The “Big Data Analytics in Manufacturing Industry Market“ Report companies operating in the market are incessantly focusing on the implementation of various strategies in order to retain their positions in the market. Decrease in prices, implementation of more efficient technology, broader product portfolio, and long term supply relations with key end-use industries as well as localized manufacturers are the core strategies of the leading players to amplify consumer base and market share.
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Big Data Analytics in Manufacturing Industry Market study was conducted using an objective combination of primary and secondary information including inputs from key participants in the industry. The report contains a comprehensive market and vendor landscape in addition to a SWOT analysis of the key vendors.
The Big Data Analytics In Manufacturing Industry Market is expected to register a CAGR of over 30.9% during the forecast period 2019 – 2024. With the high rate of adoption of sensors and connected devices and the enabling of M2M communication, there has been a massive increase in the data points that are generated in the manufacturing industry. These data points could be of various types, ranging from a metric detailing the time taken for a material to pass through one process cycle or a more complex one, such as the calculation of the material stress capability in the automotive industry.
Manufacturing is a crucial component of a companyâs end-to-end supply chain. The value chain participants, like Raw material suppliers, Inventory managers, and Manufacturers have moved from manual product, tracking to the use of barcode scanners and investing in technologies, like RFID and sensors to monitor the stock, production processes, and ascertain when maintenance is required and to take action before the production quality is affected. Such technology adoption was made to monitor aging manufacturing equipment, in order to avoid production downtime, which could be as high as EUR 180 billion (for Britainâs manufacturers, according to Oneserve, the field service management company).
In addition to monitoring the asserts, these technologies are being used to gain information about the location of raw materials and finished products within the production facility, to know the status of the availability status (both volume and location data). In addition, advancement in UHF technology has made creating RFID systems more efficient and evolved in such a way that they are able to identify raw material/product specifications like SKU, color, and type thus improving the traceability throughout the supply chain.
Manufacturing is one of the most targeted industries by cyber attackers owing to the presence of vital data related to company and government. According to EEF (formerly the Engineering Employers Federation), over 45% of the manufacturers have been subjected to a cybersecurity incident.
With the increasing integration of technological advancements in the manufacturing industry, the security concerns are also ascending at a significant pace.
The scope of the Report
The manufacturing industry has evolved since the last industrial revolution. Technology has played a critical role in shaping the modern manufacturing industry. With the introduction of Industry 4.0, the production establishments took a step forward and implemented many IoT and IIoT solutions to get live feedback from factories and working environments. With the implementation of Machine to Machine services and telematics solutions in production establishments, the industry has moved from the traditional value chain to technology, asset, and engineering-oriented value chain
Key Market Trends
Condition Monitoring is expected to register a Significant Growth
Condition monitoring or the act of monitoring the condition of an asset, especially through real-time data points, forms the foundation of what has become known as Industry 4.0, in its basic form. An integral part of condition monitoring, within the IIoT ecosystem, is providing data that can then be used for Predictive Maintenance (PdM) and many more smart factory applications, such as Digital Twin.
Big data analytics, especially with predictive analytics, is a growing trend and often prompts discussions around centralizing data across multiple sites, so that the consistency of data is achieved. However, a significant roadblock remains the inability of many customers to convert the flood of new data into actionable information. Big Data systems need to monitor machine failures repeatedly before they can analyze adequately and predict effectively for the future.
For instance, overhead conveyor systems are used in assembly production lines in the automotive and other manufacturing industries. The failure of single support frames can lead to the disruption of entire production lines. A condition monitoring system based on big data analytics detects the problem at an early stage and, thus, prevents unplanned downtime.
North America is Expected to Hold Major Share
North America is among the lead innovators and pioneers, in terms of adoption, for big data analytics in the manufacturing industry, and is expected to hold a significant share over the forecast period. Manufacturing sector adds a lot of value to the US economy. According to Trading Economics, GDP from manufacturing in the United States increased to USD 2125.80 billion in the second quarter of 2018, from USD 2113.80 billion in the first quarter of 2018.
