Big data can help many manufacturing companies with continuous improvement issues. According to Forbes, by using the power of data analytics, companies can quickly accelerate existing automation techniques, so that work is done faster and more efficiently. Companies can also make more accurate predictions about their raw materials supply and the speed at which they can produce different combinations of items. For example, the time it takes to make one product might change depending on the other products being made at the same time in a factory. This is a complicated matter that likely would be hard to figure out without using big data to crunch the numbers and find correlations that people wouldn't otherwise have considered.
Companies can also turn big data outward and predict the demand for their products. They can track how well they are performing in comparison with previous days, weeks or months, and make estimations about the most optimal layout of a factory.
Pharmaceutical companies in particular can benefit from big data because of the complexity of the products being manufactured, Forbes reported. Food companies are also likely to benefit from an expanded understanding of the way that the supply of various raw materials can impact the optimum production of different finished goods. For example, a company that does enough research of its data can use complex calculations to figure out how best to use a limited supply of a certain starch, based on the amount of products that are sold and the cost to produce the items. For a simplified example, if a company buys 10 units of starch, it may be more efficient to make four units of product A and six units of product B, which would only be determinable through using big data to find the correlations that already exist but remain hidden.
Big data can also reduce inefficiencies by accurately determining the reasons for different defects that occur in products. By tracking everything through to shipments and seeing which items are returned as defective, a factory manager can see when something was made, what equipment was used and possibly determine at what point it was damaged and rendered faulty.
Collecting the Data is the First Step
Most manufacturing companies are already collecting massive amounts of data through barcode software or other data capture tools. At any rate, if they are not doing this, then they should be. By leveraging automatic data collection, companies can make major advancements in efficiency, Global Manufacturing reported. By using the software that RFgen provides, companies can begin gathering data that can be put toward uses that are still being invented by professionals who are experimenting with what can be done through big data processing.
Big data is already being put to use in finance to determine very accurate prices for different goods and financial instruments, and this same process is now being applied to many other aspects of business. With the proper technology in place, using tools as ordinary as barcode data collection, a company could theoretically collect up to a terabyte of information every day that can be put towards calculating highly accurate correlations which will save money and help factories maintain a competitive edge when it comes to producing on demand and supplying items for the cheapest possible price while maintaining good margins on the sales.
Data collection is a crucial tool for businesses to stay in top form during a time of transition when manufacturing is becoming even more automated than before. The industry is heading into a direction where computers are making major decisions about what to produce, how much to produce and when to produce it, and without data collection software, a manufacturing business will soon be left behind.