The Future of Work in Manufacturing

[CButzlaff]

In this article I am looking at the social impact of past Industrial Revolutions. I am discussing the current, 4^th Industrial Revolution, it’s potential and impact on work in the context of manufacturing. Finally I look at options to mitigate employment risk.

In 2016 the term Industry 4.0, the 4^th Industrial Revolution, was presented to a wider audience at the World Economic Forum in Davos, Switzerland. This concept had been introduced earlier by the German Government, describing the effects of further automation, the use of Internet of Things (IoT) and Artificial Intelligence (AI) to the production and supply chains of modern businesses and business networks. The term 4^th Industrial Revolution implies profound changes to the way we work, much like the former three Industrial Revolutions.

Looking back in history, the first Industrial Revolution, during the mid-18^th century and early 19^th century, is defined by the mechanization of production process by the usage of steam or waterpower. This revolution converted the mainly agricultural societies to more industrialized and urban societies. For example, inventions like the Spinning Jenny[i] moved spinning from the homes of the textile workers to factories. The Industrial Revolution changed society by creating the middle class but also created harsh conditions for those workers employed at the factories, many of whom were children. The anger over the effects of the industrial revolution provoked a variety of uprisings. Examples are the “Luddite riots” by English textile workers against the introduction of machinery, threatening their skilled craft.[ii]. The uprising of Silesian weavers in Germany during the 1840s is featured by the famous book “Die Weber (The Weavers) by Gerhard Hauptmann[iii] and portrays the human cost of the Industrial Revolution.

During the second Industrial Revolution (late 19^th century until the early 20^th century) the industrialization further advanced through production lines and mass production. The most famous example was the introduction of the assembly line by Henry Ford in 1913. In particular in the US, the massive expansion of railroad construction allowed for long distance transportation, opened new markets and eliminated the need for local bartering systems.[iv] The second Industrial Revolution resulted in a period of economic growth due to increase in productivity, the invention of the telephone, advances in medicine and other developments. It expanded the standard of living for many people. On the flipside, the increase of urbanization as well as poor and unhealthy working conditions were the cause for the outbreak of diseases like cholera or tuberculosis[v]. At the same time, machines decreased the demand for labor, resulting in long term unemployment, mainly for women. Social critics pointed to the loss of freedom and independence, which was replaced by boredom and repetition. Early 20th-century movies like Fritz Lang’s sci-fi dystopia “Metropolis”[vi] or Charlie Chaplin’s assembly line comedy” Modern Times”[vii] “capture this fear of the factory worker to become a human robot.

The third Industrial Revolution, driven by the development of the microprocessor, computers, and process automation, started in the 1950s. Computers and robots could automate entire production lines, sequencing production steps without human intervention. The latest inventions like Additive Manufacturing even allow for production on demand. As stated by the toolmaker Sandvik Coromant, “one consequence of the Third Industrial Revolution is that the number of blue-collar workers will continue to decline while productivity increases. More work will be done in front of computer screens” [viii]. The rise of microelectronics took a toll on mechanical labor. For example, a mechanic for mechanical typewriters took pride in his skill, only to see his job to be converted into replacing ink cartridges in electronic typing and copy machines.

During the time of the third Industrial Revolution, global transportation increased, and the world became increasingly more connected, last not least by the Internet. The plant with product design and production line got replaced by a global manufacturing process, driven by a global supply chain, standardization, and an economy of scale at each of the nodes of the network. Only the final product assembly often occurred in or close to the target market. This was pointed out by William Mougayar with the example of TV sets resulting in lower prices for end consumers.[ix] On the other hand, the automation and globalization of the manufacturing process let to a loss of manufacturing jobs in regions like the US or many Western European countries. In 2017,11.6% of the US American GDP came from the manufacturing sector, in 1953 it was 28.1%[x].

