Big Data - the Alchemist in Manufacturing Wipro Experts
Big data has arrived in manufacturing and in a big way. Needless to say that it governs the future of manufacturing as is clear from the Economist Intelligence Study commissioned by Wipro – 'Manufacturing and the data conundrum' where 86% survey respondents report major increases in collection of data and 90% respondents saying their companies have mature data analysis capabilities for many manufacturing processes. Having said that, some questions need to be answered. How are manufacturers using these huge volumes of data for deriving valuable insights which in-turn will help in profitability? Is data collection easy or cluttered with problems related to quality and transparency? Is it easy to integrate data from various sources?
The time has come to shift from mere forecast of problems using data to actually solving the above questions using data effectively. Despite the complications between shop-floor data theory and practice, companies surveyed have found a number of comfort zones where the benefits of real-time machine-generated information are accessible. As mentioned above, many have mature data analysis capabilities and using insights gathered from production-data analysis, two-thirds of companies report annual savings of 10% or more in terms of the cost of quality and production efficiencies. According to a McKinsey report, nearly 1.8 billion people will enter the global consuming class over the next 15 years and worldwide consumption will nearly double to $64 trillion. In such a scenario data analytics provide manufacturers with a huge opportunity to predict, innovate and implement. The challenge now is to integrate the data from multiple sources and draw valuable insights.
Although state-of-the-art digital systems can predict problems and suggest solutions in advance of actual need, more than half of manufacturers aren’t confident that their analytical skills are up to the task. In Professor Daniel Apley’s (professor of industrial engineering and management sciences, Northwestern University) words 'It is very difficult to find young, talented people who want to go into manufacturing. They want to be with financial companies, or Google and Facebook'. Just 22% of surveyed companies have predictive analytical capabilities for production throughput, for example; just 16% have mature analytical capacity to generate potential solutions.
After all is said and done, it turns out that coordinated digital control systems can and do produce insights that are extremely valuable. Some 34% of those surveyed have generated annual savings of more than 25% annually in the cost of quality; the same proportion report 25% or better efficiency improvements annually.
Effective use of data is the alchemist to the many challenges manufacturers are facing today. Do you have any other thoughts on how data is being used in manufacturing processes to provide transparency,increase efficiencies and reduce cost of quality?