Artificial Intelligence (AI)

Solution offerings for tansforming manufacturing industry by introducing Artificial Intelligence and Machine Learning in production. By creating new ways to automate tasks, we can rebuild the way people and machines live, interact & collaborate, to make a superior, stronger digital economy.
Why is AI important in the manufacturing industry?

Artificial intelligence plays a significant role in manufacturing. Companies utilize artificial intelligence platforms to make data-driven decisions that reduce plant downtime and save them hundreds of thousands of dollars in production.

The volume of data generated within manufacturing is enormous, but there is little point in gathering it all if it will not be used to gain information. For example, in a factory the engineers and operators know how their machines are operating, if machines are suddenly consuming too much power, or if they’re headed toward a malfunction. Proactively noticing indicators, such as temperature and pressure, and acting on them can prevent costly downtime.

AI and machine learning were made to analyze chnnels of information, identify the trends within them and enable business leaders to make more informed decisions faster.


Benefits of Industrial AI and Machine Learning in Manufacturing

Quality Assurance

Predictive Quality and Yield automatically identifies the root causes of process-driven production losses using continuous, multivariate analysis, powered by Machine Learning algorithms that are uniquely trained to intimately understand each individual production process. Automated recommendations and alerts can then be generated to inform production teams and process engineers of an imminent problem, and seamlessly share important knowledge on how to prevent the losses before they happen.

Preventative Maintenance

Instead of performing maintenance according to a predetermined schedule, alert rules and configurations, predictive maintenance uses algorithms to predict the next failure of a component/machine/system. Personal can then be alerted to perform focused maintenance procedures to prevent the failure, but not too early so as to waste downtime unnecessarily.

Predictive Forecasting

Artificial intelligence platforms can manage the entire supply chain And predict any shifts in demand that can affect your production or distribution processes. The goal is to have a proactive strategy to satisfy demand rather than reacting after the fact. The data gathered from sensors and beacons helps to determine consumer activity, allowing companies to anticipate future needs and make rapid decisions on production, as well as speeding up the exchange between manufacturers and suppliers.

Enhanced Monitoring

Programmable logic controllers with AI capacity for deep learning can then respond automatically to the seamlessly generated information, and make alterations to the minutest function without recourse to human intervention. The big data analytics processed by AI can substantially improve performance across the entire production process, and can be operated remotely.

Industrial AI will continue to transform the manufacturing sector

Artificial intelligence is a game-changing technology for any industry. As the technology matures and costs drop, AI is becoming more accessible for companies. Every day we see the continued development of new technologies, new applications, and greater investment in AI and Machine Learning. The manufacturing sector is a perfect fit for the application of artificial intelligence. Even though the Industry 4.0 revolution is still in its early stages, we’re already witnessing significant benefits from AI. From the design process and production floor, to the supply chain and administration, AI is destined to change the way we manufacture products and process materials forever. With AI adoption, they are able to make rapid, data-driven decisions, optimize manufacturing processes, minimize operational costs, and improve the way they serve their customers.


Top AI use cases

Artificial Intelligence Will Change the World in Future

  • Predictive Analytics
  • Real-Time Operations Management
  • Customer Services
  • Risk Management & Analytics
  • Customer Insight
  • Pricing & Promotion
  • Supply Chain
  • Customer Experience
  • Fraud Detection
  • Knowledge Creation
  • Research & Development
  • Human Resource Management