The industrial revolutions are sometimes defined in different ways. Some define the first industrial revolution as the transition to manufacturing, the second as the transition to a service industry and the third as the transition based on outsourcing activities[xi]. Others look at the aspect of energy resources used. The first industrial revolution can then be defined by the commercial use of coal, the second as the transition to oil and the third by the transition to renewable energy[xii]. In those definitions, we are approaching a third industrial revolution rather than a fourth. We do see, however, that the advances in technology justify the definition of an ongoing fourth industrial revolution. The characteristics of the other definitions very well fit into the narrative and the move toward renewable energy will become a major influencer of the fourth industrial revolution.

Advances in computer storage, processor speed, and the roll out of 5G networks allow for huge steps in the development of Smart Factory solutions, supported by AI and IoT. Each of the former Industrial Revolutions had impacts on the society. In today’s industrialized world, we enjoy higher living standards and longer life spans; the short-term impacts of the former industrial revolutions, however, were not distributed equally and led to profound short-term negative impacts on mainly the lower classes and most vulnerable citizens. Despite all improvements, as we are approaching the end of the third industrial revolution, the western world is facing profound changes in employment opportunities due to the technical advances. With that in mind, we shall proactively manage any foreseen negative impacts of the fourth industrial revolution to the society and work environments to the best extend possible.

The fourth Industrial Revolution will further drive automation. However, the concept of a Smart Factory goes beyond the automation of production lines. It uses digital technologies to combine processes of design, planning and operations. It leverages the developments in the areas of IoT and AI for decentralized decision making (i.e. “edge computing”). In today’s world, a machine learning model can be deployed de-centrally on a simple device such as a smart phone or small, palm size computing device like a Raspberry Pi, allowing for local, autonomous decision making. For example, real time image classification can improve quality control and intervene early in the production process, limiting further damage. IoT and data science based predictive maintenance, rather than periodic maintenance or preventive maintenance, can reduce cost and optimize spare parts inventory[xiii]. Other examples are autonomous transportation between workstations, autonomous warehouse picking, drone base cycle counting and many more[xiv].

The fourth Industrial Revolution will further transform from automation to autonomy.

In a 2013 article, Frey and Osborn[xv] have discussed the impact of computerization on the labor market. In our context we can look at it from the angle of automation. The article describes a polarization of task into those susceptible to computerization (automation) and those, which are not or less susceptible to it. The former contains mostly routine work, such tasks in and logistics as well as a continuation of production activities being replaced by industrial robots. However, the lines are blurry and will change over time. In an empirical study of highly automated, state of the art automotive assembly lines in Germany[xvi], one of the discussed examples is the following: A worker, controlling parts of a highly automated assembly line, had to intervene 20-30 times per shift. These interventions were not reactions to actual technical incidents but rather intended to prevent them and keep the automated processes running. The interventions were identified and performed by a highly skilled worker and need to be considered as non-routine work. The study emphasizes that the workers main skill was the ability to have a holistic view of the end to end production process. Their intuition and experience allowed the worker to intervene early enough to prevent even the smallest and seemingly insignificant single event that could affect the whole production process at a big scale. An example is the worker listening (maybe even subconsciously) to the machine noise, where a small change could indicate irregularities, requiring intervention or maintenance. But this example does also show that the advances in AI and the availability of big data allow for computerization of this kind of skill. AI based sound and vibration monitoring of the robots could identify early warnings and trigger maintenance activities. Spare parts deliveries could be automatically scheduled. As Frey and Osborn are also showing in their work, computerization does not stop with manual, routine tasks. The technical advances in AI, IoT and Edge Computing will drive a transition from automation to autonomy through machine learning based decision-making, covering routine and non-routine, manual and even cognitive tasks.

The impact on the workforce is that qualification, education, as well as experience and very importantly creativity and social intelligence will be crucial skills and abilities to ensure employability. As concluded by Kagermann et.al.: “Lifelong learning is one of the most important keys to translating the opportunities of the digital transformation into productivity gains and faster and better innovation. In addition, it plays a critical role in safeguarding and maintaining employees’ ability to perform their duties and employability over the longer term”[xvii]. Frey and Osborn concluded that “low-skill workers will reallocate to tasks that are non-susceptible to computerization – i.e., tasks requiring creative and social intelligence. For workers to win the race, however, they will have to acquire creative and social skills”.

