For the past two decades, companies have been turning to manufacturing data analytics to improve the production and output of their factory automation. With this research method, mathematical and statistical data is analyzed to determine the causes of poor yield or inconsistent performance. Information can also highlight specific areas that need improvements and offer solutions to problems. More than ever, companies have the ability to measure increasingly specific or targeted variables in the manufacturing process, from overall operations to the shop floor, and can react accordingly to make needed changes or to prevent problems.
Increase Efficiency
Manufacturing data analytics gives companies the ability to compile a deep history of their production process. Analysis of data can reveal that one aspect of their factory process or one aspect of their management procedure is slowing production or decreasing the quality of their product. With data analytics, measuring compliance and traceability is much more specific than previously possible. Problems can be diagnosed at the machine level. Making one simple change may make all the difference in improving the factory's efficiency.
Knowledge is Power
In other instances, data analytics might not reveal an encompassing solution to optimize the efficiency of a factory automation process. Maybe the process is already working well and does not need to be changed. However, having the information can still offer a better understanding of each phase and the relationships between steps. An enhanced understanding of all of the nuances associated with production will come in handy if any problems arise. Quick action is possible with access to the right information.
Better Service
Big data can also be used to accurately forecast a products’ supply and demand. This is useful in two ways. To start, with better forecasts about supply and demand, management is able to set production goals in advance to maximize efficiency. For example, some manufacturers keep production lines running 24 hours a day. If management had a better idea of what time of year the demand decreases, then the company could alter practices to meet demand without wasting resources. Secondly, with more accurate supply and demand predictions, clients are more likely to get the product they want when they want it. Big data can enhance customer service experiences with a company.
A company may use targeted data aggregated by a cloud-based provider or other service provider. Koops can provide data-driven services to its factory automation clients. We analyze a client's production process, help develop specifications using 3D CAD and FEA capabilities, manage all aspects of the project as needed, and provides tailored solutions to the client's needs, including equipment installation, and on-site support.