I.1. A brief history

It was in 1873 that the venerable British University of Cambridge achieved something new, by opening a real physics laboratory within its walls, under the guidance of James Clerk Maxwell – the great scientist to whom we owe the discovery of electromagnetism. This was a completely new idea and the decision to graft a research laboratory to the University began to serve as a model that now seems self-evident. After the transition of the “mandarins”, children of isolated scientists working out of a desire to find and/or understand the world, we arrive at competitive research “factories” with a framework, a place and even, although this is less and less true, regular salaries. Have we gone from a brilliant dandy to a needy mass of millions of research workers around the world because of Maxwell?

What has been lost in this evolution, if not a philosophical approach (a global vision) without remarkably sophisticated (but intelligently designed) instruments getting replaced by precise instruments? A high level of computer science, but without a holistic approach to phenomena related, in particular, to the transformation of matter and energy? In about 150 years, if we refer to this scientist, we will have gone from a thinker/actor to a society of researchers, or rather of research professionals for whom general culture is not a priority. By dividing science into separate disciplines, what knowledge of Nature can we then have? Is Baudrillard (2001) right when he writes: “We are in a world of ‘Sunday drivers’ […], people who have never looked at their engines, and for whom things are not only for their function, but also for their mystery of functioning”?

In addition, the system of funding research and allocating permanent and non-permanent posts is included in New Public Management by forcing people, even if there are charters on researchers’ freedoms, to respect rules in order to be allocated, for a few years, some subsidies (it is necessary to transmit your “submission”). What a chance for the dandy to function in his own way, without being held accountable! But, basically, no one complains about this situation, which is constrained due to the obligation of achieving measurable results… In a few decades, there will be few recriminations and no revolts (perhaps the real researchers did not want to be assimilated to anglers?). Is this reflected in what Aldous Huxley wrote in Brave New World: “All conditioning aims at that: making people like their unescapable social destiny”?

It must be said that after the Le Chapelier Law, the engineer at the end of the 19th Century regulated the manufacturing methods by eradicating artisanal practices and the inductive knowledge system that accompanied them. For the know-how of companions, transmitted from master to disciple, teaching intuition and sensitivity, it substituted the rational and efficient approach of Science applied to engineering. We still live under this system, with reductionist approaches linked to mono-disciplines with an environment that is not very conducive to disruptions: “old technology imposes on new technology its own standards of economic evaluation, developed by reference to its natural qualities, thereby introducing a kind of bias when exercising economic calculation” (Foray 1992).

However, does that which made the engineering sciences such as PE so successful until the end of the Trente Glorieuses (1945–1975) (respecting these remarks of rationality, of fragmentation of research) correspond to what is expected today with the oppressive trends that beset us: sustainable development, global warming, the depletion of reserves, various fundamentalisms, growing inequalities, etc.? Everything pushes us to go towards the marked paths, but do they lead somewhere? So, deep down, is Maxwell an angel or a demon? What about the University of Cambridge?

I.2. A little bit of the future

The Gartner Institute² has published a report on emerging technologies that increasingly involve artificial intelligence and digital technologies. Gartner believes that the combined effects of these technologies will provide unparalleled intelligence, profoundly new experiences and platforms that will enable organizations to connect to new business ecosystems. For example, in the field of artificial intelligence, Gartner expects that deep learning, the technology based on artificial neural networks, will become a crucial component of data analysis and guidance.

However, augmented reality (AR) and virtual reality (VR), because of their ability to blur the boundaries between the physical and digital worlds, are immersive technologies. They are expected to facilitate access to new types of content and profoundly transform the interaction experience for both customers and employees. Gartner estimated in 2017 that, by 2019, AR, VR and mixed reality solutions would have been evaluated and adopted by 20% of large companies. Finally, emerging technologies require a transition from compartmentalized technical infrastructure to ubiquitous ecosystem platforms that are capable of providing more data and computing power. This lays the foundation for entirely new business models and changes the relationship between people and technology. Some of the most well-known examples include block chain, additive manufacturing and its complements (4D printing and bio-printing), the Internet of Things, neuromorphic hardware and quantum computing, among others.

In a more prosaic way, brought to play with matter, for the partial benefit of this highly digitized future, where are we going? This is one of the challenges of this chapter.

I.3. Resolving emerging problems

Even if they have a good image of science in general, the French seem much more skeptical than others about the impact of scientific and technological innovations. They are thought of as being unlikely to consider that these innovations could have a positive impact on freedoms and employment. They are the more likely to believe that they will have a negative impact on freedoms (after the Israelis) and on employment. They express doubts, even concerns, about the risks related to so-called applied research and technological applications. Some even go so far as to denounce a possible collusion of interests between the scientific, political and economic worlds “on the backs” of citizens (Hamel 2019). Process engineering, as an engineering science at the interface between scientific deepening, is considered as disinterested and as the transformation of matter and energy at the service of society. So, if the notion of technological progress is not called into question, to whose benefit does it develop innovations? The debate is engaged in this volume, since it concerns innovation in PE, but will be more deeply engaged in Volume 3.

