Artificial IntelligenceTo Make Machines Trouble-free, Efficient

By K Soundhar Rajhan:

As the world is moving towards Industry 4.0, we at LMW are working with the emerging technologies to keep our products in line with the market demand. We intend to use technology to upgrade our facilities and increase the overall efficiency of the plant mainly in two ways. One is product upgradation with emerging internet technologies or Industry 4.0-compliant machines, which will deliver greater value to the Customer. The other is enhancing our operational efficiency using emerging Industry 4.0 technologies
We find machine tools in general are stand-alone equipment and quite isolated from digital information highway. We are working on bridging this gap by integrating the machine with internet and cloud platforms. This will enable the buyer to be in touch with the machines from anywhere in the world, a real-time update on status of the machine and production data.
This technology was demonstrated at IMTEX 2017 in January this year by integrating seven of the machines on display. The customer can access the status of the machine in real time and will be able to take instant decisions, as the data is available or accessed from any of his electronics gadgets, be it the Laptop, tab or mobile phone.
At the next level our quest will be to use IoT technologies to make our machines more intelligent, so that they are able to self-diagnose and predict the failures which arise due to temperature rise in machine elements such as spindle, ball screws, bearings, coolant, vibrations caused due to deterioration of key elements. They will even detect variations in input materials by keeping track of sudden surges in motor power consumption, etc .
This will enable the operator or maintenance engineer to take proactive corrective measures and achieve a near-zero downtime of the machines.
The challenges faced in implementing IoT are to bring a high degree of reliability and integrate them into our existing software systems like Oracle or SAP ERP systems for data management. The task also throws up another great challenge, as different software platforms are used in different equipment. For example, the CNC system has proprietary software. This needs to be interfaced with Windows, Android, Unix or IOS operating systems. We have been fairly successful in our attempts so far.
The other major challenge is the cost, as a large number of our customers are from the medium and small industry category. We must be able to provide a viable solution with minimum maintenance.
This technology can help improve our operational efficiency, in the external operations (Customer) and the internal operation at the factory.

Customer

We are experimenting with remote diagnostics and remote machine monitoring tools. This will help reduce travel time of the service engineer and quick start-up of the machine in case the machine requires attention. This is a win-win situation for the customer as well as the manufacturer or service provider.
This will also allow capturing of machine performance parameters on a continuous basis in real time and can be used for product upgradations.
The sales force is also equipped with android-based software to capture customer requirements “on the go” and help us respond to the queries at a much faster rate.
The service team is also equipped to manage service requests through cloud-based mobile applications and stay connected with the customers, their respective regional offices and Head Quarters.

Factory

In our factory we have networked most of the CNC machines on a wireless platform and the real time status is shown on a dashboard. This helps the shop floor manager or supervisor to have a bird’s eye view of the entire shop floor. This has helped increase productivity by about 10 to 15 percent.
Data capturing for longer durations helps us understand trends and micro- deviations, which are normally overlooked in the conventional methods of data capturing. We now get a greater insight into the bottle necks to re-visit the manufacturing process and scheduling, which directly enhances the OEE% (Overall equipment efficiency). This is also a stepping stone to using Big Data analysis in the near future for better decision-making and improving productivity.
To sum up, in the next decade we are looking at the rapid changes in Internet technology, with a high degree of artificial intelligence, which will be incorporated to make the machines manufactured more trouble-free and highly efficient with minimal human intervention.

(K SoundharRajhan, is President – Machine Tool, Foundry Divisions & ATC, Lakshmi Machine Works Ltd. Views expressed are personal

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