Now the automation boom in the mold industry is unstoppable, which is certainly a good thing from the perspective of development. The mold industry really needs to eliminate some backward manual modes. However, if automation is used in the mold industry, do not simply think that as long as you spend money on the most advanced automation technology, you can replace technicians to make high-quality molds. This is a big mistake. Mold managers and senior managers can clearly distinguish, and the most afraid is that the investment after a fever will return a pile of equipment that can not operate!
The mold factory should not be in a hurry to automate, but use human brains to solve problems first
We have all seen many automation cases in the western world. Why do foreigners come to China and other countries with relatively abundant human resources and relatively low labor quality to place mold orders? Why don't they use the method of Industry 4.0 to manufacture molds in automated unmanned factories? This also shows that not all molds can be made by automatic methods.
It seems that the application of mold automation is pessimistic. To be sure, for some products with high similarity, or for a certain product that requires a batch of molds, the manufacturing of these molds can completely achieve a high degree of automation to enhance the competitiveness of mold factories.
However, for single set of mold manufacturing and ever-changing mold manufacturing, there are still some problems if you want to apply mold automation production!
The mold factory should not be in a hurry to automate, but use human brains to solve problems first
After seeing many mold manufacturing plants, I think the profit of mold depends on two guarantees: the best design scheme and the best processing efficiency.
There is no inevitable relationship between the efficient processing and automation of typical single piece flow workpieces such as molds. The core of automation is numerical control, and the core of numerical control is programming. The programming here refers to the data generation and control of the whole process. However, the quantification of 3D objects with high complexity such as molds and the huge quantized data stream are exactly completed with the actual workpiece according to the process sequence and quality requirements of mold processing, so as to achieve satisfactory results judged by the human brain. At this stage, it is absolutely impossible to complete the task.
I can see that the problems in countless mold workshops are mainly slow, from finding things to processing to logistics, which can not be solved by automation. Automation refers to the limited digital transfer of the knowledge system in the human brain to the computer, which is just a very stiff, no sense to complete a series of actions, of course, they do not know the meaning and purpose of these actions. Automation at this stage is in fact rigid.
We all feel sorry that there are no craftsmen in the workshop, so we can't make a good mold. Similarly, we can't expect a robot without perception to do a good mold. Do they know what is good?
Just like PM software can't program a good path by itself and UG software can't draw a good graph by itself, it still needs high-quality designers and programmers to use the software well.
Then we need a high-quality team to solve all the problems on the production site first, make customers satisfied, and then quantize the satisfied results with data to form the instructions that can be executed by the automation equipment. Only when the results after the automation equipment executes the instructions are closest to the results of manual operation can we achieve the role of the automation equipment.
When a team cannot rely on the knowledge system and practical ability of the human brain to achieve customer satisfaction, how can we talk about using automation equipment to achieve customer satisfaction?
A mold factory that can operate normally must start from the human-machine material method measuring ring of 5M1E, and improve all aspects step by step, including water, electricity, gas and liquid, cutting tool measuring card, logistics, design, process, plant planning, supply chain optimization, information management and other issues. It is not too late to talk about automation after the problem is solved by human brain.