| 传统自动化设备和 AI 自动化有什么区别？ |
| 是什么让自动化设备发展到如此程度？ |
| 当工人的学徒变成机器人时？ |
| 多臂特种机器人 |
| 人工智能的最大好处 |
| 数据的爆炸式增长使人们陷入决策困难 |
| Twin 技术 |
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当人们还在谈论人工智能是否会威胁人类的生存时，人工智能自动化设备的进步已经变得不可阻挡。一场正在彻底改变制造业的革命正在悄悄进行，您可能还没有意识到它。人工智能已经在您身边，很快就会超出您的想象。
传统自动化设备和 AI 自动化有什么区别？
• 解决简单的批量重复工作，减轻员工的体力劳动负担，自动化生产设备的这些功能已成为过去。在人工智能技术到来之前，这些现代技术似乎为人类提供了很多便利，但人工智能自动化设备可以做的远不止于此。
• 人工智能的雄心远不止解决重复性劳动的问题。那些不易复制的困难任务也是 AI 试图接管的，包括抛光、切割、研磨、去毛刺或其他精密机械任务。只有学习机器人可以处理这些任务。
• 普通机器人需要编写固定的程序，以便它们完成设计的动作，例如在固定工作站上贴标签和拧瓶盖。这种机械程序可以用算法来代替。学习机器人不需要传统的编程。他们需要学习如何自己制作产品，犯错误，然后自己收集数据。你不需要告诉它工作的细节和步骤，你只需要告诉它你想要什么结果就行了？它自己完成整个过程，并且比您更了解要避免哪些错误。
• 当你想完成其他产品的生产时，你不需要购买一台新机器，而是让它重新学习另一个产品的生产过程。因此，不再需要冗长的编程，这大大降低了软件工程师的作用。
• 机器人或协作机器人可以学习并接管不易复制的非线性流程的执行。多臂特种机器人。他们可以自己决定用哪个手臂来执行哪个动作。
是什么让自动化设备发展到如此程度？
• Industry generates large amounts of production data every day. For example, the process of making goods, predictable reasons for product failure or behavior, etc., can be collected and compiled into data to build AI models. The neural network of the human brain inspires artificial intelligence. Each node is also called an artificial neuron and has associated weights and thresholds. If the output of any single node is above a specified threshold, then that node is activated and the data is sent to the next layer of the network.
• Based on this principle, artificial intelligence learning methods can be divided into the following three types. The pros, cons and costs of each learning method are different.
• Its algorithms usually have the following five types:
Neural Networks: | Neural networks mimic the workings of the human brain with a large numberof linked processing nodes, Neural networks excel at recognizing patterns and play an importantrole in applications such as natural language translation, image recognition, speech recognitionand image creation. |
| Linear regression: | This algorithm is used to predict values based on a linear relationship betweendifferent values. Ffor example, this technique can be used to predict house prices based onhistorical data for the area. |
Logistic regression: | This supervised learning, algorithm predicts categorized response variablessuch as yes/no answers to questions. lt can be used in applications such as spam classification and production line guality control. |
Clustering: | Using unsupervised learning, custering algorithms can identify patterns in data inorder to group them, Computers can help data scientists by recognizing differences betweendataitems that humans ignore. |
Decision Trees: | Decision trees can be used both to predict values (reeression) and to categorizedata, Decision trees use a sequence of branches of linked decisions that can be represented as atree diagram. One of the advantages of decision trees is that they are easy to validate and audit.unlike the black boxes ofneural networks. |
Random Forest: | ln a random forest, a machine learning algorithm predicts a value or category bycombining the results of multiple decision trees |
• Enterprises can use it to improve production or operational efficiency. The most important thing is to provide very accurate and unbiased training data sets. Otherwise, AI learning that keeps making mistakes will only consume a lot of resources and money, and will also make business owners lose confidence to Keep going.
When a worker's apprentice turns into a robot?
An amazing fact is that machines can program themselves through learning,If you want it to learn a job, you may need a worker to pick up the robot's arm, teach it to complete various steps or process positions, pick it up or put it down, etc. The machine can even self-correct through its own algorithm, completing better work results and more efficiently than workers, and can work for extremely long hours without the need for vacations.
Multi-arm special robot
With the help of machine learning, multi-arm special robots do not need to be programmed to set their movements. They can decide the position and direction of their robotic arms and complete their work autonomously. Therefore, if there is a problem with the settings, the robot will lose control and it will be really dangerous for humans.
The biggest benefit of artificial intelligence
Manufacturing is likely to be the area that benefits the most from artificial intelligence. Manufacturers around the world are racking their brains to use AI to bring them more benefits.
The explosion of data has put people in decision-making difficulties
It is estimated that the manufacturing industry generates about 1,812 pb of data every year. The large amount of data does not bring convenience to enterprises, but makes their decision-making more and more difficult and slow. This is also a suitable time for the explosion of AI technology. This phenomenon does not only exist in the manufacturing industry, but also in all walks of life.
Twin technology
When you are learning from a very senior technical worker's experience, and he is serious about correcting your mistakes and teaching you new skills, he may not be a real person, but a person provided by smart AR glasses in an industrial environment training program,When you are testing new cutting paths or robotic assembly, you may also find that you are just in a simulated factory,not a real one,Experienced employees can provide on-site guidance to multiple new employees at the same time without having to go to the site.
Many automated equipment factories are facing the problem of increasingly low profits and difficulty in survival. Either this is an opportunity to transform to AI, or we should think more about when machines can learn skills by themselves and decide where to swing their arms. Will it bring any threats to us?
