Automating IT Service Management in Manufacturing: A Deep Learning Approach to Predict Incident Resolution Time and Optimize Workflow
Keywords:
IT Service Management, deep learning, incident resolution timeAbstract
Industry Increased human engagement, poor procedures, and sluggish problem resolution plague ITSM. Manufacturing firms need modern ITSM to boost efficiency and reliability. Deep learning improves industrial ITSM and predicts incident resolution time, research indicates. With accurate projections, deep learning models prioritize and allocate IT event management processes. IT teams can manage major events faster and more accurately by enhancing operational continuity and response times.
Implement these predictions into ITSM procedures to improve efficiency, then build a deep learning system to forecast industrial IT issue response timeframes. Industrial enterprise IT event data trains LSTMs and RNNs. Sequential data helps explain and forecast patterns, hence these models are employed. Predictive ITSM analytics cross-validates models against random forests and decision trees.
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