Published on June 13th, 2020 | by Ayushi Sharma0
Manufacturing Analytics and Its Applications
Your machines are producing tons of data every second. Your manufacturing plant is basically a mine of important data ready to be analyzed to give you game-changing insights. Previously, if anyone had to understand how a machine is performing, what is the complete output of a plant or any other detail, it became a long tedious process, how? You had to write down the data, understand what calculations are needed, and calculate the necessary KPIs, this could take from days to weeks. It led to not just delayed insights but many a times insights that are now totally worthless. However, things changed for the positive in the past few years with innovation of IoT to gather the data from your machines digitally and manufacturing analytics to smartly analyze your data and get to the very last and minute detail. This enabled manufacturers to be ahead of their game.
What is Manufacturing Analytics?
Manufacturing Analytics is the process of collection of various kinds of data (structured, unstructured, real-time, and more) and analyzing and manipulating it to derive game-changing insights. Manufacturers can understand and analyze data regarding the working of machines and the people operating them. They can have a 360-degree view of a problem at hand and can analyze it to reach potential solutions. This empowers not just the manufacturers or the company management but also the field executives to understand any problem related to the machines, supply chain, demand or anything. Managers can have a detailed view of the complete process right from when a production order arrives at the point when it gets delivered.
How Analytics benefits its users?
Real-time insights: Using analytics, the real-time data getting gathered at every machine and useful points can get analyzed in real-time and any current problem related to a machine or supply chain or anything can be resolved right there and then. Analytics even allows the people to detect any potential future issue which can be prevented by taking the right measures.
Error Detection and Reduction: With the capability of analyzing large amounts of data, the identification of errors becomes easy. This allows detection at the earliest which could have led to cause a loss in quality in the final product or any potential machine downtime. This saves the manufacturers a lot of time and money which would have otherwise spent on the correction of these errors or running the production cycle again.
Understanding Cost, Revenue, and ROI: A manufacturer can easily get to know his exact cost per machine, per product, and overall operations. They can also see the exact revenue generated from the large units producing a large number of goods that otherwise would have been impossible to be done manually. This equips the management with the right statistics regarding their ROI and identifies any rotten apples to sorted.
Reduction and Prevention of Machine Downtime: The executives can use dashboards to visually identify even if a machine got slowed by 1 minute and or if there is any deterioration in the quality of production and can quickly take the right measures to improve upon. With the power of predictive analytics, they can predict which machine is likely to go down or which production cycle can get hampered and take proactive measures to solve them.
With research saying that the global IoT in manufacturing market size is projected to hit USD 136.83 billion by 2026, there is no shying away from manufacturing analytics anymore. It has shown its capability and proved itself equally important for both large scale and small scale manufactures. It is only a matter of time when the complete industry adopts it and leading to new innovations here onwards.