In my last blog I talked about predictive maintenance, a key benefit of Industry 4.0 that’s generally well recognised and appreciated by the manufacturers I talk to.
Another benefit, but one that I think some customers are less aware of, or potentially underestimate the value of, is predictive quality.
What is predictive quality? Well, rather than identifying product defects after they’ve occurred, when a whole batch could have been affected; Industry 4.0 technology means that problems are detected before they’ve actually happened. Data collected by sensors is analysed by MindSphere, our cloud-based IoT system, which can then warn of tiny changes in quality. Crucially, these changes are detected while they’re still within the parameters of acceptable quality and before they cross the line into ‘defects’. This enables manufacturers to fix the problem before complete products have to be discarded.
Although it might not be one of the first benefits of Industry 4.0 benefits that people think of, predictive quality is becoming increasingly important. In the age of digital transformation manufacturers – and their technology - are challenged with producing ever more complex and sophisticated outputs. Mass customisation, for example, gives customers more power to adapt products to their needs leaving manufacturers to produce many different variations on a large scale. But the more complicated the product, the more scope there is for error to creep in.
Predictive quality also has particular relevance for industries that are tasked with keeping pace with regulatory compliance. If regulations change, the data parameters are simply altered and the technology responds accordingly. In this way, manufacturers are sure that their technology is producing products that meet the very latest requirements.
In my last blog I also talked about how MindSphere is also being used to align the cost of the technology with its benefits. Through smart performance finance, a minimum production volume is agreed with the customer (which the production line almost never undershoots) and a pay-for-performance rate is set for production over and above this level. This model has been successfully launched in Germany and is giving customers access to transparent production rates which are directly connected to their finance payments (find out more in our whitepaper).
Predictive quality boosts the value of this model. Since issues that impact quality are detected before they happen, manufacturers won’t find themselves paying for unusable products. Predictive quality therefore provides another reassurance to manufacturers that the risk of such an important investment can be significantly reduced. For organisations that are seeking to justify the cost of their digital transformation journey, and demonstrate that the investment will lead to tangible bottom-line benefits, this is a huge benefit.
It’s now our task not only to successfully communicate all of the benefits of Industry 4.0 technology to our customers (a sizeable challenge!) but also to demonstrate how finance can be embedded as part of the package to make the investment more affordable and justifiable for businesses.
I’d be interested to hear your thoughts on predictive quality and the role of smart finance in enabling digital transformation.
Siemens Financial Services
Head of Region West, Commercial Finance