The manufacturing sector is also forecast to increase faster than the general economy. According to the MAPI (Manufacturers Alliance for Productivity and Innovation) foundation, production will grow by 2.8% from 2018 to 2021. According to the Digital Change Survey done by IFS in 2017, to assess the maturity of digital transformation in a range of sectors, such as manufacturing, oil and gas, aviation, construction and contracting, 46% of the companies in all industries are looking to invest in the big data and analytics.
American multinational corporation, Intel is finding significant value in big data. The company uses big data to develop chips faster, identify manufacturing glitches, and warn about security threats.
The Big Data Analytics In Manufacturing Industry Market is highly competitive and consists of several major players. In terms of market share, few of the major players currently dominate the market. These major players with a prominent share in the market are focusing on expanding their customer base across foreign countries. These companies are leveraging on strategic collaborative initiatives to increase their market share and increase their profitability. The companies operating in the market are also acquiring start-ups working on big data analytics in manufacturing technologies to strengthen their product capabilities. In January 2018, Datawatch has completed the acquisition of Angoss Software. This acquisition is expected to help the company to expand data science capabilities, which will enable the data scientists to perform predictive and prescriptive analytics in a wide variety of enterprise applications.
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Big Data Analytics in Manufacturing Industry Market Analyse according to leading players, Competitive landscape, geographical regions, top manufacturers, types, and applications forecast over a period of 2019 to 2024. Geographically, this report is divided into many key Regions, with production, consumption, revenue (million USD), market share and rate of Big Data Analytics in Manufacturing Industry Market 2019 in these regions, from 2018 to 2024 (forecast), covering: North America, China, Europe, Japan, Southeast Asia, India.
The Objectives of this report are:
- To define, describe, and analyze the Big Data Analytics in Manufacturing Industry market on the basis of product type, application, and region
- To forecast and analyze the size of the Big Data Analytics in Manufacturing Industry market (in terms of value) in six key regions, namely, Asia Pacific, Western Europe, Central & Eastern Europe, North America, the Middle East & Africa, and South America
- To forecast and analyze the Big Data Analytics in Manufacturing Industry market at country-level in each region
- To strategically analyze each submarket with respect to individual growth trends and its contribution to the Big Data Analytics in Manufacturing Industry market
- To analyze opportunities in the Big Data Analytics in Manufacturing Industry market for stakeholders by identifying high-growth segments of the market
Key Questions Answered in Big Data Analytics in Manufacturing Industry market report:
- What will the market size be in 2024 and what will the growth rate be?
- What are the key market trends?
- What is driving this market?
- What are the challenges to market growth?
- Who are the key vendors in this market space?
- What are the market opportunities and threats faced by the key vendors?
- What are the strengths and weaknesses of the key vendors?
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Big Data Analytics in Manufacturing Industry Market Report Provides Comprehensive Analysis as Following:
Market segments and sub-segments
Market size & shares
Market trends and dynamics
Market Drivers and Opportunities
Market Analysis and Segmentation
Supply and demand
Technological inventions in Big Data Analytics in Manufacturing Industry trade
Marketing Channel Development Trend
Big Data Analytics in Manufacturing Industry Market Positioning
Distributors/Traders List enclosed in Positioning Big Data Analytics in Manufacturing Industry Market
Big Data Analytics in Manufacturing Industry Market report provides you a visible, one-stop breakdown of the leading product, submarkets and market leaders revenue forecasts till 2024. In conclusion, Big Data Analytics in Manufacturing Industry Market 2019 report presents the descriptive analysis of the Big Data Analytics in Manufacturing Industry Market Major Key-players, Types, Application and Forecast Period knowledge which is able to function a profitable guide for all the Big Data Analytics in Manufacturing Industry Market competitors.
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