Why manufacturing needs Big Data?

Over the past decades the manufacturing operations have undergone a remarkable evolution, the simple production and fully under human control, to a complex, automated and increasingly intelligent process that, like any form of business management requires accurate data and reliable. In this sense, Big Data has helped, and much, the sector. To get an idea, some companies even collect every 250 milliseconds, more than ten thousand data. Therefore, the adoption of digital strategies for Big Data analysis can be substantial since, in addition to increasing business productivity, the study of this information will enable more assertive processes, reduce costs and to predict and prevent operational problems. Planning and prioritizing this type of initiative, however, still show challenging for many companies.

According to the survey “Manufacturing and the Data Conundrum“, The Economist Intelligent Unit conducted on behalf of Wipro, only 42% of respondents consider to have a well-defined data management strategy, but despite this number does not reach half of the total 86% of these companies claim to have been an increase in the production and quality of data to be analyzed – a sign that the insights generated a positive impact on business. The study also found that companies that have a well-defined data strategy are more likely to profitability, with average growth of more than 10% profit annually – 34% of companies reported annual savings of more than 25% by using the analytical systems.

An example of successful strategy is Meritor, transmission systems manufacturer, brakes and other components for commercial vehicles. In assessing the industry vendors, customers consider the number of parts rejected per million (PPM). To raise your note in this regard, Meritor quintupled the data collected and numbers began to track the defect rates, not only by product batches, but also by individual production operations. It also decided to differentiate the parts rejected by clients of rejected by suppliers, allowing evaluate the quality levels of their own sources. The result? In 2013 the rejection rate of the company stood at 139 parts per million. During the first quarter of 2014, with the company working to improve the traceability of production problems, the rate dropped to 67.

Today more than ever it is essential to manufacturing industry run an effective and integrated management of Big Data. We see that the way to achieve success in the midst of this immensity of information is increasingly collect them and analyze them in order to meet a preset goal, seeking valuable information and will allow the company to better understand the needs of its customers and, from that, find out how to optimize their production.

Full article: http://corporate.canaltech.com.br

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