Artificial Intelligence changing industries and creating new operational management systems
The production of today is supported by a huge amount of information. It is beyond human capabilities to process the growing data flow and make quality decisions under time pressure. Fortunately, this task can be delegated to Artificial Intelligence (AI) combined with other Industry 4.0 technologies.
So far, AI has been implemented by as few as 9% of enterprises (source: PwC). However, the application range of this technology is enormous: from reducing production to minimizing human errors. In this material, we will provide a detailed overview of how AI is already applied and can be used in industrial manufacturing.
Organizing unstaffed production
Industry 4.0 has created new opportunities for industrial automation. Now it is possible to involve tech tools in planning, decision-making, manufacturing and others.
This change aims to save resources – not only by minimizing the need for staff but also through eliminating the human factor. AI cannot get tired and continues operating 24/7 without performance losses at any time of the day.
Big Data analysis
Dashboards are now used by many companies as a visual display of the current situation at the enterprise that can be analyzed within a minimum time. Still, the effectiveness of decisions made in this case is limited by the number of metrics taken into account.
AI does not have such constraints and can undertake to analyze bigger data volumes. In fact, this is a technology capable of real-time data collection from billions of various endpoints.
Analyzing such data promotes quick and optimal decision-making. It also helps to simulate several possible scenarios on a larger scale – in particular, by factoring in external events and less obvious risks.
One-size-fits-all products are becoming a thing of the past. Not only are В2С markets raising the demand for diverse, customized offers, but this trend is also observed in B2B, now a buyer market.
Again, AI comes in handy with its ability to quickly design new products, test them in the virtual environment (Digital Twins), calculate the required amount of resources and optimize production planning. In the future, AI is expected to take on all market-entry operations and minimize human involvement.
A combination of Machine Vision (MV) and Artificial Intelligence enables enterprises to achieve a totally new level in quality control.
Firstly, digital solutions experience no such thing as fatigue and demonstrate constantly good results in detecting anomalies, deviations and issues.
Secondly, MV can notice even the slightest defect that would otherwise manifest itself much later (for instance, when the product is already in use).
Next, early detection of defects saves time and resources that would be wasted on further manufacturing of a product that does not meet user requirements.
Finally, Big Data analytics allows AI to predict possible defects. Similarly, this functionality proves useful in another area – Predictive Maintenance.
Predictive Maintenance is the most cutting-edge and efficient methodology in equipment maintenance. It forecasts equipment failures, thus reducing downtime and improving equipment availability.
This is made possible by analyzing big data serving as the basis for each assembly’s profile. Rather that warranty periods (and unlike preventive maintenance), it focuses on the data obtained from real user experience and interactions with the environment.
If there is a possibility of a component failure, AI issues an alert in advance. So, there still remains enough time left to prepare: say, place an order for the required part. At the same time, the predictive approach frees up warehousing space as it is no longer cluttered with parts and assemblies “for a rainy day”.
Organizing a safe workplace is another essential capability of AI. Along with managing work in hazardous conditions, it can ensure compliance with anti-COVID-19 regulations: in particular, checks an employee’s temperature, plan safe routes, and a lot more.
In the times of the COVID-19 pandemic and a shortage of qualified staff, many experts are labeling AI as a blessing for businesses. It has already proven effective: here is a case study from a cement company, or an example of adopting AI in agriculture from a Ukrainian business. Likewise, other industries also benefit from this technology.
The years to come will see the development of new AI-based operational management systems. They will help increase productivity and boost profits in normal periods, whereas during a crisis, they could also maintain sustainable and flexible production.
Yet there is no reason to fear that Skynet will rob human workers of their jobs and make them redundant. On the contrary: employees will get broader opportunities, get new positions (for example, a system learning assistant) and get rid of the routine. Companies, in turn, will satisfy the market demand more efficiently, enhance safety and go green.