Manufacturers have always been an early adopter of new technologies. Efficiency experts have been involved with improving manufacturing processes since the turn of the 20th Century. They focused on enhancing the quality of goods, lowering costs, eliminating waste, automating tasks and compressing the cycle time of work.
From the 1980s
In the 1980s, statistical process control (SPC) became a key strategy to improve manufacturing. Computers were implemented to create quality charts and foresee incidents in production. At that time, I managed a software development group that created SPC solutions for the automotive industry. The systems collected data from manufacturing production lines and produced SPC charts. They were also able to do basic predictive analytics to predict failures on equipment. This is what IoT projects claim they do can today. So, what is actually new?
In auto manufacturing, downtime can cost $22,000 per minute. The ability to foresee a failure before it occurs is of tremendous value to a manufacturer.
To the future
Today we can collect data at 1.3 megabytes per second, and our computers run at least 100 times faster and have terabytes of data storage. In the 1980s, a large hard drive could only store about 500 MB.
The software also had to be written from scratch. To create a simple X bar and R chart required a software developer. Today, basic software can produce any statistical process control chart, all at the click of a button.
Emerging technologies have both changed and created the tools that are available to improve manufacturing. Let’s look at some use cases enabled by these upgraded tools.
1. Predictive maintenance
When a production line goes down, the cost is exorbitant. In auto manufacturing, downtime can cost $22,000 per minute. The ability to foresee a failure before it occurs is of tremendous value to a manufacturer.
GE’s Pune multi-modal facility produces products for GE’s oil & gas, aviation, transportation and distributed power businesses. It is unique in that it can switch to building various products using the multi-modal approach. They have implemented IoT to do predictive maintenance.
The system provides visualized performance from all 20 CNC machines on a single screen. It enables them to reduce machine downtime and has saved $1 million in cost avoidance. Overall equipment effectiveness has also increased from 45 percent to 60 percent.
2. Improve the productivity of employees
By utilizing IoT technology, Caterpillar has developed a new telepresence tool called LIVESHARE that enables a technician to collaborate with experts in different locations in a live setting using augmented reality, “utilizing voice, 3D animation, annotation, screen sharing and white-boarding.”
They have implemented remote monitoring devices and have 500,000 connected assets around the world that can be inspected by service technicians by simply uploading a photo through their smartphone.
3. Reducing manual labor using Cobots
In SEW-Eurodrive’s factory in Baden-Württemberg, a “Cobot” or co-robot is a robot intended to physically interact with humans in a shared workspace.
The SEW-Eurodrive factory has implemented Cobots to assemble a complete drive system. The Cobots complete many simple tasks, leaving the most complex activities for humans to do. Employees stated that they have increased job satisfaction since they now assemble an entire product with the help of the Cobot, and they don’t have to lift heavy parts.
With 5G, data delivery latency will decrease to as low as 1ms and data transfer will increase up to 10Gps, meaning faster detection of issues on the line.
4. Automating manual processes & quality improvement
Teel Plastics has ten manufacturing lines that produce different products throughout the day. Each line requires a custom recipe of material inputs and equipment heat settings for each product. In addition, recipes can change several times in one day. The variety of variables creates a higher potential for human error.
Teel has implemented the Kepware software solution to enable a line operator to save a recipe and then distribute the instructions to the machines on the line via interfaces to multiple programmable controllers. As a result, Teel has:
- Reduced set up times by 30 percent.
- Eliminated the need to memorize 30 to 40 instructions.
- Increased visibility in the plant enabling them to support predictive maintenance.
- Doubled output from 18 units per minute to 35 units per minute.
The promise of 5G
There’s more to look forward to in the manufacturing industry that will improve productivity levels, automate laborious tasks and detect potential problems. 5G will be the catalyst for scaling the smart factory. With 5G, data delivery latency will decrease to as low as 1ms and data transfer will increase up to 10Gps, meaning faster detection of issues on the line. These speeds will enable manufacturers to meet Industry 4.0 use cases that demand this kind of performance.
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