It seems like it was just yesterday that talks about artificial intelligence fell exclusively in the domain of science fiction. Today, it and its sub branch, AI and machine learning, are everywhere in business and manufacturing.
Indeed, manufacturing of any kind is a cut-throat business. The margin for error is small, the market is changing every second, and by its very nature, it’s comprised of uncountable moving parts. A human brain might have trouble handling it all, but a machine brain has a good shot.
Difference Between AI and Machine Learning
An AI and machine should be able to mimic hitman intelligence and perform tasks and activities like thinking, learning from experience, and making decisions. Machine learning is a branch of AIs that is specialized in learning from data without extra assistance.
This learning is based on how well the machine analyzes data and, based on its algorithms, creates a model, sees how it can perform under specific circumstances in a specific environment, and what the results of this performance might be.
How To Begin Incorporating
We should start by mentioning that, of course, every business, and indeed every field, is different. However, some universal rules do exist, and sticking to them can help you maximize the result you want. So, some things you should keep in mind are:
- Gather and prepare data
- Decide which areas of your business will this apply to
- Train your staff
First of all, machine learning requires a large amount of data at the very start. It needs this information in order to make predictions, detect patterns, etc. We suggest you have someone gather all the important information you want to be used in one single place.
It needs to be accessible by the Machine Learning tools you want to use in the right format. In other words – don’t make the technicians and software live any harder than they should be.
Next, you want to be clear on what you want to accomplish with these systems. These can be used in different segments of manufacturing, from the actual early stages of the process, right down to quality control.
Of course, ideally, you would want to apply this machine learning to every level of production, but budget constraints, human resources, and time simply might not permit that.
Finally, you want people who know how to implement these things. Finding the right technicians is always an option, but perhaps it would be better to train the people you already have. They are more familiar with your company and your processes, and you will also gain loyal staff.
Machine Learning and Manufacturing
The best way one can explain machine learning is to give practical examples. In this article, we have listed some of the benefits of machine learning for manufacturing, as well as how it can be incorporated into production processes.
Maintenance Costs and Reliability
One of the ways you can incorporate machine learning and artificial intelligence in manufacturing into your manufacturing process is by optimizing maintenance schedules.
These schedules can be for your own equipment or for your staff maintaining client gear off-site.
So, let’s say you deal in agricultural machinery. You have 30 different machines for 30 different processes, all working during different times in the year, at different times.
One way to maintain them is to have a specific maintenance day. Another is having a machine calculate the most optimal times you can check this equipment without losing time, resources, or work hours.
New Product Design
With the right amount of data, machine learning can help you better understand how a piece of equipment is being used. It will be much easier to analyze conditions under which it performs excellently and the conditions under which it starts getting into trouble.
Gathering all this information, taking into account various circumstances at various times, can point to design flaws, both in the equipment themselves and in your processes.
Perhaps there is a glitch during the manufacturing process that leads to a bottleneck, but only for a couple of times a year. Perhaps the reason behind it is human error, or it might be that humidity during only certain times of the year causes trouble. You might not notice it, but an ML will.
Reduced Waste
With Machine Learning, you can become much more accurate in optimizing and predicting your production schedules, their demands, and their problems.
You may not have noticed that the amount of fuel you have been storing is too much, even for a triple backup.
It’s been hogging up space in your warehouses, and you’ve been wasting money on buying extra. It’s a simple thing to miss, especially if you had significant changes in your operation and equipment, but it’s just money down the durian.
Quality Control
Here is a really sci-fi-sounding example of the utilization of machine learning. A baby food manufacturer incorporated machine learning with Google Vision, letting it scan discolored products. It removed the human element, along with the human error, lowering expenses.
Greater Efficiency, Lower Costs
The favorite word of any manufacturing boss and manager is efficiency. Here is one example – optimizing cooling and heating within a factory.
Instead of doing thousands of complex calculations by yourself (or your team), let the machine handle it. There are times when there is no need to waste energy on heating or cooling a specific area. Perhaps your air conditioner runs an hour too long on weekdays.
Perhaps it can shut off for 30 minutes in the middle of the day and still keep everything comfortable.
These little things add up, especially for larger factories. In the end, they can help you save up a great deal of money.
Robotics
FOr some people, the first thing that comes to mind when talking about not only machine learning but optimizing the manufacturing process. Namely, getting the right machinery can speed up a lot of processes.
One piece of machinery can handle multiple different tasks, things done by an entire team of people. Furthermore, it can do it more safely, with greater consistency. Machine learning can allow this automatization process to become even more complex, handling more responsibility and becoming more efficient.
Conclusion
Join the future and start incorporating AI and ML into your processes. Train your staff, gather and prepare data, and try to implement it in as many areas of your manufacture as you can. The benefits in terms of costs, waste, and efficiency will be well worth it.
Apart from that, if you are interested to know about 6 Innovative Ideas to start a Successful Packaging Business then visit our Business category.
Author Bio
Sophie Douglas is a digital marketing specialist and a journalist based in Columbus, state of Ohio.
Her characters are passionate, innovative, and ambitious.
Before becoming a writer for FindDigitalAgency, she was writing short stories, screenplays, and directing short films.
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