The decrease in lower skilled employment opportunities, the displacement of lower skilled jobs and increased requirement for upskilling will leave unskilled and unexperienced workers behind. This consequence can be mitigated not only by training and education opportunities, but also possibilities for career changes into jobs, less susceptible to computerization.

The decrease of the workforce would also decrease the tax income states will receive from those workers and probably increase social benefit payments. As proposed by Bill Gates and others, one way to counter that would be the introduction of a robot tax[xviii]. Depending on the size and format of such a tax, the proceedings should be used to fund re-skilling, training, and education opportunities and even career change activities.

Looking at the high skill workers, they will not be shielded by these developments. Since the beginning of automation, workers were affected by the consequences of the “Irony of Automation”, which was described by Lisanne Bainbridge in her paper in 1982[xix]. A robot is to perform the tasks it can do better and faster than human beings. At the same time, the human being is supposed to oversee the robot and to step in when the robot is failing, which leaves the human being with the more difficult tasks and seemingly unforeseeable situations. The example used was the airline pilot, who relies on the autopilot function most of the time but is expected to take over when the situation becomes critical, Without constant practice, however, the pilot will lose the skills and routine to perform that task with the right intuition, speed and preciseness. Other examples have been described by Gordon Baxter et.al[xx] in 2012, who showed that even during the third industrial revolution this irony remained valid. Going forward, the advance in AI, IoT and Edge Computing will drive a transition from automation to autonomy through machine learning based decision making. The transition will fundamentally change the interaction between machines and humans. Whereas in today’s world machines and human beings occupy different physical spaces, the advances in human robotics interaction and situational awareness allow them to occupy and act in the same space as interacting members of a team. The advances in self-driving cars, moving autonomously through inner cities, are demonstrating this ability. A similar development can be seen with manufacturing robots being aware of their surroundings. Those robots will not need to be isolated from people due to their unthinking motions being safety hazards. Future robots will be tuned to serve human workers: fetch and carry parts, hold, and sort items, clean up and provide real time assistance for production and maintenance workers[xxi]. This can lead to environments, where robots are considered full members of a team of humans and robots[xxii]. The “Ironies of Automation” will expand into “Ironies of Autonomy”, where humans cannot intervene in the machine learning based automated decision making but are expected to and might ultimately be held accountable for it. In her paper[xxiii], Indira Ganesh points out that “Significant legal and accountability loopholes have emerged from these earlier conceptions and require new approaches to protecting human values, as current automation law does not, even though it proposes to. What kinds of rights and protections are there for people working within the platforms of autonomous driving? What is the accountability of AV (author: Autonomous Vehicle) manufacturers in deploying computer vision software that effectively increases the risks of people with darker skin?”

Another trend affecting manufacturing work is the increased consumer demand for a higher level of personalization. The term “lot size of one” is used to describe this development. This is not true for all products (for example commodities like dry wall anchors), but is for those serving the “basic human urge to express themselves, even if they must pay a premium price”.[xxiv] Examples are designer accessories, sport shoes, furniture or even cars[xxv]. The stock price increase of etsy.com, an e-commerce website focusing on handmade or vintage items and craft supplies by 300% in one year demonstrates this emerging trend. Here is where the human-touch comes back into play and where in some cases humans and robots can collaborate and work together as a team. The robot can enhance human craftmanship, whereas the human adds a personal human touch to it, an individualization of design, size, or distinctness of the individual item.

In summary the new industrial world will look more diverse than deserted assembly lines. Different types of manufacturing will co-exist. In mass production low skill work might will replaced by automation and autonomous robots, but even here, there will be a high amount of work available for skilled and experienced workers. In addition, specialized skills will be required for highly individualized production, most of which we might not be aware off today. The collaboration between humans and robots, drawing from each other’s individual strengths, will create additional opportunities going forward. I am optimistic but it will require some conscious decision making to assure that the transformation is fair and will become a winning transition for all, assuring that we will not fall victim to John Maynard Keynes’s prediction of widespread technological unemployment “due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour” [xxvi].

