How do you digitally feel?

Forewarned is forearmed, as they say. The significance of correct diagnosis and timely prophylactics has been well known in medicine, for instance, since the ancient times.  Anticipating negative consequences of some process or agenda is the core of diagnostics. Thus, prophylactics and diagnostics are two sides of the same coin.

The more system is complicated the harder predicting of its behavior becomes. The complexity of equipment has been growing continuously aligning the pace of industrial revolutions happened (four industrial revolutions are commonly assumed where the fourth one is digital). Predictability of equipment functioning can hardly be overestimated in the contemporary environment of fierce competition.

The sustainable economic growth as the non-negotiable scenario of the nowadays business paradigm relies on the very ability to follow the preplanned schedules no matter whether it comes to production or business processes.

Shift people – raise profit

Despite numerous advanced management practices successfully developed for and implemented into business processes, people remain people. The notorious human factor keeps threatening organizations turning a well-established mechanism of staff collaboration into a mess sometimes.

Human errors cannot be excluded completely whatever training or rewards-sanctions techniques are practiced. That’s why the so-called digital pundits are very enthusiastic about the automatization and robotization to be implemented wherever possible. The industrial manufacturing remains the leader in shifting people away in favor of automotive solutions. Leaving the factor of social justice beyond discussions, nobody would argue machines can do work many times more effectively, faster, cheaper, and safer than people do.

The feasibility of robotization in serial industrial production, for example, is undisputable; firing up to 90% of human staff in favor of robots is becoming a norm in the contemporary gadget manufacturing.

Intuition for machines

While changing people for machines making production more stable and profitable is rather an obvious and simple solution, figuring out what can contribute to better performance within the machine-to-machine paradigm is not so straightforward.

For all their imperfections, people have one crucial advantage against the machines in terms of prediction and diagnostics. This is intuition. The human intuition is grounded on life experience, which in turn is based on learning. Once human intuition is worth replicating, something functionally similar should be developed for the robotics.   

And here the digital leap represents the revolutionary methods of diagnostics based on such technologies as Big Data and Machine Learning. The core idea does not lie in something hitherto unknown, nonetheless. The mere meaning of it is statistics. The task is collecting as much data as possible with after-processing in order to get valuable insights about keeping the system’s behavior maximally predictable.

Old doctors’ methodology

Under equal conditions, an old doctor has better chances to make a more accurate diagnosis than a young one because of a wider experience i.e. the bigger number of similar cases happened during the longer practice. Unless the young doctor uses a profound automated solution accumulating information about the similar cases the other doctors have collected. The more data is collected the better statistics appears finally.

However, when it comes to the operation of equipment, the overall sensorization itself is not sufficient for the proper diagnostics and preventive assistance. There should be someone or something capable of processing the collected data rapidly and effectively. Such an “intelligent agent” should recognize and sort all received sensor signals, compare them with predefined threshold values, visualize the results in the form of logical statistics, and represent recommendations worth following.

Early stages matter mostly

The software solutions developed for diagnostics basing on big data processing become popular in the light of the growing trend of IoT (Internet of Things) and IIoT (Industrial Internet of Things). Such IT products work with different hardware generating signals to be processed. Meanwhile, the mere early stage diagnostics becomes valuable above all in the segment of the industrial equipment. Reducing repairing cost by 125% is just the most obvious advantage of the EasySigPro diagnostic system created by Indeema, for example. The advantage is obvious being easily monetized.

However, the other advantages such as saving investment, reducing standby periods, environment protection, and providing staff with more safety working environment all cannot be overlooked. Embracing all possible features and advantages of the EasySigPro or IReDSPro (another Indeema’s remote vibration diagnostic system) solutions, it is easy to come to a conclusion that such early stage diagnostic software/hardware products contributes to saving the most valuable asset of the contemporary business – time.

How machines feel

The computing power evolution allows collecting millions of signals from around the world within seconds for after-processing by the multi-layer artificial neural networks. Hence, the newest paradigm fostering diagnostics appears in the form of IoE (Internet of Everything). This valuable coin sparkles with its two equally important sides - Big Data and Deep Learning. Implementing artificial intelligence technologies assists developers of diagnostic equipment in creating methods mimicking human intuition to some extent.

Robots and people

 

A natural mechanism of anticipating consequences of pain inherent in human bodies can be extrapolated to machines by means of processing of prolific sensor signals comparable with predefined behavioral patterns of equipment. Even the current stage of AI technologies suggests some degree of self-examination of industrial systems. Potentially, such a practice could lead to the self-adjusting and self-maintenance of machines.  

Nonetheless, without going too forward, Indeema represents the right approach to the industrial equipment diagnostics. The above-mentioned EasySigPro and IReDSPro systems compose the actual and imminent paradigm of the intelligent augmentation (IA) where the remaining unrivaled     human intelligence is organically complemented with the advanced software solutions.

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