Kamran Farooq, sales manager – manufacturing, of Datalogic, the global automatic identification technology and process automation solutions provider, discusses the technologies driving digital transformation in manufacturing and logistics.
It sounds like just another tech industry buzzword, but Digital Transformation is increasingly being referred to as the next industrial revolution and is becoming top of mind for business leaders across every industry sector. According to IDC, within two years, 50% of the G2000 will see the majority of their business depend on their ability to create digitally enhanced products, services and experiences. It won’t stop there either. Organisations of all shapes and sizes, including manufacturing and logistics companies, will need to deploy new tactics and new technologies to compete in the digital economy.
If you are worried about how you will adapt your business to compete against the latest generation of digital native organisations, you are not alone. In fact, research conducted by Silverton Consulting last year suggests that ‘digital disruptors’ pose such a high risk, that 45% of organisations fear they will be obsolete and 3 to 5 years’ time.
What does all of this have to do with auto ID technology?
Since the invention of mass production, automatic identification technology has played a vital role in streamlining processes and delivering operational efficiencies. This is still the same today, only now customer demands and expectations are changing. Supply chain operators, from production line to point of dispatch, must develop new ways to increase speed and offer customisation, while maintaining accuracy, quality and traceability. Imaging, sensor and machine vision technologies are critically important to achieving these goals.
We expect the use of sensor technology to continue to grow in the coming years, especially in quality assurance applications. In Germany, KMS Automation is already utilising Datalogic sensors to ensure the accurate production of clutch housing for automatic transmissions. The chosen sensor generates a LED red light with a Class 1 laser in order to check whether the component is properly seated. Clutch housings have different grooves at different levels. By stacking three or four sensors on top of one another, the entire height of the housing can be inspected to ensure that each groove is located in the correct place.
Imaging technology can also be utilised to reduce errors on the production line. When tasked by their label-printing customers to provide a high-quality inspection process, Converting Equipment International (CEI) looked to Datalogic’s IMPACT machine vision software to help it identify errors before the materials leave the production line and without the need for additional production steps. By integrating an automated inspection solution that could keep up with the high-speed converting equipment, the overall throughput was increased 18-fold. Similar methods can also be applied to many other applications, for example checking that product packaging has the appropriate use by or sell by dates printed. If there is an error, the system can even be configured to stop the conveyor when the affected product is in front of the operator.
Automated pick & pack
The production line is not the only area where machine vision technology is growing in popularity. In logistics operations we are finding that cameras and imagers are increasingly being deployed to streamline pick, pack and dispatch operations. At present, many of these systems are configured to capture information contained in either a 1D or 2D barcode but could that be about to change? By placing cameras or imagers at multiple angles, it is possible to capture a barcode without having to worry too much about the package’s orientation. However, there is still a great vulnerability caused by printed labels themselves and their tendency to become damaged or dirty and unreadable.
To reduce failure rates, it is quite possible that we will see traditional barcodes and printed labels phased out and new methods for marking explored. Laser marking technology for example allows a barcode, text strings and even images to be marked directly onto a number of materials including pure metals, metal alloys and plastic. Digimarc is another possibility, allowing packaging manufacturers to embed digitally watermarked, invisible barcodes to the entire print surface area and making it virtually impossible for a code to be missed.
If neither of these methods is suitable, then machine vision will likely step into the breach. In the same way faults can be identified on a production line, imaging software can also be configured and learn to recognise items in the distribution centre by their unique packaging, size, shape or even weight. This technology can not only aid with picking but can also automate the calculation of shipping costs.
At the forefront of a revolution
There is a wealth of opportunities for image and sensor technologies to streamline operations and help manufacturing and logistics organisations to address the challenges of digital transformation. We have only just scratched the surface in this article. As the industries continue to evolve to meet customer demands by ensuring the right products are delivered at the right price to the right person, auto ID and machine vision technologies will play a pivotal role and Datalogic is excited to be at the forefront of this exciting revolution.