Artificial intelligence has brought about a change in the pattern of the operation of industry, driven by a new form of interaction between man and machine. This industrial revolution, which has given rise to Industry 4.0, is characterised by intelligent factories where humans and cyber-physical systems interact in the cloud.
Intelligent factories absorb automated structures and include digital enablers that allow machinery to communicate with each other and with the factory systems as a whole, through a IoT configuration. These skills are increasingly in demand by factories in all sectors, seeking to ensure the competitiveness of their production plants in an increasingly technological context.
AI applied to industry 4.0
Artificial intelligence has become the most disruptive technology called to revolutionise the management and business models of organisations. Its main applications in the 4.0 industry are:
- OEE optimisation through predictive repair and maintenance.
- Quality 4.0 through operational excellence, which continuously improves production quality.
- Generative design through AI and automation algorithms, which simultaneously generate multiple design solutions valid for the same objective.
- Robotics through robotic and collaborative machines that support the operators to free them from methodical and/or extremely precise tasks.
But who operates these machines that run on algorithms? This type of functionality will only express its value if the human capital is trained to work with processing, programming and data systems. Companies must invest not only in technological capital but also in training employees to be qualified.
Impact of AI on industry 4.0
- The shift from traditional automation based on independent industrial robots to networked ‘cyberphysical systems’ has revolutionised the way production plants work and imposed new standards of competitiveness on the market. This has brought a number of benefits to producers and consumers, including the following:
- Just-in-time manufacturing: Adapted, real-time production models have reached a new level of optimisation. These AI-driven manufacturing systems can produce pieces in an adaptive way to the order. Sensors track components by ordering them according to demand patterns and algorithms to shorten lead times.
- Introduction of new products: Production lines become information systems that feed decision making on issues as central as the product line. This facilitates adaptation to demand, making it easier to change from the raw materials entering the factory process to the final product leaving it.
- Changes in consumption: One of the biggest changes in mentality has occurred between assets and customers. Consumers are connected to the industry through information networks and expect products and experiences of a higher quality and level of personalisation. On the other hand, manufacturers are able to produce customised products without losing efficiency thanks to digital designs and intelligent production.
- Labor market evolution: The learning curve of AI techniques is slow and yet AI advances at an unstoppable rate. This makes titles such as ‘Data Scientist’ increasingly in demand. The labor model is moving towards more analytical and qualified applicants in the field of technology, so it is essential that governments invest in education, a factor increasingly key to mitigate unemployment.
Meaning of AI for industry 4.0
Artificial intelligence sharpens business intelligence, which is an important advance for the global economy. According to an IBM study entitled “The Global Race for AI”, 82% of Spanish companies are already exploring the use of AI. AI allows factories to scale up their production models without compromising process quality, which is essential given the growing competitiveness in the market.
AI techniques such as machine learning (ML) and deep learning (DL), if well implemented, have very significant positive effects on companies’ ROI. Automatic learning vastly improves product quality by introducing predictive maintenance systems into production processes, replacing visual inspections with robots or cobots that execute quality controls infinitely more accurately and efficiently.
In addition, ML creates sophisticated algorithms that enable ‘Smart Manufacturing’; data gathered during production is analysed and changes are automatically adapted. Deep Learning, a subset that has evolved from Machine Learning, creates its own neural networks that allow for unsupervised learning, taking the autonomy of these methods even further. These AI techniques give rise to three fundamental benefits for the industry 4.0:
- Production optimisation
- Supply Chain Integration
- Company‘s adaptation to the market
- Better product development
However, the complexity of AI use in industry 4.0 requires manufacturers to collaborate with specialists to achieve appropriate and customised solutions. Building the necessary technology has very high costs and requires in-depth knowledge both internally and technically.
Your driving tool in industry 4.0
Nexus Integra, Big Data’s integrated operations platform, partners with your company to know your goals and create together a clearly defined roadmap with an agile and customised development process. The industry 4.0 advances at a frenetic pace and so do the new technologies that form it. Therefore, our goal is to guide you so that implementing these technologies is a simple process full of value for your business.
To guarantee your competitiveness in the industry it is essential to have your data connected and your industrial processes integrated. If this is not already the case for your company, the IOT Nexus Integra platform, leader in industry 4.0, will be the technological ally that will convert your traditional factory into a smart industry, so that you can extract all the value and potential from your data and achieve the maximum level of efficiency and productivity.
