Cognitive Predictive Maintenance (CPdM) in Transportation is focusing on targeted servicing and monitoring. Against this background, transportation companies are looking for new and improved ways to reduce downtime and make the best possible use of available resources and also to reduce cost. Below is the reason why a Transport industrial need to use Cognitive Predictive Maintenance (CPdM) in their system.
Transforming transportation and logistics safety
With the trove of data from IoT comes an opportunity for safety managers: They can leverage information with predictive analytics to better keep employees safe on the job. The Internet of Things has provided the transportation and logistics industry with an escape from the norm. Estimations and educated guesswork are no longer the fundamentals of making operational improvements (for example, thru IoT sensor and automation provide information such as speed, location, threshold, weight for automate calculate and make the automated operation decision) . With this trove of data comes an opportunity for safety managers: They can leverage information with predictive analytics to better keep employees safe on the job.
Transporting and Accounting
Implementing AI in transportation can help reduce the burden on logistics accounting teams (which in turn bring down operation cost). Many providers in this industry cooperate with third-party vendors to ensure safe and high-quality transportation processes. It results in a large number of invoices and other documents that a logistics provider’s team has to deal with AI-based systems and natural language processing (NLP) technologies can assist in working with massive volumes of unstructured data and extracting critical information on received billings, addresses, dates, etc. Among other things, the use of technologies to automate accounting tasks significantly contributes to security.
Targeted Servicing and Monitoring
Against this background, transportation companies are looking for new and improved ways to reduce downtime and make the best possible use of available resources. Regularly scheduled maintenance, where equipment is serviced within pre-defined windows, has its limitations. It is geared to typical experience, with a generous safety margin, not to actual wear and tear. One effective answer is preventative maintenance to the monitoring of assets and targeted servicing in response to detected anomalies (so can proactive prevent the downtime happen in the first place, which directly boost the up time).
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