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Introduction
The big data has led the revolution of computational power in industrial manufacturing and spread the horizon of the market. Big data shows trends, reveal patterns, and relations of human behaviour and interactions. Industry giants like Apple, Tesla, Uber and Airbnb, have used big data for the expansion into new big markets and used these trends to know the customer needs and making their products accordingly to grab the market share. It has improved the supply chain mechanism in markets. IDC study has revealed that the Sales and analytics from big data can reach up to $187 billion in 2019, which were $122 billion in 2015. One area which has benefited from big data is the manufacturing industry which has projected the growth in 2019 to be $39 billion for the big data revenues (Agrawal, 2016).
After the invention of assembly line anug=facturing has grown massively as before 20th century, the production processes were slow and these processes yielded few products. The assembly line integration with other methods like lean thinking approach in manufacturing has enabled the mass production in manufacturing with maximum utilisation of their available resources; statistics used to analyse big data could result in more accurate and more straightforward to understand results of big data analysis (Oregon State University, 2017).
Effects of Big Data on Manufacturing Companies
IT plays the major role in manufacturing revolution even the companies which have generated the large number of data sets which yet don’t have realised what to do with the available data which is in access than needed. For instance, the factory sensors which can generate the number of data points by the inspection of the product defects across the assembly line. When put into analytical software it can produce different types of data which can be used to improve the manufacturing processes. It has developed the industry in the number of ways.
Cost Savings
Big data has changed the thinking about the manufacturing processes through available data companies can know the trends and methods from which the cost can be cut. The information produced data which can help the industry lower their manufacturing, packaging, transportation and normal loss costs and at the end huge saving in inventory and warehousing costs.
Improved Quality and Safety
Most of the big organisations use data analytics for their product model simulation to enhance the quality of their products. Companies used computerised sensors to along assembly line which identify the defects in products and put out them from an assembly line, by analysing these defects and the reason behind companies can improve the quality and manufacturing processes to reduce these rejections. To make improvements in the product before launching and delivering into the markets (Agrawal, 2016).
Improve Workforce efficiency
Through analysing the production floor data companies can improve the effectiveness of the workforce by making improvements into the areas where the workforce is lacking and where they are excelling, it can be used to study the error rate and identification of the processes which needed to be optimised. This data analytics can also improve the production line speed for higher output.

Better Collaboration
Data analytics can improve the overall organisational efficiency by enhanced workflow information in the manufacturing organisation. The synergistic flow between departments of engineering, management, quality control, machine operators and other departments within the organisation, this can improve access to massive data sets within organisation’s different departments.
Implications of Big Data
Despite delivering lots of benefits to the industry, the industry is slow moving and lacking top reap the full potential of big data analytics industry needs to integrate more with big data. Manufacturing is more complicated than other industries which have implemented the big data analytics, and it makes difficult the integration of the big data analytics in manufacturing. Companies should know where to mine the data and what right analytical tools to make sense of the data. If the software has a problem assembly line can suffer a huge loss and to implement fixes it can take more time if the problem is not identified (Agrawal, 2016).
Industries have reaped the benefits from big data analysis and still have a lot of data to use and to make sense of the available data. Big data improved the manufacturing processes and helped every sector which are using this software to analyse data and take industries, not only tech but also manufacturing industries to incredible growth (The Network Impact of Big Data, n.d)

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