Statistical technology in the hottest automobile i

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Statistical technology in the automotive industry since 2002, China's automotive industry has gradually become a brilliant industry. Various automotive companies and their parts suppliers have become the biggest winners in the car buying boom of the Chinese people. Most models of almost every automaker have become the focus of the public. It is expected that this boom will continue for some time with the sustainable development of China's economy

even in this excellent situation, we must clearly realize that the current heat cannot last forever. With the development of WTO and the improvement of people's car purchase level, the domestic automobile industry will face great challenges. One of the challenges is how vehicle manufacturers and parts suppliers in the automotive supply chain can increase the quality management ability of the entire automotive supply chain and integrate with the international market in response to the increasingly fierce competition

as the leader of the automobile supply chain, the whole vehicle factory is faced with how to guide and promote the development of the quality management system of the whole supply chain, jointly achieve the goal of "preventing defects, continuous improvement, reducing the variation and waste of the whole supply chain", and finally achieve user satisfaction. One of the many problems faced by the largest parts suppliers in the automotive supply chain is how to deal with the different quality management system requirements of different vehicle manufacturers

from the successful experience of American and Japanese leading enterprises such as general motors, Delphi, Toyota and Honda, data-driven continuous improvement activities are one of their magic weapons to maintain competitiveness for a long time. The automotive industry has always attached great importance to data analysis. For example, in the five tool manuals of the early industry specification TS16949 quality system, there are two categories ("measurement system analysis" and "statistical process control") that specifically introduce the role and methods of quality improvement from the level of statistical analysis. In recent years, the Six Sigma movement based on JMP and other statistics to guide the healthy development of software in the new material industry has also reflected this feature

compared with American and Japanese enterprises, China's automotive industry has a very obvious gap in this regard. Because for a long time, Chinese people have been used to the "chest patting" mode of obeying orders and the "brain patting" experience oriented way of thinking. Even if some leaders are aware of this shortcoming and want to reverse this situation, they often find that the quality of employees varies greatly, especially without considerable statistical analysis skills

fortunately, the rapid development of Feimu bamboo powder in information technology in the early stage of heating provides an opportunity for us to narrow the gap and improve quality. Desktop statistical software represented by JMP, a high-end statistical analysis tool, has become increasingly popular in Chery and other domestic automobile enterprises, greatly reducing the data calculation burden of non statistical engineering and technical personnel. More importantly, by using the graphic analysis technology, advanced experimental design and other tools provided by JMP software, enterprises can use scientific and objective analysis ideas to solve many actual quality problems that have been troubled for a long time, the low-quality cost has been doubled, and the production efficiency has been significantly improved

next, we will combine a successful case to help you understand how to apply statistical technology in the automotive industry

background: the cylinder of an automobile engine is assembled from the cylinder block, cylinder head, piston, piston bearing, connecting rod, rod bearing and shaft (as shown in Figure 1). At present, the headache of the cylinder assembly workshop is that although the size of each part meets the original specification requirements, a considerable proportion of the finished products will always be assembled too loosely or too tightly after the final assembly, and each batch will spend a lot of money to resolve the repair costs beyond the policy goal of excess capacity. Although the company has realized that the size and specification of parts should be adjusted, it cannot be determined: which one or several parts are adjusted most effectively? To what extent is the tolerance range of the component most appropriate

Figure 1 structural diagram of engine cylinder

first, based on the principle of quantitative management, we can define this product quality characteristic as assembly clearance (= cylinder block + cylinder head - piston - piston bearing - connecting rod - rod bearing - shaft). The final assembly result cannot be too loose or too tight, that is to say, the tolerance specification of assembly clearance must be defined within a certain range, such as [0.005,0.015]

secondly, we will observe the quality level of assembly clearance when all parts meet the current specification requirements, that is, cylinder block ~ 8.50121 ± 0.00468, cylinder head ~ 0.70921 ± 0.00219, piston ~ 2.00156 ± 0.0011, piston bearing ~ 0.25035 ± 0.00114, connecting rod ~ 5.00017 ± 0.00327, rod bearing ~ 0.20008 ± 0.00099, shaft ~ 1.74825 ± 0.00249. Through the powerful simulation and graphics functions of professional statistical analysis software JMP, it is not difficult to find that the defect rate at this time has reached 4.96% and ppm has reached 49600 (as shown in Figure 2)

Figure 2. The current quality level of assembly clearance

it is obvious that the assembly defect rate of nearly 5% cannot meet the requirements of mass production. Where should we break through and seek improvement? To solve this problem, let's first understand the concept of overall defect rate. Taking the component "piston" as an example, the inappropriate length parameter of the piston will only produce two kinds of defects: first, the assembly clearance of the finished product is too small due to the excessive parameter, that is, the assembly is too tight; Second, the assembly clearance of finished products is too large due to too small parameters, that is, the installation is too loose. These two kinds of defects cannot be reduced to the minimum at the same time, and can only reach the overall minimum at a certain position. This position is the lowest point of the overall defect rate curve in red in Figure 3. Other parts also have similar overall defect rate curves, but the steepness of the curves varies with the lowest point

Figure 3 Schematic diagram of overall defect rate formation

similarly, using professional statistical analysis software JMP can quickly and easily produce defect rate diagrams of all parts and components as shown in Figure 4. Obviously, the average value of all parts has reached the lowest point of its overall defect rate curve, but the steepness of the cylinder block is the most obvious, indicating that it is the most sensitive to the defect rate of assembly clearance, and adjusting its specification limit can most significantly improve the quality level of finished products

Figure 4 current defect rate of all parts

therefore, we decided to reduce the specification limit of the cylinder block from the original 8.50121 ± 0.00468 to 8.50121 ± 0.00234 (that is, the standard deviation is reduced by 1/2), and the specification limits of other parts remain unchanged. The improved results are shown in Figure 5. It is noted that at this time, the assembly defect rate simulated by professional statistical analysis software JMP is reduced to 1.76% and ppm is reduced to 17600. Compared with the quality level before improvement, the effect is very significant. Of course, this result is not the most ideal, but we can also continue the analysis idea just now, find the improved parts and components step by step, improve and verify them, until we get a satisfactory assembly defect rate

Figure 5. The quality level of the improved assembly clearance

the above case analysis reflects the statistical analysis concept of tolerance design, but it is very simple to use the statistical analysis software JMP to realize the specific operation, which does not need special statistical knowledge to understand, and compared with the traditional test design, it saves a lot of the cost of collecting test data, so it is deeply loved by the practitioners of continuous improvement in automobile enterprises at home and abroad

the application of statistical technology in the automotive industry is far more than these. The improvement of the overall competitiveness of China's automotive industry chain cannot rely solely on statistical technology. The level of manufacturing technology and overall strength have been further improved, but there is no doubt that statistical technology provides a new idea and method for Chinese enterprises and employees who lack quantitative thinking to solve practical problems. Moreover, with the increasing popularity of statistical analysis software JMP, practitioners will no longer need to memorize complicated mathematical formulas and waste precious time on derivation and calculation, which will inevitably accelerate the breakthrough and innovation of China's automobile quality and enter the ranks of the world's advanced automobile manufacturing countries as soon as possible. (end)

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