The Machine Learning as a Service in Manufacturing Market is expected to reach $ 626.82 million by 2023

Increased application of advanced analytics in manufacturing, high volume of structured and unstructured production and shop floor data, integration of machine learning with big data and other AI technologies, rising importance of predictive and preventive maintenance are few factors propelling the market growth.
Infoholic Research LLP, a global market research and consulting organization, has published a study titled “Machine Learning as a Service in Manufacturing Market: Global Drivers, Restraints, Opportunities, Trends, and Forecasts up to 2023”.
According to Infoholic Research, a new wave of digitization is impacting the manufacturing industry. The advent of Industrie 4 and industrial Internet of Things (IIoT) has revolutionized the manufacturing industry. In the imminent future, machine learning will prove to be a disruptive trend in the manufacturing industry and bring about mammoth improvement in productivity, supply chain efficiency, and product quality, optimize production processes, and enable economies of scale. The market is expected to grow at an impressive CAGR of 49%. The market growth is driven by growth factors such as the rising importance of predictive and preventive maintenance, the increased application of advanced analytics in manufacturing, a huge volume of structured and unstructured manufacturing data, and integration of machine learning with big data and other technologies. The market faces some restraining factors such as implementation challenges, the dearth of skilled data scientists, rigid business models, data security, and data inaccessibility concerns and affordability concerns of organizations. The market is on a high growth trajectory due to unexploited opportunities such as untapped data, digitization in manufacturing, and the increasing complexities in manufacturing processes.
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The Machine learning as a Service in Manufacturing Market has been segmented and analyzed by components, deployment modes, end-users, and regions. The market has been analyzed by components such as software tools, cloud and web-based application interface, and other components. The market has also been studied in terms of process and discrete industries. It has been segmented and analyzed by deployment modes as either public or private.
The regions studied in the report are Americas, Europe, APAC, and MEA. Americas holds the largest market share followed by Europe and APAC. The Americas has experienced extensive adoption of machine learning technologies. The manufacturing industry is a major contributor to GDP of the American as well as European countries. Digitization is significantly impacting the manufacturing industry and advanced analytics is being extensively applied across diverse manufacturing industries in these regions. China, Japan, India, and South Korea are the leading countries in APAC for Machine Learning as a Service in Manufacturing Market. Discrete industries account for a greater share of the market than discrete industries.
“The manufacturing industry has been a slow adopter of machine learning, but the new wave of digitization, with the advent of Industrie 4 and IIoT, has brought about a paradigm shift in the manufacturing industry. Machine learning as a service through subscription models has become a cost viable option for manufacturers who earlier had been hesitant to adopt ML in their production processes. The future of machine learning as a service in manufacturing is promising with greater integration of machine learning with AI technologies.”- Shayantani Deb Roy, Team Lead, Infoholic Research
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The report covers the present scenario and the growth prospects of the Machine Learning as a Service in Manufacturing Market during the forecast period (2017-2023). The report provides an exhaustive analysis of the industry covering the following features:
  • The report is analyzed based on components, deployment mode, end-users, and regions
  • The report covers the evolution of machine learning in the manufacturing industry, its features, advantages, and importance
  • The report covers the drivers, restraints, and opportunities(DRO) in the market impacting the market growth during the forecast years
  • The report includes a detailed vendor profiling, which includes financial health, business units, key business priorities, SWOT analysis, business strategy
  • The report covers implementation and adoption of machine learning as a service in the manufacturing industry
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