The material and energy processing industries (TMEs) constitute a stable economic base within the European Union with employment support, in particular for managers. Chemical engineers, who have become process engineers in Europe, have been participating in this dynamic for about a century by introducing rational rules allowing the optimized production of materials and products in a context of minimizing the energy used.

This important field, which has its learned societies and specialized expert committees, is now “well established”. However, as with many other industries, it faces several constraints:

• – energy consumption (chemistry is one of the largest consumers of energy);
• – pollution;
• – reserve management;
• – a poor brand image towards the public;
• – a modest attractiveness to students, who find the concept a little abstruse;
• – a certain stationarity of activities, with incremental innovations;
• – the departure of the best minds in the industry, etc.

At the same time, new technologies are emerging, if only those related to the immense and attractive power of digital technology, which is impacting or will impact process engineering training. This is indeed what is shown in Volume 1 (Schaer and André 2020a) with the necessary modifications that must take into account the new pedagogical technologies, but also the students’ appetites, their sensitivity and their way of understanding a society in disarray.

I.4. Innovating to save the Earth

In this volume, research in the field of “process engineering” is addressed with some disruptive developments. TME is confronted with a need for optimization over the long term (sometimes a century) at the same time as it needs more immediate reactivity, being more at risk and therefore more rarely supported.

But, “innovation must be taken out of the research ghetto: although inventions that create new markets draw heavily on cutting-edge research, many other factors, not the least of which, structure the processes leading to the emergence of new industries and the innovative performance of companies in structured markets. Basic research [normally] creates knowledge, a public good; but it is still far from innovation” (Miller and Coté 2010). The question asked in this remark concerning research aims at an approach of a rather incremental pilot research aiming at an improvement of existing production systems. But what is also expected (rather?) from the academic world is that it should be able to propose possible solutions to overcome new challenges. This bottom-up approach will be the subject of reflections in Volume 3 of this series of books, but already raises some research questions concerning the transition from the idea to the industrial application: it is necessary to invest a little money to carry out a proof of concept with competent researchers and a little “handymen”, but to go further, it is sometimes difficult to find funds corresponding to the production challenges and to carry out a pre-industrial pilot and start with a startup. This is confirmed in Appendix 1 concerning the possibilities of supporting innovation, in particular breakthrough innovation in engineering sciences and particularly in process engineering.

However, new technologies are profoundly transforming industrial production, giving rise to the “factory of the future” or industry 4.0 (Küpper et al. 2017; André 2019a). What will the material and energy production plants look like in terms of their structures, organizations, technologies and processes? What catalysts, what feedstocks will manufacturers need in the future to develop a winning strategy and leadership, and what skills will they rely on? Etc. In this commentary, there is already disruption, a word that has become fashionable, in the ambient “polluted” air.

Today, manufacturers are already working with elements that are part of the plant of the future concept. However, it is already known that achieving this assimilation will require much more than isolated implementations of discrete use cases. “Through the holistic application of new design principles and digital technologies, leading manufacturers can intelligently coordinate all aspects of their plant operations and integrate the value chain that runs from suppliers to end customers. The first manufacturers to succeed in transitioning to full-scale adoption will usher in a new era of industrial operations” (Küpper et al. 2017). This field of digital technology, which affects all industries, cannot be set aside for process engineering and the place of digital technology will be addressed in this volume.

For their new needs or their evolutions in structured markets with high inertia (these are often adaptations at the margin of what is known), companies rely on the academic research community, which avoids this problem (but confines researchers to the incremental, etc.). By creating differentiating factors, disruption is able to change current research standards (who needs it, if only to meet the real industrial needs of tomorrow). Many structures have not yet understood that they will be subject to sabotage, unless, at a minimum, they take the train with a renewed vision of the distant future and goals (so it is not a question of pretending). However, the trained professionals generally subscribe to stable and old basics; the same is true for most decision-makers, far from the reality on the ground, but still committed to strategic planning. The planet is becoming increasingly complex, with shocks linked to digital technology, high tech, sustainable development, cultural diversity, globalization and the emergence in France of new attitudes towards its own achievement (growing individualism, relative distance from work, the value of work under scrutiny, precariousness, etc.), all with a refuge state that considers itself to be thinking in the place of its citizens, who expect it to provide the means and solutions set in stone. Don’t we have the right ingredients to be late for the event!

Volume 1 mainly focused on training. It should be recalled that in this field, the ISF (2016) recommends that the following elements be included in the training:

Initiating pedagogical transformations to adapt the initial training of future engineers to the challenges of tomorrow, in particular:

• – developing the intelligence of complexity by teaching the epistemological foundations and fundamental concepts of complex thinking;
• – accompanying scientific and technical education with the development of a genuine ‘scientific mind’ and in particular a critical mind;
• – preparing for the digital world, not only by mastering technologies, but also by taking a step back regarding design, uses and challenges of data and algorithms;
• – strengthening collaborative skills and student openness through more multifaceted teaching and more collaborative transdisciplinary activities (see also EFCE 2016).

But, after these skills and competences have been acquired, will we be able to develop new processes that will bring out the future?

