31: intelligent wing for service
In the traditional industry camp, 31 always seems to reveal a "living in the future" temperament. It has become a normal for this enterprise to build an overseas factory, create an e-commerce platform, and cross border insurance.
In 2014, 31 started the construction of large data platform to achieve the low cost and massive equipment data access and analysis. Based on this, 31 not only inserted intelligent wings for its own services, but also made the design side have a powerful way to understand the defects and risks of device performance.
Improving the safety factor of truck crane based on large data
For the lifting equipment, the firmness and efficiency are very important. In order to guarantee the strength, safety factor need sufficient, however, the use of this value and materials are positively related. This means that if we want to increase the coefficient, we will increase the use of materials. The more materials we use, the higher the manufacturing cost will be, and accordingly, the cost of customer purchase will also increase. If the material is added sturdy, the weight of the crane will be increased and the efficiency of the crane will be affected. So, what is the most appropriate factor for this coefficient? With the help of large data, 31 perfectly solved the problem.
By collecting data, 31 not only understands the real-time operation of crane, the information of the devices themselves, but also grasps a common problem of customers in the process of using cranes: overload. With these data, 31 can design an optimal mild coefficient in the product development stage, so that it can remain reliable and efficient under the premise of overload.
If there is no big data
Before big data is available, sampling or collecting some customers for conference research is a common way to get data, but this operation has drawbacks. In order to improve the safety factor of crane as an example, either sampling or the meeting research, can get the data is limited, and even a crane driver personally involved in the investigation, the existence of his habit of overloading is unknown, even if he has his own habit of overloading, overloading for numerical whether can achieve one hundred percent accuracy is unknown. That is to say, the data obtained, both in quantity and in quality, seem to be incompetent.
The data tend to be full sample, suggesting that the customer is accurate
Under the monitoring of large data, the data samples will tend to be full sample and high precision. In addition to providing information for the design end, this precision can also be given precise advice when the client intends to buy a machine. For example, if a client wants to buy a excavator for rent, then he needs to know first what kind of excavator is easier to rent in the current market situation. Is it a big dig, a middle dig or a small dig? The message is one-sided if the client asks, and is restricted by the individual circle. 31, relying on the data provided by big data, we can not only know which excavator market is the best, but also predict the future market situation, so that we can give customers precise suggestions so as to facilitate customers to get better profits.
"Frontier" in the industry, the words used to describe exactly 31 however, as a traditional leader in the industry, 31 has never stopped the pace of exploration, believe that the exploration and practice of big data, will also give the industry to bring some new inspirations, leading the industry into a new era!