The number of devices connected to the Internet of Things per second will reach 63, or 5.5 million per day. It is expected that the Internet of Things market will reach the scale of 100 billion in 2015-2020. Xively analysis of the Internet of Things PaaS platform shows that by 2020, there will be 40-80 billion devices connected to the Internet of Things, of which government equipment will account for at least 7.7 billion, with a total value of about 2.1 billion US dollars. The estimated return on investment is 4.7 billion US dollars. There will be 10 IoT devices.
How to avoid being overwhelmed by IoT dataWith such a large market size, many companies are struggling to cope with the challenges. Although big data analytics is the primary driver for IoT deployment, companies are inevitably at risk of being overwhelmed by data. On the one hand, companies don't know how to deal with huge amounts of data so that they can make better use of the value that is not wasted data; on the other hand, companies try to distinguish which data is beneficial and which data is redundant. This is often difficult.
At the LiveWorx2016 conference, Harvard Business School professor Michael Porter, PTC CEO JamesHeppelmann and iRobot CEO ColinAngle discussed how the company should adjust to the massive data generated by the Internet of Things. Its customers, value chain and organizational structure strategy.
Data troubles
As more and more products are embedded in IT technology and have the characteristics of smart interconnection, the data generated in real time, the capacity and the variety of the types are unprecedented. The format of these data is varied, including sensor data, geographic location, temperature, transaction and Warranty record, etc. Factories, marketing, sales, and the product itself are generating data streams, and everyone is learning how to get value from such huge amounts of data.
PTC Senior Presales Director Dr. Ji Fengwei said that big data analysis brings a series of new technical tools to help companies master these rules; however, the challenge for enterprises is that the data generated by the smart connected products themselves and related internal and external data are often They are all unstructured.
Dr. Ji gave detailed examples to illustrate the troubles caused by the data. Traditional data aggregation and analysis tools, such as spreadsheets and database tools, are incapable of managing such complex data formats; on the other hand, the amount of data produced by product associations is enormous. For example, GE installed hundreds of sensors on the aircraft engine. Based on the collected data, the company can analyze the actual performance of the engine and the expected gap to further optimize the engine performance. All next-generation GEnX engines will retain all operational data for each flight. And will be transmitted from the aircraft in real time. Such an engine will generate more data per year than all the data in GE's previous history.
PTC CEO Jim Heppelmann pointed out that in order to meet the requirements of these data streams, engineering technology must be updated. Engineers already know about mechanical, electronic, and even embedded software, but they don't yet understand the key factors that cloud architecture, security technology, and other smart connected products can succeed, and that requires IT to get involved.
How should companies respond?
According to Dr. Ji, enterprises want to better handle IoT data, not only need the support of new technologies and solutions, but also need to change from within the enterprise, including organizational structure and business model to adapt to this change.
As data capacity, format, and management requirements have changed dramatically, a solution called DataLake is becoming more popular, storing various data streams in their original format. In the data lake, people can mine these data with a series of new data analysis tools.
In order to better understand and apply the data generated by smart interconnect products, some companies have begun to apply a new technology called "digital map" (digitaltwin), which is actually the digital copy of 3D virtual reality of physical products. Physical products continue to operate, their state and operating environment are constantly changing, and the digital mapping of products is accompanied by the inflow of data to constantly reflect changes in actual products. As the digital incarnation of the actual product, the company can control the product status and environmental conditions thousands of miles away. Digital mapping also provides new product insights to help companies better design, manufacture, operate and maintain products.
In addition, in addition to the construction of the technology foundation, enterprises must also change the organizational structure, collaboration methods and governance structure to apply the challenges of the data age, such as the establishment of a dedicated data management department, the integration of research and development and IT, and the establishment of data security mechanisms. Wait.
How to make data more beneficial?Harvard Business School professor Michael Porter said: "Smart Connected Products brings us a treasure trove of data that stores the most valuable data that all companies are dreaming of. We can learn about the operation of the product - is it working? Is it open or closed? Is it malfunctioning? What kind of failure is it?"
“The ability of companies to leverage data and leverage the full value of their data will be a key source of competitive advantage for the company,†said Dr. Ji. If we want to make the right judgment, we must ensure that we can extract value from the data. Although the information captured by individual sensors is also valuable, if companies can collect information on hundreds of sensors on different products over a long period of time, they will identify certain operating patterns and obtain extremely important product insights.
At the same time, the application of big data can greatly expand the boundaries of products and product differentiation capabilities. The goal of smart thermostat manufacturer Nest is to lead in improving energy efficiency and reducing energy costs. Therefore, the company not only collects detailed data on product use, but also collects data on grid peaks. Based on these data, the company developed a peak-time reward system that automatically raises air-conditioning temperatures during peak hours, reduces energy consumption, and cools rooms early before peak hours. Nest also works with power companies to integrate the data they provide with user data, and the power company rewards customers for discounts and points that reduce peak electricity usage.
The application of big data can also bring new business models to enterprises. Enterprises can connect to each other, collect data and analyze data through smart connected products, thereby expanding the functions of after-sales service, providing new types of services, and bringing new revenue and profit growth points to enterprises. Caterpillar has set an example in this area, providing a range of new solutions to help customers better manage their construction and mining equipment. The company can collect and analyze each piece of equipment on the site. The service team can provide customers with information on the distribution of equipment, thus reducing the number of devices used. They can also tell customers when they should add equipment, how to break through the capacity bottleneck and how to Improve the fuel efficiency of the entire fleet.
Professor Michael Porter explains how the organization needs to change in the face of the arrival of the Internet of Things. He said that a basic principle of organizational structure design is to divide different functions into one dedicated department, but we also need to integrate between different functional departments.
To get the most value out of new data sources, many companies have established specialized data departments that are responsible for data collection, integration, and analysis, and pass insights gained from the data to different departments and business units. For example, Ford Motor Company recently appointed the chief data and analyst to develop and execute a company-wide data analysis program. CDO will lead the company to use the data of smart connected products to understand customer preferences, designate future vehicle networking strategies and re-engineer the corresponding internal processes.
Incremental encoders provide speed, direction and relative position feedback by generating a stream of binary pulses proportional to the rotation of a motor or driven shaft. Lander offers both optical and magnetic incremental encoders in 4 mounting options: shafted with coupling, hollow-shaft, hub-shaft or bearingless. Single channel incremental encoders can measure speed which dual channel or quadrature encoders (AB) can interpret direction based on the phase relationship between the 2 channels. Indexed quadrature encoders (ABZ) are also available for homing location are startup.
Incremental Encoder,6Mm Solid Shaft Encoder,Hollow Rotary Encoder,Elevator Door Encoder
Jilin Lander Intelligent Technology Co., Ltd , https://www.jllandertech.com