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Software-Defined Machine Market - Industry Analysis, Growth and New Market Opportunities Explored
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There are several advantages associated with the implementation of software-defined machines which are primarily driving their demand in the global market. Presently, the machines which are used in manufacturing processes are limited in terms of their hardware capability. These machines are either operated by a person mechanically or with the help of software specifically designed to run that operation. In addition, some of these machines also run through applications which were built to a specific firmware and difficult to upgrade based on various requirements. Moreover, these machines are also difficult to connect with the industrial internet for remote access. Furthermore, the machines were not able to communication with each other due to the lack of hardware and software.
The idea of software defined machines has helped to commercialize the concept of industrial devices which can autonomously connect with the internet network and execute operations. In addition, the function of the machines can also be modified with the help of these advanced softwares. Going further, the software defined machines can also be used to stored useful data in the cloud for future access. The rising crisis of increase in labor wages has resulted into the need to automated process in countries such as China and South Korea. The software defined machines can also be used to replace the human workforce as it would reduce the chance of human error and increase the efficiency in operations. These factors are aiding to the demand for software defined machines globally.
However, the high initial cost of installing the software is one of the major factors hindering the demand for software-defined machines market. Nevertheless, the upcoming trend of industry 4.0 is expected drive the need for industrial automation substantially. This in return is expected to drive the demand for software-defined machines market in future.
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The global market for software-defined machines can be segmented by end use industry and geography. By end use industries, the market can be bifurcated into automotive, manufacturing, chemical, logistics and warehousing, food and beverages and process industries. The growing demand for automation in industries is expected to drive the demand for software-defined machines steady across all the segments during the forecast period.
By geography, the global software-defined machines market can be segmented into North America, Latin America, Europe, Asia Pacific and Middle East and Africa. North America and Europe have been identified to be early adapters of new technology and hence expected to witness strong demand during the forecast period. Furthermore, the Asia Pacific region is expected to witness strong demand due to presence of emerging economies such as India, South Korea and China which developing rapidly and investing heavily towards industrial automation. Middle East region is also expected to witness steady growth over the forecast period.
There are several players operating in the global software-defined machines market. These players are witnessing strong competition which is resulted into frequent mergers, acquisitions and partnerships between them in order to sustain in the highly competitive environment. These players have been profiled in terms of their business overview, product segments, financial performance, SWOT analysis and business strategies. The leading players operating in the software-defined machines market include GE (U.S.), Atos (France), Drem Kft. (Hungary) and VMware (U.S.) among other emerging players.
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Transparency Market Research (TMR) is a global market intelligence company providing business information reports and services. The company’s exclusive blend of quantitative forecasting and trend analysis provides forward-looking insight for thousands of decision makers. TMR’s experienced team of analysts, researchers, and consultants use proprietary data sources and various tools and techniques to gather and analyze information.
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