Human skills required include an understanding of the potential of automated technologies, how those technologies can be integrated, including with business and other systems, and skills in business analytic.
Until recently, we had become used to dominance of the bandwagon that promoted the view that the future of developed countries depended on the transition from industrial into knowledge-driven service-based economies. It always seemed that the analyses that led to that conclusion were extremely light on understanding the interdependence of different economic sectors and on the sustainability of export markets for the different sectors. Following the financial crash in 2008, there now seems to be a consensus that, after all, manufacturing is the essential growth driver. So far, so good, but the question then is how can the developed countries, with their relatively high cost bases, compete in manufacturing? The answer has many components, but a significant factor is, of course, automation. Accordingly, the overall market for industrial automation software and equipment is predicted to growth at a healthy pace in 2013; the chart below shows the estimated volume of sales of robots in industry by region.
It’s now over 50 years since the introduction of automation into manufacturing industries—the first robots and numerically controlled machine tools into factories, the development of the first computer-aided design technologies, and even the first computerized production planning and control systems. But an explosion in their capabilities has been enabled by the advances in communications technology over the last 20 years, transforming the structure of the industrial landscape profoundly. In most industries, a suitable mix of automation technology has delivered desired outcomes—the ability to produce more with fewer employees, reduced costs, faster time to market, and so on. Figure 2, extracted from Cambashi’s Market Observatory datasets, shows the full scope of today’s industrial automation technology set. But what has been the impact on the workers in terms of required skills and the nature of their activity; and what is the outlook?
Fewer routine tasks
The most obvious impact of automation is the elimination of routine tasks, be they manual production line activities or repetitive office processes. However, the ability to automate manual work has penetrated much further in the last 10 years, a good example being the extent to which even some aspects of design can be automated.
For specific, highly focused design tasks where the parameters and rules can be defined clearly—for example, routing of electrical/electronic circuits—a computer can certainly produce a viable design automatically. Similarly, for tasks like simulation and analysis, specialized expertise is no longer required to create the model in many cases, due to advances in technology that automate that pre-analysis modeling step.
Understand design principles
Does this mean that the design engineer can get away with lower levels of engineering expertise, a kind of “the calculator eliminates the need for mental arithmetic” effect? Or does engineering expertise need to be augmented by other skills? Today, the latter remains true for most situations. That is, the engineer will need to understand the principles underpinning a design to validate the outcomes of the automated aspects of the process. However, the reliability of automated design technology is improving all the time and in some areas—electronic circuit routing being a case in point—is well-established and produces reliable outcomes. This raises a lot of questions for the future. If the engineer no longer needs to validate the details of the design, what skills will be needed? Surely the detailed engineering expertise must reside somewhere, so is it with the software developer?
The answer is probably that it depends on the industry. But one aspect that is common to all is the point about communications technology. Coupled with dramatic improvements in both ease of use and integration between engineering applications, the ability to search, use, and share information has transformed work processes and the reach of individual engineers. This impacts all areas of the design process, from the ability to access existing options, through assessing more alternatives, to dealing with aspects, such as manufacturability, that might have previously required a hand-off to another engineer. The implication here is that each individual engineer will be in a position to take a broader view of the product development process. To exploit that potential will require a broader understanding of the engineering issues.
We have looked at the impact of automation on design, but what about the domain with which the term “automation” is most associated, the factory? Not only simple production tasks, but even those that may have required a high level of skill like welding complex geometries can be done to the required quality and to a high level of consistency by a robot. The automotive industry, along with the electronics industry, is the major exploiter of robotic technology; see the chart below.
Skill sets are changing
There is no doubt that factory automation results in fewer traditional factory workers; indeed, it’s one of the main justifications for automating. So here again we have the question of the impact on the skills required of the workforce. For the factory, the skills shift is more significant than for other areas. The use of automation technology does not eliminate the traditional jobs altogether. In fact, understanding the manufacturing technologies and processes in the factory is a vital ingredient for process improvement. Nevertheless, the majority of roles will change in nature, at a minimum towards operating more complex computer-controlled equipment.
This trend will increase with the uptake of new technology that enables the “Internet of Things” and its exploitation for industrial Internets. This trend exploits the ability of machines and devices to exchange information over the Internet without human intervention. A recent example is GE’s new advanced sodium-nickel battery plant in Schenectady, N.Y. The plant is peppered with sensors to measure all manner of manufacturing process data (cycle times, process parameters, material tracking, etc.), not only supporting a high degree of automation but also enabling comprehensive process analysis to identify opportunities for improvement. The human skills required are therefore an understanding of the potential for automated technologies, how those technologies can be integrated, including with business and other systems, and skills in business analytics.
The ability of devices to exchange information over the Internet without any human involvement also has major implications for higher-level factory and supply chain management activities. It will not be long before we see those activities having significant automated content as inputs like supply chain status, production status, quality information, and so on are fed automatically into a new planning run. Even the agent of much of the automation in industry, software, is experiencing substantial progress in the automation of its development, with technologies like model-based code generation gaining ground all the time.
Integrated digital factories
While, from an engineering perspective, the technologies that underpin digital factories are fascinating, any discussion of the impact of automation on the workforce should include a global perspective. This is a very large and broad-ranging topic, with no easy answers. While the developed countries see their future post-industrial economies involving high levels of automation, as shown in the chart in Figure 1, Asia is already the largest consumer of robot-based factory automation technology. So, while proponents of automation claim that it gives the high-cost countries the necessary productivity edge to compete in global markets, leadership in exploitation of the technologies is vital. A good example is achieving effective integration between the factory floor and the rest of the enterprise. This is a dynamic and evolving picture, requiring constant assessment of the opportunities for IT-enabled process change in the planning and execution of manufacturing activities. To achieve this requires a broad combination of IT and industry skills.
From this point of view, the developed countries should maintain the advantage for perhaps another decade; but over time, the approaches and methods will be adopted by emerging countries and the need to find other sources of advantage will be pressing. In the short term, it is true that the roles in manufacturing will not be as plentiful as in the past and that many of them will require more advanced skills. In fact, we must bear in mind that we may have reached the point where technology has become so pervasive that, despite the activities involved in its development, implementation, and maintenance, it is a net eliminator of jobs. The retail industry has suffered just this under the impact of Internet-based automation. Perhaps the most valuable skill of all will be adaptability!