What are your machines telling you? You have probably heard the term “machine learning” several times over the last year. We hear that it is now an essential element that will revolutionize every aspect of supply chain and facility management.
But what is machine learning? Its definition is as clear as it sounds. Software platforms merge what machines “experience” and patterns that emerge with advanced analytics, IoT sensors, and real-time monitoring. The partnership provides answers based on insight versus guesswork. This means for the first time there can easily be end-to-end visibility.
How telematic machine learning revolutionizes a warehouse
With increasing demand for speed, quality, accuracy and transparency, many sectors of the supply chain industry require an entirely new operating platform structured on real-time data, enriched with patterns and insights not visible with previously available analytics tools.
Machine learning oversees and shapes the daily warehouse operations for many companies, creating:
- Intelligent warehouses – with increased tracking of operator patterns, order picking, inventory monitoring, and just-in-time deliveries
- Communication - all systems can “talk” to each other; combined information supports improved timing and routing, product location, and traffic patterns
- Integration – telematics systems that partner with other SMART systems; increased efficiencies result as they monitor and track behaviors within the warehouse environment
- Increased indoor locationing capabilities – systems will become much more “context aware,” able to locate inventory (down to the foot) and suggest optimum forklift routing to find the shortest paths or paths of less congestion
- Tailored operational parameters – forklift parameters based on location, battery charge state, presence of other vehicles, physical conditions at current location, historical performance and predictive calculations, etc.
The big benefit – where the ROI resides
By identifying new patterns in usage data collected via IoT sensors, companies are extending the life of their assets, including warehouse machinery, forklifts, and the batteries that power them. This cut costs tremendously while boosting efficiency.
Machine-derived data has become invaluable in determining which causal factors most influence machinery performance and operational costs. This includes:
- Maintenance and repair schedules that support safer operation, less downtime, and increased productivity
- Battery care and proper charging that extends battery lifespan
- Operator behaviors such as skill level, recklessness or excessive speed. Software that learns operator patterns assists in safer equipment usage and a better understanding of how and why impacts occur.
Advanced telematics platforms facilitate machine learning through matching patterns, providing digestible, easy-to-use data insight in real time. So, warehouse managers across the supply chain industry can take a proactive role and accurately determine how to meet the challenges of supply and demand, while predicting and reducing costly mistakes.