Debunking the 'myths' about Industry 4.0
The first myth is the idea of “artificial intelligence (AI) in a box” which would simply require one to supply data without knowing what it means. In practice, those technologies are useful for tasks that are impossible to model, especially those giving the five senses to computers (to analyze images, noise, vibrations, etc.). But they should be combined with appropriate industrial expertise and a physical model of the machines or processes involved. This is quite different from the commercial internet, where consumers are impossible to model and the margin for error is greater. Achieving 90% of suitable purchasing recommendations is a good performance for a bookstore, but experiencing one air crash for every ten flights that take off would be catastrophic for the airline sector. Simply put--AI still takes a great deal of human intelligence to be effective.
The same goes for the 'magic' of big data, where simply investing in collecting data would be enough to bring about valuable data. The problem is, some data is not valuable enough to be collected. Furthermore, other data should be collected but not stored for it can be processed on the 'edge,' meaning within the machine’s embedded system or controller. To obtain a guaranteed return on investment, one should instead start with the technology value levers, meaning the tangible improvements that are expected (faster prototyping using 3D printing, computing power from within the cloud, automated data analysis, agile methodology, etc.). Then one should find a profitable way to confirm and then extract this value on a wide scale (minimal product in a site, a strategy to extend it to other instances and other sites etc.)
Another myth is the belief that traditional skills in materials science, chemistry, or processes could be depreciated by their digital equivalent. In fact, those traditional skills will probably continue to account for 90% of the added value. Admittedly, those businesses among the remaining 10% that are not performing at their top level will be wiped out by the competition. But the same applies to those that might abandon the top 90%. Industry has always thrived through innovation--the future will be no different.
The fourth mistake is to underestimate the human factor and the appropriation of technology. In the past, a great many air crashes happened with correct software and data, but under conditions (weather, fatigue, or stress) where the pilot was having too much difficulty absorbing all of the information coming at him to perform the right action. The risk exists in any place where there are large volumes of information (control rooms, operating blocks, etc.) or tough working conditions (a dirty or noisy environment), or when the software is ill-suited to the qualifications of its users. Industrialists in critical sectors (aeronautics, health, transport, energy, etc.) are quite familiar with those issues, and there are ways to resolve them. Unfortunately, those ways are often ignored by those who are focusing too much on the factory of the future, and not enough on how to make it function in this day and age!