Virtual Reality And Smart Machines Work Towards Zero Equipment Downtime In Oil Machinery
Man and machine are at a crossroads. Machine learning and artificial intelligence are making machines smarter. These advances have raised the question of whether machines are ready to take on more of the human cognitive load. Practically, the day when offshore oil ghost rigs will operate on automation alone is still a scene in a science fiction novel.
The focus of automation is not about dumbing down intelligence to machines. But rather, automation is about expanding and interconnecting intelligence across the value chain. With the aid of virtual reality, the oil and gas environment can be simulated, improvised, and continually reinvented.
This interconnectivity creates new predictive maintenance capabilities. The IoT (Internet of Things) network provide an unprecedented level of insight into the operation of machinery at the part and component level. At the heart of automation are hundreds, if not thousands, of control systems and connected devices. When onsite engineering and maintenance are connected to the oil machinery part manufacturer, offshore oil rigs can produce continuously.
The All Knowing, All Seeing Virtual Plant
Predictive maintenance is one way automation is improving productivity and lowering costs in asset-intensive industries. Predictive power is increased when plants, machinery, and control systems are connected to virtual plant software. Data from equipment design to oil machinery part manufacturing can inform whether and when a component is replaced. Oil machinery part manufacturers become part of the just-in-time loop to minimize costs and keep machines operational.
Cloud layers interoperate. Enterprise resource planning connects all departments via the cloud, from product ideation to manufacturing. Production can be controlled in real time according to changes in market demand and supply. Data can be shared across departments and virtual plants.
Zero Equipment Downtime
At product ideation, virtual reality provides information on how oil machinery will function. This insight reduces equipment problems in the field. Once in operation, the system collects thousands of data points at the equipment, parts, and components level. This intelligence creates powerful preventive maintenance capabilities.
With sensors and virtual reality, engineers can time and imagine the degradation of an oil machinery part. As the part's end of life approaches, the system automatically orders the part from the oil machinery part manufacturer. Before production can be affected, the oil machinery part is replaced.
More data collection points provide more accurate simulations using feeds from real time and historical data. These predictive analytics improve virtual plant optimization. Output can be increased while improving quality and reducing errors. Data from these improvements then inform which processes to digitize next.
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