[6A5] Predictive techniques and analytics: experience and expectations in Industry 4.0
T Pyne
Center for Reliability and Diagnostics, India
The importance of predictive techniques, applied independently or jointly, in the health monitoring and assessment of assets (machines or humans), has already been proven in industries. Each technology, whether hardware or software, has evolved over the decades, as per the depth of analysis required to arrive at the root causes of the anomalies, to satisfy the diagnostic requirements in the handling of health data, both quantitative and qualitative, and to interface the requirements of industry-specific reliability and maintenance performance indices. Therefore, the monitoring and prediction tasks, in terms of their applicability, have traced a learning curve. However, unfortunately industries have not been able to reap the results to the extent the proven technologies are capable of providing, possibly due to the mismanagement of knowledge in the inter-disciplinary fields of reliability and diagnostics.
In this talk, the speaker attempts to bring out, in brief, the lessons learnt so far from the ineffective usage of the proven technologies and the present claims made by the overhyped asset analytics in the age of digitalisation and the consequent global industrial disruptions. While narrating the current scenario, the speaker places emphasis on the diagnostic interests and expectations of the owners of industrial assets, and then concludes the topic with some encouraging notes on the merits of analytics.
In this talk, the speaker attempts to bring out, in brief, the lessons learnt so far from the ineffective usage of the proven technologies and the present claims made by the overhyped asset analytics in the age of digitalisation and the consequent global industrial disruptions. While narrating the current scenario, the speaker places emphasis on the diagnostic interests and expectations of the owners of industrial assets, and then concludes the topic with some encouraging notes on the merits of analytics.
