Harnessing the Power of Data to Improve Efficiency

Striking the balance between cost and quality

Harnessing the Power of Data

Error-proofing has become a core focus for every manufacturer seeking to strike the right balance between cost and quality, regardless of their scale or the complexity of the products they assemble. Atlas Copco’s Seven Steps to Securing Product Quality aims to provide manufacturers with a scaleable and flexible roadmap to meet current and future needs by taking a structured approach to error-proofing every aspect of the assembly process.

With the advent of 5G wireless networks, Atlas Copco’s ‘Smart Integrated Assembly’ is designed to work with the latest connectivity technology, which provides not only faster and more reliable data uploads but also significantly enhanced security for manufacturing environments. Atlas Copco’s latest range of digital tools are all 5G compatible.

As manufacturers begin to understand the power that automatically collected and analysed data can have on its operations, and artificial intelligence and machine learning technologies continue to mature, it won’t be long before we see an end to the industry-wide wastage of data.

Atlas Copco has introduced a pioneering application which harnesses artificial intelligence (AI) and machine learning to identify risks in production before they occur. The ALTURE app provides users with real-time manufacturing performance notifications, as well as any ‘Not OK’ (NOK) tightening trends and recommendations for process improvement.

Accelerating value from data-driven manufacturing

Feedback from over 50 of Atlas Copco’s global customers during a 12-month trial confirmed that the app was the simplest and fastest means of delivering real-time information, enabling personnel on the shop floor to counterstrike any emerging issues.

The development of data driven services for maintenance, quality and process optimisation has reached a level where, as demonstrated by applications such as ALTURE, failures can be predicted well before a problem arises, and potential quality issues detected even though the process has been performing within specification.