Industrial Automation Magazine India

Intelligent data models help in tracing back problems to its source

Published on : Tuesday 08-02-2022

Sanjay Guhathakurta, Industry Leader, Industrial Products, IBM India.

Which forthcoming advances in technology will impact industrial automation?
Industrial Automation is on the verge of a revolution. An explosion in nextGen technologies like IoT, AI/ML, Edge Computing and AR/VR – are capturing the interests of manufacturing companies all across the globe.
 
How are manufacturing industries leveraging AI/ML? How do automation controllers provide the necessary platform?
Within a plant, data is everywhere – terabytes of data are generated every second. But data has never been a problem – what to do with it has been the question which is of primary interest to manufacturing companies for over a decade. We are living in the times where data, and its usage through predictive modelling is helping manufacturers to make decisions with far more accuracy and without manual dependency.
 
AI and ML need massive amounts of data to be gathered by IoT devices. What strategies do industry plan to collaborate in data collection?
Data capture, be it at the device level, or at the enterprise systems level, helps in building predictive models for operational accuracy. Intelligent data models help in tracing back problems to its source.
 
Data collection can be sourced from multiple sources – machine level data (e.g., vibration data, etc.), through IoT sensors, data generated at MES levels as well as data generated at the ERP level (e.g., inventory levels, etc). Interoperability of data between these systems is also extremely important. Hybrid Cloud strategies are increasingly most manufacturers' choice when it comes to continuous data storage and analysis. The adoption of 5G frameworks at factory premises also facilitate these strategies.
 
How can AI and ML help companies create predictive models, analyse operations, make accurate forecasts and automate supply chains?
Efficient algorithms and neural networks that understand industry nuances, built using AI and ML are influencing decision making for manufacturers. By creating clusters of unstructured data that share certain attributes, ML algorithms are discovering underlying patterns. This is vastly helping in increasing uptime, consistency and quality – thereby improving the overall OEE of machines.
 
The full potential of AI and ML is realised only when the scale of operations is big enough. How can the average SME benefit with their limited resources?
While large manufacturers operate with larger budgets, manufacturers in the MSME segment can leverage predefined AI and ML frameworks. Intelligent Cloud offerings developed for the manufacturing industry and built leveraging industry benchmarks, can easily get manufacturers in the MSME segment to get started in AI/ML adoption.
 
The human element remains critical in deployment of new technologies. How is skill development to be planned in a scenario of not yet mature technological advances?
While there is still a significant difference in the factory automation factors between the manufacturers in Europe and China, verses India, the gap is reducing. Keeping that as an observation, it is important that manufacturing companies invest heavily in training their human workforce towards adapting to factory automation and 'factory of the future'. Understanding the nature of data, the study and intelligent decision-making based on predictive suggestions, are still key manual interventions that every manufacturer would rely upon.

(The views expressed in interviews are personal, not necessarily of the organisations represented)

Sanjay Guhathakurta leads the Manufacturing & Naturals Resources industry in IBM India. An alumnus of London School of Business, Sanjay has several years of experience in working with various global clients in the Manufacturing space, helping them in their journey on Digital Transformation. Sanjay is a passionate public speaker, having represented in various platforms from Chamber of Commerce and Universities. His articles around metals & mining have been adopted by the Ministry of Steel, Govt of India. Sanjay holds 2 Patents in the field of Applicability of Artificial Intelligence in Manufacturing.