Big Data is applicable in every industry including healthcare, financial, retail, and manufacturing. It has grown as an inevitable force that can shape any business in today’s world and this holds true to the manufacturing industry too. 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, ranging from the time taken to process a cycle to a more complex, can be further analyzed to improve the whole manufacturing process and more. This can be done with the help of big data analytics in the manufacturing industry. Today, leveraging big data analytics is a business imperative and it is enabling solutions to long-standing business challenges for manufacturing companies around the world. Here is how big data analytics in the manufacturing industry is transforming the entire process.

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Paves way for efficient Product management

Currently, product management is one of the biggest challenges for the manufacturing industry. Traditionally, companies used to rely on human estimates that often led to either product being developed in excess or less. But this was earlier when big data analytics in the manufacturing industry did not exist. According to a report by Research and Markets, the global big data analytics in the manufacturing industry was valued at USD 904.65 million in 2019 and is expected to reach USD 4.55 billion by 2025. With the help of big data analytics, manufacturing companies can efficiently and accurately determine the volume of products required in the market. Big data analytics can also be employed to analyze the behaviour of repeat customers and determine which products are viable and which ones needed to be scraped off.  

Increases operational efficiency in the manufacturing process

Manufacturing operational efficiency is everything in the manufacturing industry. Although process manufacturing has a big volume of data stored for decades, it is mostly underutilized. Improving efficiency across the business helps manufacturing company control costs, increase productivity, and boost margins. It is true that automated production lines are already standard practice in many manufacturing plants, but big data analytics can exponentially improve line speed and quality. The Machine logs contain data on asset performance and this data has a potential of great value to manufacturers. With the help of big data analytics in the manufacturing industry, manufacturers can quickly capture, cleanse and analyze the machine data and reveal insights that can help them improve performance. 

Brings transparency into the entire supply chain

Employing big data analytics in the manufacturing industry supply chain increases transparency into the entire supply chain process. By collecting and analyzing the huge data compiled from several sources, ranging from ERP systems within the enterprise to supplier’s business, orders, and shipment information for customer shopping patterns logistics, manufacturers can greatly optimize the supply chain. For instance, manufacturing companies can analyze individual processes and their interdependencies for opportunities to optimize everything from demand forecasting and inventory management to price optimization. Big data analytics also makes it possible to predict with greater certainty whether or not a supplier will deliver products as agreed, and makes it possible to optimize supply chains to improve gains and reduce risk.

Enhances the quality assessment process

With customers demanding more sophistication and customization in the manufacturing environment, quality control effectiveness has become an increasing challenge for manufacturing. Quality control is an area that has traditionally remained in the realm of human operations. But after the advent of Artificial Intelligence (AI) and big data analytics, this situation has been improving and these technologies are helping to drive production efficiencies and improve production quality. Automatic quality testing saves time and helps avoid human errors. Instead of the traditional manual checks, the quality of the manufacturing process and the manufactured product can be tested by analyzing data from special test devices, X-ray scans, photography, etc. 

With the increasing integration of technological advancements in the manufacturing industry, big data analytics in the manufacturing industry can be employed to improve manufacturing, product design, quality and manage the supply chain efficiently. We, at Intone, combine our 15 years of deep manufacturing industry expertise and technology knowledge with the latest industry trends to apply innovation, transformation, and digitization to enable superior growth, differentiation, and unsurpassed operating performance in the manufacturing industry. We help global manufacturing companies with mergers & acquisitions, optimizing plant operations, creating solutions for RPA and supply chain optimization, digital engineering, and manufacturing, artificial intelligence, and data-driven analytics. We have dedicated partnerships across the globe and are committed to driving positive change through the world’s largest manufacturing companies. Discover limitless possibilities with Intone.

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