Metals & Mining

Dynamic workforce efficiency tool

Key facts

typically25%reduction in workforce
typically 10%rise in work orders completed by technicians
typically45%less time to location of work order
Next Steps
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Top business benefits

Increases efficiency

Increases productivity

Cuts OPEX

Dynamic optimisation tool that boosts workforce efficiency.

In more detail

Full description

Maintenance issues often holdup production in oil and gas and metal and mining plants. This Dynamic Optimisation Tool (DOT) deploys an algorithm that helps operators to increase the efficiency of their workforce by prioritising maintenance tasks. It allows plants to align the availability of their maintenance operators with their real-time work orders.

Using Big Data and machine learning, the DOT takes into account numerous factors, such as technical skills, average performance in resolving problems, SLA requirements, access restrictions, speed of individual workers and work permits. The DOT also uses predictive traffic algorithms and internal data, such as the average number of work orders resolved by a particular maintenance technician. It then uses these analyses to improve the efficiency of field work, while helping operators to identify areas for improvement. This solution significantly reduces holdups in the production process while boosting overall production and cutting costs.

The challenge

Maintenance issues often holdup production in oil and gas and metal and mining plants. Poorly timed maintenance causes falls in production and delivery delays and can even lead to plant shutdown. This Dynamic Optimisation Tool (DOT) deploys an algorithm that helps operators to increase the efficiency of their workforce by prioritising maintenance tasks. It allows plants to align the availability of their maintenance operators with their real-time work orders.

Using Big Data and machine learning, the DOT takes into account numerous factors, such as technical skills, average performance in resolving problems, SLA requirements, access restrictions, speed of individual workers and work permits. The DOT also uses predictive traffic algorithms and internal data, such as the average number of work orders resolved by a particular maintenance technician. It then uses these analyses to improve the efficiency of field work, while helping operators to identify areas for improvement.

This solution significantly reduces holdups in the production process while boosting overall production and cutting costs.

The approach

This Dynamic Optimisation Tool (DOT) deploys an algorithm that helps operators to increase the efficiency of their workforce by prioritising maintenance tasks. It allows plants to align the availability of their maintenance operators with their real-time work orders.

Using Big Data and machine learning, the DOT takes into account numerous factors, such as technical skills, average performance in resolving problems, SLA requirements, access restrictions, speed of individual workers and work permits. The DOT also uses predictive traffic algorithms and internal data, such as the average number of work orders resolved by a particular maintenance technician. It then uses these analyses to improve the efficiency of field work, while helping operators to identify areas for improvement.

This solution significantly reduces holdups in the production process while boosting overall production and cutting costs.

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