Views: 0 Author: Site Editor Publish Time: 2022-07-29 Origin: Site
To answer these questions, let's start with the reality of the factory.
The factory has a very strict quality control system. Every quality problem, especially the quality claim, must have clear treatment opinions and measures. This includes identifying who is responsible and suggesting ways to prevent repeat attacks. However, in some treatment opinions, there is obvious irrationality. For example, a treatment is: require a process to maintain stable production. This is obviously a perfunctory approach: everyone has known for decades about the importance of maintaining stable production, but the reality has simply failed to do so.
But the question is: why the perfunctory treatment?
If we think about it, there are many ways to deal with this kind of problem. For example, we downgrade the product directly. But why don't we do it? Because production instability is the norm, most users are fine with it. It's too costly to downgrade a product. In other words: when production is unstable, most products can survive downgrading, but this time the problem is accidental.
Why did it go wrong this time?
There are three possible reasons:
1）The stability of this production is too poor;
2）This kind of product requires high production stability;
3）Customers have high requirements.
Therefore, in order to find a reasonable improvement method, it is necessary to analyze the problem from these three angles. These three directions are related to process, product and customer service respectively. Rough calculation down, may involve 7, 8 departments. Therefore, it is difficult to determine the good treatment method, had to perfunctory.
What are the problems with this fudge?
One is that companies will inevitably be claimed, one is that users have to act as guinea pigs. In the long run, the problem is even more serious. I often talk about: high-tech products often mean high quality, and high quality means a high degree of quality stability. Allow this to happen, and there must be a "ceiling" of quality stability, a barrier that is hard to surmount. As time passes, the gap between us and foreign countries is so opened.
A lot of technical support is needed to solve this kind of problem.
1）The first thing is to string the data together, which is information integration. That's the only way to know what's wrong. At the same time, to use historical data for comparison: in the past this kind of process, this kind of product has similar problems; when similar problems occur, whether other users also have claims. In my opinion, data analysis is mainly about comparison, not "neuronal analysis" and other complex algorithms. What people who work on industrial big data algorithms or tools should do is to make this comparison more convenient, efficient, and human-computer interaction more convenient.
2）This kind of analysis is time consuming. Experiments or tests may also be required if necessary. That raises a new question: Is it worth it?
In an enterprise with a good quality culture, such work must be supported; Companies with a poor quality culture will not support this kind of work. In fact, companies with a poor quality culture will never admit that they don't care about quality. They will only do one thing: calculate results. Quality improvement work is troublesome, but the benefits are not easy to calculate. And benefit involves evaluating people, something few people are willing to do. In my opinion, the work of improving quality is not low efficiency, but direct and short-term benefits are not easy to calculate. This kind of idea is the important reason that causes Chinese enterprise technology to lag behind.
We can also start with technology to find a way to solve this problem: improve the efficiency of quality work. The specific idea is to realize through the reuse of knowledge: to thoroughly study the problem, to extend the research results to different products and users, so as to draw inferences by analogy. If a piece of knowledge is used thousands of times, its value will come naturally.
However, the complexity of administration increases when the analogy is made. Moreover, such knowledge is often fragmented, impossible to keep in mind and difficult to carry out. Therefore, the key to solve this kind of problems is to digitize, standardize, model, let the computer to carry out quality management.
Computer management quality, will encounter new difficulties: the first is to the user, product, process data real-time integration, in order to respond in time, do effective management. The second is that the transfer of knowledge to the computer can be troublesome and costly, and the development of a feature can be costly. The solution to these two troubles is to adopt more convenient tools, such as industrial web platforms and digital twins. So, if you look at the problem clearly: the industrial network platform and the digital twin is not to solve the problem of technical feasibility, but to solve the problem of economic feasibility.
Further on, quality management problems are increasingly left to machines, what do people do? The human role is to constantly improve such systems. Retreat from the production line to the second line actually, do the producer of knowledge. After being a full-time knowledge producer, people's professional level will be higher and higher, and the technical economy will be stronger and stronger. In this way, the knowledge economy really has the economy.
Will my story ever come true?
That's what Big River Steel did in the United States. 'We're a technology company that got into steel by accident,' says Dahe.
Now many people realize that the development of industry is not done in a day. Why not in a day? Because the development of industry requires the accumulation of knowledge and experience. What is the meaning behind accumulation? In fact, pay attention to small progress! Blind emphasis on leapfrog development, in fact, is to despise the accumulation of small! Who does the accumulation? Accumulation is done by frontline workers and engineers. Therefore, only by emphasizing the importance of accumulation can we cultivate the craftsman spirit! Chinese ancients had many good thoughts: "A hurricane begins at the end of Qingping"; "A folded wood grows from a grain, and a nine-storey platform from a pile of earth"; "Do not take evil small and do it, do not take good small and do not do it"; "Steed leap cannot ten steps, ten dobbin driving work in not give up", "no accumulation of small steps without as far as thousands of miles, not small stream beyond into the sea". When a company aims to be a world-class enterprise, it should carefully look back to the teachings of the ancients.
Remember: the greatest advantage of digitization is its ease of standardization, and thus its ease of inheritance, its ease of continuous improvement, its ease of continuous improvement more efficiently, and its ease of accumulation. The failure to see the value of digitalization is often the failure to see the power of continuous improvement. And not seeing the power of continuous improvement is often because we don't really position ourselves as a leader in technology. People who overemphasize "leapfrog development" tend to attach importance to technology in a "leaf Gonghaolong" way: what they value is not the real technology, but the fame and fortune that technology brings. Really good technology for them is not as good as packaged bad technology.