Table of Contents
- 1 Artificial intelligence, what for?
- 2 Artificial intelligence and Big Data
- 3 Industrial ERP: how to exploit artificial intelligence?
- 4 Towards new decision-making models?
- 5 What applications in the industry?
- 6 What are the obstacles to artificial intelligence?
Topping this list were Artificial Intelligence (AI or IA) and Machine Learning (ML), which were commented as follows:
“Applied AI and advanced machine learning are giving birth to a range of intelligent implementations, including physical devices (robots, autonomous vehicles, consumer electronics) as well as applications and services (virtual personal assistants, intelligent advisers). These implementations will be deliver as a new class of applications and connected objects capable of providing integrated intelligence for a wide range of mesh devices, existing software, service solutions… ”
It is now possible for ERP software editors to consider adding functionalities using Artificial Intelligence. Indeed, although these are particularly sophisticate and complex technologies, they are within the reach of many publishers who will be able to rely on the services of the big names in Artificial Intelligence.
Like the Cloud model, which allows access to great computing power or storage on demand, computers dedicate to Artificial Intelligence such as IBM will now be able to be interfaced with all types of applications and in particular an ERP software. The end customer will thus benefit from a technology that was previously inaccessible to him.
Artificial intelligence, what for?
Artificial intelligence makes it possible to use computer data to arbitrate situations, make decisions, and automate certain actions.
It is already use in many sectors of activity: for example, in the field of finance; at the heart of an ERP software to sort the millions of emails sent to a company and to prepare standard responses taking into account the obligations legal.
In the area of distribution, visitors can ask questions in natural language and return receive personalized advice on clothing choice.
Elsewhere, a law firm analyzes legal texts and court decisions with cognitive technology that provides answers in seconds.
Artificial intelligence and Big Data
The rise of Artificial Intelligences is largely linked to Big Data, which is its perfect complement.
Big Data captures and stores very large amounts of data, relying on analytic applications, which process the data to make sense of it.
But rather than leaving it to humans alone to analyze these results and draw relevant conclusions that can bring added value; Now possible to entrust it to a machine.
Industrial ERP: how to exploit artificial intelligence?
Since its origins, with the MRP (Material Resource Planning) method in the 1960s and then MRP2 (Manufacturing Requirement Planning) in the 1980s; industrial ERP software has been based on the use of precise company data.
The perfect example is the Net Needs Calculation (CBN) which uses the company’s product ranges and BOMs to accurately estimate manufacturing times and purchasing requirements.
It’s already a form of artificial intelligences!
It must be recognize that the capacities of the ERP are often under (or badly) use; its complexity and the quantity of data that it can produce or collect.
Towards new decision-making models?
Providing an ERP with an Artificial Intelligence capacity would allow it to anticipate, for example, raw material orders; to partially manage production automatically, to suggest improvements in processes, etc.
If we add to this the irruption in companies of Connected Objects, themselves intelligent; and other more restricted but very efficient technologies, such as digital twins, it is undeniable that we are slowly moving towards a supply chain; an ERP, and ultimately an increasingly “cognitive” business.
What applications in the industry?
Drones and robots: from fiction to reality?
The robot is one of the oldest human fantasies: an intelligent machine capable of performing increasingly successful tasks.
What if this fantasy was already a reality?
Their use in industry is nothing new: welding, painting; and assembly robots have been used for many years, particularly in the automotive industry. What changes, however, is precisely the intelligence of these robots, capable of adapting their behavior in real-time.
The example already exists, once again in the general public sphere: autonomous vacuum cleaners
Capable of “learning” the configuration of a room to optimize their movements.
Drones are also experiencing a considerable boom.
Their main advantage lies in their low cost and ease of use, which makes them very affordable in various fields. For example, infrastructure maintenance and industrial expertise; a drone can more easily access difficult or dangerous areas to inspect and detect faults or breakdowns.
Less risk, time-saving, and efficiency: the potential is impressive!
What are the obstacles to artificial intelligence?
Artificial intelligence, although in constant progress, remains a recent set of technologies and therefore still complex to implement. The main obstacle is economic: the mass deployment of artificial intelligence requires very significant investments.
Solid IT infrastructure, massive storage capacity, computing power, all of this comes at a major cost (again).
Industrial ERP capable of using this data and effectively coordinating this new equipment will also require major R&D efforts on the part of publishers.
Another obstacle will be psychological: should we be afraid of artificial intelligences?
Should we allow it to occupy more and more land in our offices and factories?
What will be our place tomorrow in an “AI” world? Complex questions, but one thing is certain: artificial intelligences has not finished shedding ink!