Extruder blocking the flow of raw materials) with its highest final RPN score ( $R P N=0.323$ ) should be taken more attention. On the other hand, FM1 is also determined as the second most important failure mode $(R P N=0.320)$. FM3 and FM6 are determined as the least important failure modes.

The main factor in the formation of FM5 is that the raw material taken from recycling is not homogeneous. It is quite challenging to adjust the melt’s optimum temperature due to plastics with different melting temperatures in the supplied bale. In this case, the following measures can be taken. (i) As much as possible, less molten plastic should be sent to the system. This will reduce the production rate but improve flow through the extruder. (ii) It is not possible to provide the production parameters because the raw material used is not homogeneous. Therefore, preliminary tests should be carried out at each supply to determine the optimum melting temperature and pressure amount. Thus, congestion in the extruder is prevented. (iii) Homogeneity should be taken into account in supplier selection. (iv) The grain size in the grinder, feeder speed, silo temperature should be controlled continuously, and necessary precautions should be taken to prevent clogging of the extruder.

The main factor in the occurrence of FMl is the size difference in the raw material supplied. To prevent this failure: (i) A pre-screening process should be carried out on the raw material supplied. Thus, more homogeneous particles will not create clogging in the shredder. (ii) Storing the raw material at appropriate humidity and temperature will increase the shredder performance. (iii) Necessary thread adjustments should be made according to the incoming raw material while setting the shredder. The operators should be given the necessary training in this regard. Since the raw material arrival is irregular, the operator should make the necessary adjustment without delay.

## 统计代写|决策与风险作业代写decision and risk代考|Discussion

A comparative study that considers evaluations of both risk parameters and FMs with respect to three RPN elements via AHP is demonstrated to test the validity of the proposed approach. Figure $3.8$ shows the whole evaluation and obtained weight

values and preference values of six FMs according to these parameters ( $S, O$, and $D)$. All evaluation matrices are found consistent. The CR values of each matrix are also given in Fig. 3.8. By combining preference values of failure modes with respect to each RPN element, the first matrix is gained. Then, final RPN values were obtained by multiplying this matrix and weight matrix. The results are presented in Table 3.4.
As a result of the AHP calculation, FM ranks are as follows: FM5 $>$ FM1 $>$ FM2 $>$ FM4 $>$ FM3 $>$ FM6 When the values of this RPN calculation procedure by AHP and the proposed approach by BWM are compared, it is observed that the ranks are quite similar. Pearson correlation coefficient regarding final RPN values and Spearman rank correlation coefficient regarding rankings in both approaches were determined as $0.98$ and $0.94$, respectively. In this case, it can be said that there is a very strong relationship between these results.

## 广义线性模型代考

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## MATLAB代写

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