The Operations business function is currently being disrupted by Machine Learning and AI. Inventory and supply chain optimisation algorithms are able to automate and optimise the inventory management process to minimise loss of profits and storage costs. In addition, predictive maintenance models are able to forecast unscheduled equipment downtime based on historical patterns – in effect reducing downtime, maintenance costs, and increasing operational efficiency.
Logistics Control Tower operations are utilising the power of technologies to get new insights for the improvement of warehouse management, collaboration, logistics, supply chain management.
Machine learning can analyse timings and handovers as products move through the supply chain. It can compare this data to benchmarks and historic performance to identify potential holdups and bottlenecks and make suggestions to speed up the supply chain.
The advent of visual pattern recognition has changed the support of physical assets across the supply chain network. Inspection of the inbound quality has also been automated by Machine Learning with the help of algorithms, isolation of product shipments, logistics hub. Efficient supply chains rely on products being in the right place at the right time. Machine learning can assess customer requirements and optimise the upstream supply chain. It matches the timely supply of goods with marketplace demands.