Factory owners of decades past would gape at today’s manufacturing processes.
Many companies now rely far less on human labor and far more on machine precision.
However, just because they’ve managed to up their efficiency doesn’t mean there’s no room for improvement.
Up-and-coming industry 4.0 technologies will give manufacturers a considerable boost.
The implementation of these technologies — using the Industrial Internet of Things (IIoT), cloud computing and analytics — will boost operations efficiency even further and enhance communications across the manufacturing process.
The Industrial Internet of Things
To put it simply, the Industrial Internet of Things is like the regular Internet of Things’ heavy-duty older brother. Many new precision manufacturing machines on the market are now internet-connected. However, selling manufacturing companies on these high-tech machines is more complicated than it sounds.
Because most manufacturing types of equipment got made to run until it physically breaks down of old age, many companies still repair and work with these legacy machines, rather than invest in new ones. However, factory owners need to realize that IIoT equipment has the potential to overhaul their business into a more efficient and connected one.
By switching to connected machines — or retrofitting existing ones — manufacturers will gain a completely accurate picture of the factory’s flow of production.
Using the data drawn from the machines, it’s possible to monitor nearly every aspect of the plant — from outputs vs raw material to machine conditions.
Though it’s difficult for a human to glean meaning from all that data, software using data analytics can translate it with ease.
Data Analytics
The fact is, just the raw data output from connected machines isn’t much good on its own.
Moreover, it would take a team of dedicated engineers ages to interpret it. Here’s where data analytics software comes in.
Acting on data gleaned from the software can help companies reduce their operational costs and increase revenue.
Research shows that using data analytics for predicted maintenance leads to a 30 per cent drop in costs and 70 per cent less equipment downtime.
For example, as a plant manager, you may need to know how to monitor your compressor system.
It is estimated that inefficient compressors waste $3.2 billion annually in the United States. Using data logging, you can see the system’s usage in real-time.
By compiling historical data built up over a period, managers can identify areas that need attention and fix systems that might be driving up operations costs.
Cloud Computing
Companies can take their factory-level data analytics one step further by utilizing cloud computing.
By integrating smart machines and data analytics across factories and warehouses, then linking them using cloud computing, the business can become more agile and reactionary to immediate trends.
For example, say there is a sudden uptick in the sales of a particular item.
Cloud-based data analytics would pick up on those sales and ensure the proper people get notified so sufficient raw materials are available for more.
Additionally, factory managers would also pick up on this data and prioritize that item over others to maintain availability.
This type of integration also helps a factory’s non-robotic workers, as the predictive data helps them prepare for their jobs. The anticipation of market events helps them work smarter and with more flexibility, leading to production gains.
Today’s high-tech manufacturing process is far different from its ancestors.
Advances in industry 4.0 technologies like network equipment, machine integration, big data analysis and cloud computing have enabled companies to be more efficient.
Of course, there are also the risks associated with adopting such technology too.
They’re less like a system of factories and warehouses, and more akin to an actual organism, reacting to the difficulties of business and making adjustments along the line accordingly.
Also, be sure to read ‘Industry 4.0 in Southeast Asia’