Artificial Intelligence remains an emerging field. It has entered the mainstream consciousness through the abstract discussions and concerns among folks like Elon Musk and Mark Zuckerberg regarding future risks, advertisements that put forward an image of AI capability that evokes science fiction, and the increasing rate of movies exploring AI in robots that often end badly for their human progenitors. All of this has resulted in a flawed public perception of the actual state of AI. The following briefly summarizes Aegis’ view on the current technical capability and application value of AI, and then where Aegis thinks this capability can have practical application in manufacturing.
According to LNS Research, Industrial Transformation (IX) is defined as a proactive and coordinated approach to leverage digital technologies to create step-change improvements in industrial operations. Today, around 45 percent of companies are currently executing an IX program. But just because an organization is executing an IX program does not mean it is experiencing the benefits of IX. In fact, it is estimated that 15 percent of companies are stuck in the pilot phase.
One down-side of being human is the realization that not everyone can be considered a “team player”, even at a time of crisis when our entire species is being challenged. Whether creating and delivering key medical devices, critical industry products, or even a piece of software, we all need to focus equally on the potential influence of “bad actors”, as well as the efficiency of doing it right first time. There will be consequences if we don’t.
As momentum around the Connected Factory continues to build, manufacturers everywhere are intently focused on reaching Industry 4.0 in their own factory environments. But to reach Industry 4.0 implies that it is a destination—and that, once reached, one’s quest for Industry 4.0 is somehow complete. The lion’s share of the industry speaks about Industry 4.0 this way. However, to reap the full benefits of the Connected Factory, it is critical that today’s manufacturers approach Industry 4.0 as a journey.
The rapid advancements and utilization of new technologies is simplifying everyone’s life, enabling us to do things quicker, more intelligently, and more efficiently. However, some people see this as being a way to exploit others. One instance of this is counterfeit electronic and mechanical goods, parts and assemblies. As manufacturers and counterfeiters try to out-smart each other with their respective detection and concealment efforts, costs and risk increase as a result. Instead, we should be considering ways to stop this cycle before a severe problem occurs.
Many people are confused by the term “Artificial Intelligence” or “AI”. Touted as part of Industry 4.0, yet it is also linked with the threat of using automation instead of human workers. AI is not hardware but in fact software and not the end to civilization as often portrayed by Hollywood. Let’s look at the fundamentals of AI and put them into perspective, enabling us as an industry to accept the opportunities that so-called AI embodies, without being caught up, by the hype.
It’s no secret that technology is a heavy focus for today’s manufacturers. Unfortunately, many manufacturers often focus on technology as an end, when in reality, technology is a means to achieving better business outcomes.
The promise of the benefits that can be reaped from big data and predictive analytics through access to machine and operator data is compelling enough for most manufacturers to seriously direct their IT and OT departments to look into ways to enable such machine and operator data acquisition. Indeed, being able to optimize overall equipment effectiveness or OEE in terms of equipment availability, performance and quality of produced items by the equipment directly affects manufacturers’ bottom lines.
The act of “putting out a fire” is associated with resolving an urgent problem. Afterward, we worry about the cause, the consequences, and what knowledge we can gain, or so we believe. Quite frequently, this next step is replaced by handling and putting out the next fire. The digital factory provides us the ability to prioritize quality “hot-spots” that require handling. However, in world-class organizations, we must ensure that we complete the additional step and do more than extinguish the flames.
People have begun describing their cloud systems as "the fog." I get the feeling the joke is based on actual events. Are we" venting" gases into the atmosphere with our data during this digital era just like we did during the industrial age? Is it possible to simply throw our data in the cloud and expect a software application to analyze and organize it when we need it? But first, we must begin with an understanding of what the cloud can and cannot do, as well as knowing what is required to make the cloud an effective strategy for storing data that is easily accessed.