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There is no shortage of essays, discussions, conferences, or books that address interaction between the human and the digital world. There is, however, one aspect of human activity that is particularly illustrative and interesting to address: the manufacturing environment

 

Today, the penetration rate of the “smart machine”[1] in the manufacturing process is increasing at an exponential rate. The performance, the functionality, and the complexity of each “machine” is rapidly increasing. The fact that more and more machines coexist with one another further accelerates the growth of performance and functionality, while increasing the complexity of the overall manufacturing system. Further, individual “machines” and overall systems are becoming increasingly flexible. This fast and radical change is already modifying the role of the human. What are humans’ expectations, and how will they fit into this rapidly changing manufacturing paradigm?

People as employees

People as employees of manufacturing corporations are facing a radical change in the way they are integrated into and evolve in companies, the economy, and society. The first, certainly well-addressed, aspect of this change is the shift in the skills required of people. It seems almost unnecessary to illustrate this: manufacturing (and, more globally, industrial) sites need increasingly dedicated IT capabilities. In the past, a worker who had to operate a lathe needed to know how to do so. Today, the worker who operates a numerically controlled lathe needs to operate the IT system that controls the lathe and, of course, to understand the functioning of the lathe.

The demand for new type of skills leads to the question of where and how these skills are to be acquired. Technical schools or technical universities have trained young people in late adolescence or post-adolescence. Today, this kind of system is no longer viable since workers need to acquire new skills continuously. A window of opportunity for creating new structures and methods for lifelong training and education adapted to the continuously evolving environment is now opening.

 

This lack of the skills required by industry fuels unemployment. And that unemployment impacts those closer to retirement age more than it does young people. “Robotization” and automation amplify this trend, because—globally—the overall number of blue-collar manufacturing jobs is decreasing. And even if we postulate that jobs lost to robots and automation are going to be replaced by other types of jobs, jobs that create greater added value (and therefore pay higher salaries), it is probably not the blue-collar workers that are suffering from this transition that are going to get those new jobs.

 

Another societal impact of the transformation of blue-collar jobs is the expected increase in rates of telecommuting. telecommuting for manufacturing jobs, meanwhile, has until recently been unthinkable. This, however, is ready to change. Blue-collar telecommuting can, for example, simply involve the replacement of certain on-site operations by equivalent remote operations. So, for instance, the replacement of in situ monitoring by tele-monitoring—a one-to-one replacement. Over time, a significant portion of this inspection process will be replaced by sensors that continuously monitor and communicate the status of machinery. This time around, it means the replacement of a blue-collar inspector by technology.

 

One novel development that is proving disruptive in today’s world of manufacturing is the creation of digital twins of individual machines or even entire manufacturing plants. A plant’s equipment and infrastructure can now be fully simulated using computer models. we are seeing work shift from blue-collar inspectors to white-collar software engineers.

 

The transformation of the work

 

One important trend is the transformation of “normal” workers, over time, into “augmented” workers. In a large manufacturing plant a worker needs to repair a complex piece of equipment—say, the electronic control element of a turbine. Traditionally, this worker would approach the machine equipped with nothing more than her or his tools and a manual, empowered by training and experience to carry out the repair. In the years to come, it is highly likely that this worker will approach that same machine, but this time he or she will be wearing mixed reality glasses that supply, in real time, both advice and details of the series of actions that need to be performed. The benefits of such a setup will be enormous, in terms of both repair efficiency and operational downtime. And there will be other benefits in terms of the safety and security of the repairperson, the machinery, and society in general—particularly in potentially hazardous circumstances such as the need to repair critical infrastructure (e.g., electrical powerlines or nuclear reactors).

 

Looking a little further into the future, visual tools such as special, smart eyewear will be used, not only to exchange visual and acoustic information but also to control equipment and machines.. In potentially high-impact cases (e.g., where high cost or safety and security questions are involved), such tools may prove invaluable. Think, for instance, of situations in which rapid and precise responses are required—a sinking ship, or the repair of a large turbine.

Smart eyewear, as briefly outlined above, is one among several means of intuitive communication between a worker and a machine, based upon real, existing technological tools.

 

The notion of the augmented is not limited to the interaction of repairpersons with machines, the strength of a person can be mechanically reinforced. Exoskeletons can be employed to reinforce a person’s muscular structure. This can increase the capacity of an individual to carry a load, allowing a person to work at multiples of his or her unaided capacity. In productivity terms, this means improvements in a number of jobs that require muscular strength. In security terms, this might mean an increased capacity to handle unexpected loads and being better protected should an accident occur.

The technologies above are simply illustrations of the upcoming revolution of the augmented person. They lead us inevitably toward increased productivity, increased security, a change in the skills required of workers, and reductions in our need for human resources. The response from the economy and society should include increased and lifelong training, and measures to improve time management, both for active workers and inactive individuals.

 

In the future, it is very likely that we might observe a more radical change in the production mode. The act of making things can potentially simply be displaced from a traditional manufacturing environment to the home, or to limited capacity premises. As an example of such a radical transition, we might see the serial production (i.e., unit-by-unit production) of small-scale series of devices that can be produced at home using 3D manufacturing. This trend is coherent with the shift—observable today—from mass manufacturing to mass customization, and in some cases to personalized manufacturing. We are not, of course, going to produce hip prostheses at home. But a number of goods that can be personalized to the needs of the individual (with respect to morphology or personal taste—so, for instance, footwear or glasses) or to the configuration of the built environment (so, for instance, a house’s architectural structure) could be produced at home, based on basic designs fine-tuned by the individual user to suit his or her specific needs. This trend is even transforming the very nature of commercial relations, converting the user into a manufacturer–user. Though the nature of this transformation may, at first glance, be difficult to grasp, it is the natural extension of what we have already seen with regard to service provision, where individuals reserve their own flights and hotel rooms on the Internet (now an everyday practice), thus converting themselves from simple users to users–travel agents.

 

[1] “Smart Machine”, here, means every Information Technology that helps humans with regard to the manufacturing process—from large computers to robots to sensors to computers.

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