How Big Data is revolutionizing the Manufacturing Sector
The need for supplying the products to the growing population and depleting resources is forcing the manufacturing sector to become more competent and sustainable.
Customers are becoming more and more informed about the product they consume, and therefore, manufacturers need to be flexible and open to new changes. Big Data Analytics (BDA) is one such technology that has transformed the manufacturing sector.
Organizations have now becoming more flexible with regards to their processes and, at the same time are improving the quality of their products by taking the advantages of Big Data analytics.
Already the field of data analytics, science and engineering have proven a transformative force for businesses over the last few decades and that includes the manufacturing sector.
How Big Data is being used in manufacturing right now
The manufacturing industry is heavily process oriented and as such energy efficiency is often critically important and R&D investment is made into refining processes to make them more efficient and cheaper.
This has further intensified with manufacturing industries attempting to move towards greener energy sources. The International Renewable Energy Agency reported that renewables could constitute some 27 percent of all manufacturing-related power consumption by 2030.
Big Data is thus emerging as the saver coming to the rescue to uncover anomalies or inconsistencies that drive process refinement. Big Data is about uncovering these sorts of positive trends and analysing their causes so they can be replicated to drive ROI, value and efficiency.
AI-powered data analytics platforms like Avora are able to work with huge datasets, analysing data automatically to provide AI-driven insights, graphs and reports.
The way Big Data is being applied in manufacturing is unique in certain ways, considering the specific requirements of the field. It is being primarily used to provide valuable insights to the manufacturers aiming at profit maximization, risk minimization, and productivity assessments.
The following advantages of Big Data or data analytics in manufacturing is being achieved by the manufacturing sector-
· Optimizing production and enhancing efficiency
Process manufacturing has a big volume of data stored for decades. But this data is mostly not utilized properly or underutilized.
Machine logs contain data on asset performance. Internet of Things (IoT) also adds a new dimension with connected assets and sensors. This data is potentially of great value to manufacturers.
Big Data is helping manufacturers to quickly capture, cleanse, and analyse machine data and reveal insights that can help them improve performance.
· Predicting machine failure and reduce downtime
In the asset-intensive manufacturing industry, equipment breakdown and scheduled maintenance are a regular feature. Big Data is helping the reduction of breakdowns by as much as 26 percent and unscheduled downtime by about 23 percent.
In automotive manufacturing, robotic arms in assembly lines is being used on a regular basis. These robots perform various tasks like welding of parts in an automobile, gluing, cabling etc. The downtime costs auto industry phenomenally and as such using Big Data is helping in reduction of downtime costs thereby helping in cost cutting in the production process.
· Optimizing the supply chain
The massive spike in supply chain data is becoming a huge challenge for manufacturing sector. This data is compiled from several sources, ranging from ERP systems to the supplier’s business, orders and shipment information, weblogs for customer shopping patterns logistics etc.
Forward-looking organizations are leveraging Big Data to get a 360-degree view of the customer so
as to better predict customer needs, in understanding about their personal preferences, and in creating a unique brand experience.
Beginning from supply network planning to procurement to end to end execution of the supply chain, all functions of the processes are utilizing the benefits of big data.
· Enhancing product quality and cutting manufacturing cost
Using Big Data for predictive analytics, manufacturers are able to significantly reduce the number of tests required for quality assurance to cut down test time and focus on specific tests.
Automatic quality testing using Big Data analytics is saving time and helping avoid human errors. Instead of the traditional manual checks, the quality of the manufacturing process and the manufactured product is being tested by analysing data from special test devices, X-ray scans, photography, etc.
Overall, with the increasing integration of technological advancements in the manufacturing industry, Big Data in the manufacturing industry is being employed to improve manufacturing, product design, quality and in managing the supply chain efficiently.
