Manufacturers have been collecting data since at-least 3000 BC when bags of grain or output of spears were counted and pictorially recorded on cuneiform tablets. Today, this scenario has changed, more than drastically with some manufacturers like GE collecting data every 250 milliseconds in some of their production plants.
Wipro commissioned a study with Economist Intelligence Unit, ‘Manufacturing and the Data Conundrum’ to examine how manufacturers now collect, analyze and use the complex, real-time data generated in production processes. The study shows some interesting findings.
- Almost 86% of survey respondents report significant increase in amount of production and quality-control data for analysis
- Using insights gathered from analyzing this data, two thirds of companies report annual savings of 10% more in cost of quality
- Production quality, reliability, throughput and maintenance practices have also improved for some companies.
But data analysis to generate useful insights has not been easy. There are many challenges
- Only 14% surveyed report that they have not had any problem managing the data glut from real time systems.
- Integrating data from various sources is cited as a major challenge.
- Only 42% of respondents have a well-defined data management strategy and fewer use data analytics to find solutions to production problems.
- Lack of resources and skills to analyze data is cited as other bottlenecks.
Keeping in mind these challenges, companies have resorted to various ways of tackling them. Consider the example of ABB, which makes power and electrical products. Its recent successes came in helping Sandvik Materials Technology of Sandviken, Sweden, which makes specialty stainless steel, titanium and alloys for equally specialized uses.
ABB helped Sandvik to reduce deviation from perfection by 35% in production by installing additional sensors which feed into digital controls. These sensors were used to measure precision in rolling the metal and the system provided by ABB analyzed data from these sensors carefully to remove issues and imperfections.
A rigorous and advanced data analysis capability can be a differentiator for any company. This marks an important attitudinal step for manufacturing companies into real-time controls and rapid responses to production variations. But the extent to which companies should embrace the world of big or complex data is a step best taken cautiously.
In this rapidly changing environment, the prudent manufacturer must design not only processes and products that work for them, but also a suite of data analysis that fits. As you will gather from reading this study and its findings, the benefits of getting this done right can be considerable.