Page 8 - TCExpression TATA Consulting Engineers Limited

08

State of the matter- ✔ Automation, sensors and controls are either obsolete,
require manual interpretation or are difficult to upgrade
A checklist and modernise.

✔ Several original equipments are very old and historical
✔ Disparate assets with varying capabilities resulting in data on the asset may not be available. Lack of
sub-optimal operations excellence. centralised data and/or data analysis results in increased
maintenance or unplanned downtimes which can prove
✔ Old assets following old operational techniques, co-exist expensive.
with newer assets with automated process. Net result is
a disparity in asset capability within various production ✔ Industry 3.0 brought about connectivity and automation,
facilities within a single organisation. This raises however, plant assets are still not optimal as adoption of
concerns on safe and optimal operations and rising cost 4.0 technologies have been slow. This results in sub-
of unscheduled downtime. optimal performance of assets due to lack of accurate
prediction of asset downtime and asset life cycle
✔ There is an increasing onus arising from climate management.
change concerns and the need to smarten legacy
systems to function optimally as per newly established ✔ Some advanced industries such as the Oil & Gas industry,
compliance standards throws up an impending need automobile sector, to name a few, do have upgraded
to upgrade current plant assets. technologies – both in hardware and automation
systems. The question remains – have these sectors
✔ Various production facilities within a single entity moved from predictive analysis of the data output to
function as silos and best practices cannot be proactive and prescriptive analysis and algorithm - based
replicated across the plants due to lack of asset data decision-making? This is pertinent, since modern IIoT
analysis. Much of the data generated in the modern enables operational excellence through prescriptive
systems do not add up to business benefits. decision - making tools that completely eliminate risk of
human error and lead to operational excellence.