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“Harnessing data is crucial” is what has been accepted globally and an example of this can be given by citing 2012 MIT Sloan Survey where two-thirds of companies said using analytics gave them a competitive edge. Most factories could use the boost.
In 2015, according to the Institute for Supply Management (ISM), U.S. manufacturing activity fell to 51.1 from 52.7 the month prior. The reading is the worst in two years. In Canada, the RBC Purchasing Managers Index (PMI) fell to 49.4 from 50.8 in July. A score below 50 signals industrywide contraction. In each market, factory managers are under renewed pressure to optimize processes and lower costs. Analytics tools could hold the key to finding areas of improvement.
Big Data tools are best for capturing machine-level information. Monitoring the time in which various lines in the industry manufactures certain products and then using them to derive meaningful insights, by backtracking, thus having a better understanding of the performance of the machines that are being used in the manufacturing unit.
Granular utilization data is one of the major aspects that a manufacturing industry can get by implementing Big Data Analytics. For example, when does your factory produce its greatest output? What days? What hours? And at what mix and with who on the floor? Again, the idea here is to study the conditions that lead to the very best outcomes and then seek to reproduce those outcomes on a regular basis.
Avoiding mistakes is every bit as important as optimizing the mix and hours on the floor. Using Big Data and analytics tools to study error rates and then correlating the results by product and employee. It can also be found out if some workers do particularly well with a certain brand of product and not so well with others, allowing the manufacturer to optimize his mix and make smarter decisions when it comes to training and employee incentives.
Of course, Big Data is only a tool and what matters is what you do with it. Track line and assembly speed, utilization data, error rates and prototyping costs to find out what drives efficiency and profit at your factory. Then, recognize and reward the behaviors and processes that produce them so that everyone wins including the workers who stand to lose the most during this most current downturn.
This report extensively studies the use and effects of using big data analytics in Industry and Manufacturing. Geographical estimation of the total market of big data in Industry and Manufacturing along with the expected growth rate till 2021 has been studied along with the technological areas in Data Analytics in which future growth prospects are higher is studied.
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