Whether you are a small or huge production company, every factory in the manufacturing and process industry can make enormous strides through Artificial Intelligene (AI) to improve production processes in reliability, accuracy and safety! This is not only in the production processes themselves, but also in the business processes that are necessary to transport or sell your goods.
Narrow down your business processes such as inventory management, warehouse management, delivery reliability and product quality.
In the United Kingdom (UK), different companies are already working together and helping each other to make artificial intelligence possible for the manufacturing and process industries. The KEEN consortium, a collaboration of 25 companies in the manufacturing and process industries, states that “Products and processes are becoming more complex, so engineers need advanced tools to manage that,” it says. KEEN does not see artificial intelligence as a possible alternative to the deployment of engineers, but as an instrument that can assist them. ”
51% of the largest European manufacturers are now working on at least one artificial intelligence assignment. To date, this has made Europe a forerunner in artificial intelligence in the manufacturing and process industries. There is often an enormous amount of data available. There are often a lot of sensors. That is why companies such as Siemens have been investing in artificial intelligence for years. Current models work but are static models. These can be greatly improved by using artificial intelligence in the manufacturing and process industries. You can therefore think of modeling and analyzing processes, products and / or machines / installations. Furthermore, artificial intelligence can support engineering and in the long run, artificial intelligence can autonomously control processes.
In 2017, there were only 10,000 people worldwide in the artificial intelligence industry, 95% of whom worked at the huge multinationals such as Google and Amazon. This means that only 500 people in the free sector worked on artificial intelligence. There are already a few more, but still too few to allow the other industries to catch up.
Because artificial intelligence will change business addresses so much, rules have already been put in place by the U.S. government to curb acquisitions of U.S. AI-related companies by Chinese companies (and this was for Trump ..)
The English parlement also sees that it is very important for our country to be a technological leader in artificial intelligence. That is why in recent years there have been training courses and she wants to double the investments in artificial intelligence and is allocating about 1 billion euros to achieve this. The cabinet has also issued a special action plan for intensive public-private partnerships and investments for artificial intelligence.
Nevertheless, several large companies indicate that the United Kingdom (UK) is missing the ‘boat’ with artificial intelligence and are sounding the alarm. We are not going fast enough!
So time for action !!
Supplai understands that every company has and works on a core ERP system. The terms AI, artificial intelligence, robotic process automation (RPA), artificial intelligence and perhaps machine learning or deep learning (read more about it via the links in our blog) can therefore be an elusive and difficult to understand technique. Because how do you connect this now?
We believe that you should organize your organization step by step, process by process, on the use of artificial intelligence and thus improve your business processes.
Our solutions therefore also connect seamlessly to the systems that already run at your company. Think of it as a new app on your phone! We just add something.
In the text below with examples with artificial intelligence for the manufacturing and process industries, get inspired about what your company should look like within 5 years.
– Learn to make the machines or robots the perfect product using algorithms.
– With overarching algorithms that control these machines or robots, it is even possible to learn where probable problems will arise by combining all data. So have less downtime. Worldwide, the cost of unplanned plant downtime is estimated at 50 billion a year!
– Change an existing product faster than ever. Take Tesla as an example. They are constantly updating their existing cars by using artificial intelligence in both design and factory control.
– More and more use is made of sensors. Connect all this data to algorithms and learn a lot about your factory and make your products more efficient in both time and use of raw materials. According to Mc Kinsey, ‘smart factories’ are worth 1.2 to 3.7 trillion more through material and operational optimizations worldwide!
– Made products also have to leave the factory. Use logistics warehouse management systems linked to artificial intelligence from supplai for this. The logistics costs are now an essential part of the cost price!
– Specifically for the chemical and petrochemical industry, many sensors are already present. Many regulation models are static and a lot of data is not included. What happened in the same situation 4 years ago and what were the temperatures in other columns or even outside that day? Artificial Intelligence makes all these models dynamic and can predict much better than the current models.
Within Engineering there is heavy building on data sets and artificial intelligence lends itself perfectly for this.
– Algorithms can read pictures or drawings the way you want.
– Faster design using Artificial Intelligence. Algorithms can also learn to make suggestions for a design. This is now also known as generative design
– Design the cheapest product. Use our algorithms to answer the question, how can you make the best design with the least cost and the least waste?
– Algorithms can then release calculations, make part lists or make analyzes of the design. Airbus, among others, uses this in their designs.
There is nothing more precious to a company than material that breaks during an assignment. Use artificial intelligence to reduce this. Predictive maintenance or ‘prevention is better than cure’. Some examples:
– Detecting and analyzing damage is already difficult and takes a lot of time. You can predict maintenance with our algorithms
– If you want to go a step further than predicting maintenance, you can combine it with cameras that detect damage and determine together with the algorithm whether the damage should be remedied or not. This way you prevent it from breaking down and this ensures that your trucks or equipment are stationary less often.
There are many repetitive processes in the financial department that involve data. Here artificial intelligence is well suited to analyze large amounts of unstructured data or to take over tasks.
– If you want to have incoming invoices automatically read and placed in the system, you can do this with our algorithms.
– Algorithms can help you determine your foreign currency overviews. When do you need which currency in response to debtors and creditors in your system
– Start steering even more on KPIs and let algorithms help you with this. Or to make unstructured data transparent and structured and / or even have analyzes made so that you only have to look at it!
Commercial data is often very unstructured and decisions are often made based on intuition. How do you ensure that you make the right predictions based on history? Some examples:
– Predict demand and price trends and use all internal data in combination with our algorithms to make good predictions and analyzes. This allows you to manage your company more efficiently and respond to the right movements.
– Do you receive many prices from suppliers by email? Have this automatically read into your system and are therefore always up to date! Avoid using higher prices or wrong old quotes from your suppliers.
– If you want to take this a step further because it is an important process within your organization, let suppliers analyze prices and identify trends.
– Let our algorithms calculate quotations and predict what other customers should be prepared to pay for your service or product based on other internal data (such as margin per customer).
We must have forgotten some examples.
This is also just a selection of what Artificial Intelligence can do for your organization.
One thing is certain, Artificial Intelligence within the manufacturing and process industry is the future!