 

 

[i]  https://www.bl.uk/learning/timeline/item107855.html) (accessed February 18^th, 2021).

[ii]  https://www.historic-uk.com/HistoryUK/HistoryofBritain/The-Luddites (accessed February 18^th, 2021).

[iii]  https://www.britannica.com/topic/The-Weavers-play-by-Hauptmann (accessed February 18^th, 2021).

[iv]  https://www.history.com/news/second-industrial-revolution-advances (accessed February 18^th, 2021).

[v] https://www.historylearningsite.co.uk/britain-1700-to-1900/industrial-revolution/diseases-in-industr... (accessed February 18^th, 2021).

[vi] https://en.wikipedia.org/wiki/Metropolis_(1927_film) (accessed February 18^th, 2021).

[vii] https://en.wikipedia.org/wiki/Modern_Times_(film) (accessed February 18^th, 2021).

[viii] https://www.sandvik.coromant.com/en-gb/services/manufacturing/stories/pages/additive-manufacturing-i... (accessed February 18^th, 2021).

[ix] https://yaleglobal.yale.edu/content/small-screen-smaller-world (accessed February 18^th, 2021).

[x]  https://whattobecome.com/blog/loss-of-manufacturing-jobs (accessed February 18^th, 2021).

[xi] https://www.theatlantic.com/magazine/archive/2006/03/a-third-industrial-revolution/304752/ (accessed February 18^th, 2021).

[xii] https://www.polsoz.fu-berlin.de/en/polwiss/forschung/systeme/ffu/forschung-alt/projekte/abgeschlosse... (accessed February 18^th, 2021).

[xiii] https://ieeexplore.ieee.org/document/9023106 (accessed February 18^th, 2021).

[xiv] https://abas-erp.com/en/news/smart-factory-manufacturing (accessed February 18^th, 2021).

[xv] Frey, C.B.; Osborne, M.A. The Future of Employment: How Susceptible are Jobs to Computerisation?

Oxford Martin Programme on Technology and Employment, 2013 https://www.oxfordmartin.ox.ac.uk/downloads/academic/future-of-employment.pdf  (accessed February 18^th 2021).

[xvi] Robots, Industry 4.0 and Humans, or Why Assembly Work Is More than Routine Work, Sabine Pfeiffer, University of Hohenheim,  Societies 2016, 6(2), 16 , https://doi.org/10.3390/soc6020016 (accessed February 18^th 2021).

[xvii] file:///C:/Users/i010078/Downloads/acatech_DISKUSSION_HR-Kreis_engl_01%20(1).pdf (accessed February 18^th, 2021).

[xviii] https://www.futureofworkhub.info/comment/2019/12/4/robot-tax-the-pros-and-cons-of-taxing-robotic-tec... (accessed February 18^th, 2021).

[xix] Ironies of Automation, L. Bainbridge, IFAC Analysis, Design and Evaluation of Man Machine Systems, 1982

[xx] The ironies of automation … still going strong at 30? Gordon Baxter, John Rooksby, Yuanzhi Wang and Ali Khajeh-Hosseini University of St Andrews, Proceedings of ECCE 2012 Conference, 29th-31st August, Edinburgh, North Britain

[xxi] https://www.home.sandvik/de/stories/articles/2017/05/will-your-next-colleague-be-a-smart-robot/ (accessed February 18^th, 2021).

[xxii] There is still a difference though, as the robot will be an expert in a certain environment, whereas the human being is capable to adjust to many environments. My self-driving car is not capable of moving my lawn. However, another robot, the automatic lawn mower is.

[xxiii] https://www.nature.com/articles/s41599-020-00646-0.pdf (accessed February 18^th, 2021).

[xxiv] https://www.isa.org/intech-home/2018/march-april/features/welcome-to-industry-5-0 (accessed February 18^th, 2021).

^[xxv] https://www.mckinsey.com/~/media/mckinsey/dotcom/client_service/bto/pdf/mobt32_02-09_masscusto... (accessed February 18^th, 2021).

[xxvi] Keynes, J.M. (1933). Economic possibilities for our grandchildren (1930). Essays in persuasion, pp. 358–73.