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Automation helps to manufacture to be more efficient and take less than ever. This, however, has a negative impact on the professional situation of manufacturing workers and low-level administrative staff. Some of their duties have already been taken over by machines, and it looks like more and more processes will be transferred to robots in the near future.
From the business perspective, everything is loud and clear: a machine works faster, needs neither breaks nor holidays, and it definitely doesn't ask for pay rises. Although technologically advanced robots are pricey, their purchase pays off quickly, because you do not have to pay your workers at the same time. The maintenance costs of machines are also acceptable. Many companies are already replacing people with robots, e.g. Foxconn, Apple’s business partner and subcontractor, which is striving to automate 30% of China’s all factory work by 2020.
Machines are not put at risk by hazardous substances used in several manufacturing processes. Robots have already replaced people in a number of areas, e.g. in varnishing, and welding. A machine is also outstandingly accurate as it limits materials losses to a minimum and will not hurt itself. Robots do not care about the noise, temperature, or toxic vapours. Machines help people out with the production of ammunition, caustic and biocide substances, and in the food industry, e.g. in baking and confectionery – in conditions where high dustiness prevails. Some robots are also devised to be destined to work in conditions that are generally harsh and/or dangerous for people, a case in point being made by Method-2 by Hankook Mirea Technology, a Korean company. Boston Dynamics, in turn, has developed a robot called Atlas, able to move even on boggy ground, which will surely allow for applications in all types of search and rescue operations. Interestingly, some parts of Atlas have been printed in 3D, which has made it lighter – it weighs 75 kg, being 1.5 m “tall”.
A robot has the edge on a person in tasks that require repeatability, but you can’t eliminate the human factor in the engineering sector just like that: the more complex robots will become, the better specialists will be required to program them. Also, repair and maintenance work, as well as adding different upgrades and improvements on an ongoing basis will require permanent availability of technical staff in manufacturing plants and factories. It seems that the future of tooling technicians, robotics and automation engineers, and/or robot software developers looks promising.
Low-level staff will not be left jobless overnight, despite the “expansion” of robots. Having said that, these people will have to change their sector of operation or gain new qualifications to stay in the labour market. For sure, some of them will not be left without employment, but they need to get ready for change. Machines have been replacing people for years: for example, they have been gradually squeezing employees out of factories, or – to give a more mundane example – they have been taking over the role of cashiers in supermarkets. Shops have a limited number of full- or part-time positions available, and those replaced by robots have to look for a different job or improve their qualifications.
Around the world, it is possible to notice the development and growing number of AI applications. The engineering sector also draws on the achievements of the field at stake. Optimisation of production cost reduction, and anticipating technical failure – all these processes will entail handling a large amount of data generated each day in manufacturing plants. As a result, Big Data analytics is gaining popularity: vast sets of information received from each machine in a factory are interpreted, and on their basis necessary improvements are made. No-one would ever be capable of processing such heaps of data, and this allows Artificial Intelligence to come in handy. Big Data analytics also makes it possible to control the work done by a machine in real time, add changes, and reduce deviations from the norm. Undoubtedly, Big Data analysts and developers, as well as Data Science specialists, are jobs of the future. The growth of AI can also be seen in the automotive sector: here, autonomous vehicles can’t escape our notice – even though their popularisation is still quite a long way off. The growth of a technology that allows cars to move around independently without the slightest impact of the human factor will open up new opportunities for engineers.
An engineer isn't just a technical profession. More and more often, these roles require skills that go well beyond their specialisation, and emphasis will lie on soft skills. The way we work is changing: we are often required to work as part of a team of specialists from around the globe and different cultural backgrounds; video-conferences and communication based on social media have already become routine. In the age of high demand for top engineers, specialists from the sector need to exchange their experience and keep boosting their qualifications so that they can keep playing first fiddle in the labour market. Today, it is difficult to imagine an expert in robotics or automation who lacks creativity, interpersonal skills, or teamwork skills; not to mention the ability to take constructive criticism. It looks like engineers will have to face up to a real challenge – if their voice is to be heard in the labour market, they have to become an integral part of the Digital Renaissance.
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