Automation is on the rise, and it promises to completely transform the world of quality control. But are there any downsides to automated technology? In this blog we explore the pros and cons of automated quality control, and how to use it for the greater good:
Cost savings have to be part of the big picture
To save costs through automation, you need an integrated approach. The machine or solution replacing a human must fit within the bigger picture. You can’t just use a machine to speed up processes: you also have to use the data and link the machine to other systems. The added value of technology is optimized when people really think about processes and how the machine fits into them at the highest level.
The days of just installing a machine and calling it a day are over. In order to have the automated solution fit into a greater whole, we need partnerships between companies. End users can start by adjusting the technology purchasing process. Part of good due diligence before investing in new technology is considering the vendor’s collaboration mindset: who are they partnering with? How do they view their place in the industrial ecosystem? For investments to pay off long term, vendors need to think beyond their own business.
More job satisfaction, with the right training
When it comes to automated quality control, people still fear that they will lose their jobs. But there will never be a point where humans are out of the picture. Automation will accelerate based on how it is linked to people. People are headed toward more job satisfaction by moving into supervisory positions instead of doing the nitty gritty. Their human traits are going to be in high demand to compensate for what machines aren’t capable of.
We know that employee satisfaction is going to be important for our customers to retain their workers. On the other hand, adequate education and training is going to be essential. There are people still being prepared for jobs that won’t exist in five to ten years, and that is not going to work out for anybody. Fortunately there are already initiatives in the US and Europe that are paving the way for the workplace of the future.
Data everywhere, but what about privacy?
Demand for AI technology is growing, and it’s becoming a hot commodity. It’s no longer something that makes you stand out, everyone is going to use it sooner or later. That’s all well and good, but AI is driven by lots of data. How are the vendors offering this technology going to guarantee responsible use of data? Where does the data end up, and who owns it? These questions are key to moving forward with automation.
Data is crucial to improving systems. Still, there are different ways to handle data. There are companies who are very transparent about how they use data, but there are others who stay suspiciously silent because they know they are in a gray area. In Europe this subject is getting more attention than in the US. It is up to the customers to be critical and ask the right questions about this in the coming years, and it is in the best interest of companies to be transparent and responsible.
Want to get a better sense of where we stand on all of this? Get in touch and we’ll be happy to share our vision with you!
- August 2024 (1)
- July 2024 (2)
- May 2024 (1)
- October 2023 (2)
- June 2023 (1)
- May 2023 (3)
- April 2023 (1)
- February 2023 (1)
- January 2023 (2)
- November 2022 (1)
- July 2022 (2)
- June 2022 (2)
- May 2022 (1)
- February 2022 (2)
- January 2022 (1)
- September 2021 (1)
- July 2021 (1)
- May 2021 (1)
- April 2021 (1)
- March 2021 (2)
- February 2021 (1)
- December 2020 (1)
- October 2020 (1)
- September 2020 (2)
- July 2020 (2)
- June 2020 (1)
- May 2020 (1)
- January 2020 (1)
- December 2019 (1)
- October 2019 (2)
- September 2019 (1)
- August 2019 (1)
- July 2019 (1)
- April 2019 (1)
- February 2019 (1)
- August 2018 (2)
- July 2018 (1)
- April 2018 (1)
- March 2018 (1)
- February 2018 (1)
- November 2017 (1)
- June 2017 (2)
- May 2017 (1)
- April 2017 (1)
- March 2017 (1)
- February 2017 (1)
- January 2017 (2)
- December 2016 (1)
- November 2016 (1)
- July 2016 (1)
- June 2016 (1)
- April 2016 (1)