Manufacturing

"What can make big data truly actionable is the discovery and communication of meaningful insights resulting from the systematic analysis of data."

Anser Aly, Senior Regional Brand Development Manager at Unilever

Manufacturing


Manufacturing has made use of methods such as Lean and Six Sigma to reduce waste, improve quality and efficiency. In order to continue these improvements Manufacturing has also enlisted Data Science. Data is being produced at an exponential rate and so is hard to ignore.

Customer data integration and Data Analytics can help improve demand forecasting and optimise inventory replenishment.

Through Network Analysis it is possible to conduct Process Optimisation such as targeting inefficiencies in factory floor space or scheduling production to manage peak energy demand.

With larger adoption of the Internet of Things (IOT) and the lower cost of sensors it is possible to collect data on manufacturing equipment that, when combined with Machine Learning techniques, can provide Predictive Maintenance information. This sort of scheduling can lead to more cost-effective methods of maintenance and reduce unplanned downtime.

Demand Forecasting

Predictive Maintenance

Process Optimisation

Leverage Telematics Data


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Network Analytics

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Predictive Analytics

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