In the truest sense of the word, manufacturing is the engine of the world economy. In fact, the manufacturing industry is one of the most valuable industries to any economy.
For example, the GDP of the two largest manufacturing hubs in the world, China and the USA, had contributions of $4 trillion and $2.3 trillion respectively from the manufacturing industry.
Without manufacturing, we would not be able to access the products and services we love and use. From the cars we drive to the phones we communicate with, we depend on the manufacturing industry to deliver our beloved products to us.
Ever since the industrial revolution transformed how we approach manufacturing, the business world has been looking for new ways to streamline the process even more; leading companies are outsourcing their manufacturing processes to more efficient offshore plants, and manufacturers are automating their production processes to reduce human errors and improve quality.
With the help of these advancements, leading manufacturers across the globe can produce thousands of products with tighter tolerances and minimal human intervention.
The most critical advancement in the manufacturing industry in recent years, however, has been the integration of data analytics into the manufacturing process, which has given manufacturers enhanced production capabilities.
In this post, let’s explore the benefits of data analytics in manufacturing and how it’s improving product quality across all industries.
Traditionally, introducing a product design to the market involved a lot of trial and error. Most often than not, the first iterations of the product design had an underwhelming welcome among consumers due to the less than ideal ergonomics and design.
Today, however, with the power of data analytics, manufacturers can test their designs for efficiency and ergonomics without ever making a physical prototype.
Modern data analytics tools utilise machine learning and artificial intelligence to create computerised product designs and help manufacturers put them through their paces.
In automobile manufacturing, for example, even wind tunnel testing has been moved to systems powered by data analytics.
We need to talk about the rise of automated manufacturing when considering the benefits of data analytics in manufacturing.
Today, in many industries, the manufacturing process involves minimal human interaction—everything from delivering raw materials to quality control of the finished products is executed through advanced algorithms powered by data analytics.
The tight integration of data analytics also allows manufacturers to eliminate issues due to human error. A recent study found that 23% of unplanned idle time in the manufacturing process is due to human error.
With automated manufacturing systems, manufacturers can minimise unplanned downtime by optimising the analytics algorithms to detect potential anomalies in the production process or equipment and conduct proactive maintenance.
Deciding how much to produce is perhaps one of the most critical decisions across the entire production process. Overestimating the demand can lead to overproduction, costing the manufacturer millions of dollars in the process.
Underestimating market demand, on the other hand, can tarnish the reputation of the company due to the untimely delivery of products and services.
Therefore, manufacturers need to estimate their demand accurately to maximise their profit.
Data modelling and predictive analytics use historical demand data and simulate future market conditions to produce accurate demand forecasts for the future, helping manufacturers meet the market demand without wasting their resources.
Today, many industries across the globe are going through the fourth industrial revolution—driven by the power of data analytics and digital infrastructure—and the manufacturing industry is no exception.
The benefits of data analytics in manufacturing enable modern manufacturers to enhance capabilities to deliver more quality and efficiency in the production process.