Industrial IoT: Give machines more IQ
June 01, 2018
Augment your machines with artificial intelligence and sell a production performance improvement community to your customers.
New business models are enabled by industrial IoT, making machines smarter and augmenting the knowledge of operators.
The reconfigured value chain enables new collaboration possibilities between machines and humans to increase production uptime, adapt to demand versatility, comply with regulations and mitigate intermediation risks.
It is a huge opportunity for industrial companies who have not yet started to harvest the potential of the new technologies.
OptimData is TechniaTranscat’s joint venture that focuses on ways to help customers move to industry 4.0. It develops applications based on connected devices, data science and machine learning.
What if machines could talk?
ProductInUse is a Software-as-a-service that can connect to many data sources and combine data from enterprise data silos (CRM, ERP) with IoT data in one application.
It consists of two innovative pillars. On one hand, it is a design automation application for artificial intelligence (AI) of connected equipment.
Based on machine data and data science tools, system expert engineers can diagnose, design, simulate and publish the AI of the equipment.
The user is assisted to manipulate data and to create advanced algorithms. As a result, the AI teaches a language to the equipment for it to interact with production stakeholders.
On the other hand, a community of connected performance joins people and equipment for a single objective of production performance.
The equipment behaves as a friend of the operators, talking, predicting maintenance, suggesting the next best actions, anticipating failures and shortening the time to repair.
internet of things productinuse
Shorten time to repair
By internalizing the collective intelligence into the AI, the equipment can identify, in its own context of production, the best next action to repair and restart.
About 50 percent of the MTTR “Mean Time to Restart” can be saved enabling up to 3 percent increased OEE (Operating Equipment Efficiency) and a significant topline revenue increase.
Anticipating failure
Predictive analysis can be built on critical components of the equipment.
The AI is created via an algorithm that characterizes the physical issue. When triggered, it makes the equipment communicate before the failure. This digital service realizes huge savings at production sites.
It produces a redefinition of the service engagement between equipment manufacturer and user, with direct topline direct topline effects for both parties.
Tools for Industry 4.0
Source:
https://www.techniatranscat.com/blog/industrial-iot-machines-iq