In light of these comments, we must undoubtedly try to begin – through disruption and convergence – to optimize research leading to innovation around revised foundations, emerging from reassuring continuities. To move forward, it is not only the constraint that forces the movement, but it can help. It is necessary to want to appropriate the questions for a maturation in order to organize a collective imagination, with a certain promise of pleasure (and risk), associated, if possible, with the robust search for solutions, probably more temporary than in the past. In the massification of uncertainty, it is up to proactive and enlightened training courses to prove their present and especially their future desirability and excellence by leaving the current statutory conventions behind. However, the process engineering community cannot help but be affected by the groundswell of disruption – but we don’t know to what degree. The existence of poorly affected areas, such as the manufacture of soda ash or cement, can leave some people in the dark, which would be a serious mistake in a world undergoing profound change.

But, apart from this essential aspect to start and take risks in upstream research, with emerging markets, what will also matter is that we can find adventurers who will have an entrepreneurial spirit, masters of ecosystems and marketing. So, there is “wheat to grind” to meet the challenges that process engineering will face in the coming years.

Finally, in a recent report, WEF (2019a) has just published the 10 emerging technologies for 2019. The results are presented below:

1. 1) bioplastics for the circular economy;
2. 2) social robots;
3. 3) tiny lenses for miniature cameras;
4. 4) disordered proteins as drug targets;
5. 5) smarter fertilizers capable of reducing environmental contamination;
6. 6) collaborative telepresence;
7. 7) advanced food tracking and packaging;
8. 8) safer nuclear reactors;
9. 9) DNA data storage;
10. 10) renewable energy storage on a utility scale.

In this Introduction, we will mention some of the elements present in this list (which, surprisingly enough, no longer reflects the developments in digital technologies).

TECHNOLOGY N. 1 (WEF 2019a). – It should be recalled that in 2014, the industry generated 311 million tons of polymers (said to triple by 2050). But less than 15% of this waste is recycled. The rest is incinerated, buried or abandoned in landfills. They can persist for hundreds of years and debris accumulates in the ocean, causing disturbances to wildlife and ultimately risks to humans from their food. Biodegradable polymers can mitigate these problems and contribute to the objective of a circular economy in which plastics are derived from biomass and reconverted back into biomass.

TECHNOLOGY N. 10 (WEF 2019a). – The development of lithium-ion batteries has exploded, accounting for more than 80% of battery storage capacity on a utility scale in the United States to reach 866 megawatts in 2019. An analysis cited in this report indicates that the cost of acquiring electricity produced from these batteries has dropped by 76% since 2012, bringing them closer to the competitiveness of production units, typically powered by natural gas, that are commissioned during periods of high electricity demand. Other options are still under development to make them sufficiently reliable, efficient and competitive compared to lithium-ion batteries.

Both technologies involve process engineering knowledge and related research. Without the words “process engineering” being expressed in this report, this is one of the first times that the transformation of matter and energy has been advocated by global organizations. It is true that environmental issues, sustainable development and the depletion of reserves must increasingly be considered.

Thus, even if this chapter does not only deal with PE research for the environment alone, it plays a significant role. Indeed, other options must be at work in areas already occupied and especially in new lines of action.

I.5. Framing elements

A researcher must find, invent, create, and this translates into publications, communications, conferences, books, patent applications in certain disciplines. (Petit 2019)

What is a man of science? They are first of all a common variety of humanity, with the qualities of a common race, neither authoritarian, nor dominating, nor assured of their own opinion; they have the assiduity of work, the docility to remain in rank, the regularity and mediocrity of aptitudes and needs; they instinctively sense their fellow men and know what they need, for example, a little independence and greenery without which one cannot work in peace, the need to have their merits recognized, the ray of sunshine of good fame, the desire to be confirmed in every respect, by means of a stamp, their value and usefulness, which helps to overcome the self-confidence that all subordinates and herd animals carry in their heart. (Nietzsche 1989, translated from the French)

Is Nietzsche right or wrong?

Originally, for Boudon (2010), science was born from a vague program: “to describe reality as it is […]. Every scientific discipline describes, classifies and explains.” The main missions of scientific research towards industry and society, as set out in the European Charter for Researchers (EU 2005), are defined by Fitreman (2004) as follows:

• – production of scientific knowledge with a view to developing culture and empowering citizens;
• – knowledge transfer to industries: economic growth, employment, sustainable development;
• – communication with society, bringing research closer to citizens.

This ideal, even angelic, situation is in fact limited for various reasons that are at the origin of this reflection. It is already in opposition to the opinions of Mahé (2002), echoing those of Bourdieu (1976), which define current scientific competition as a power issue: “Maximization of purely scientific profit, i.e. the recognition that can be obtained from competing peers in order to obtain the monopoly of the scientific authority inseparably defined as technical capacity and social power.” But, in the absence of real substantive debates on the existence of the disciplines and associated corporatism, this difficulty of evolution has, in particular, appeared during controversies on the aims of research: increasing knowledge and helping to solve problems of interest to society. For a long time, scientific disciplines have shown their relevance. If they are maintained in the daily lives of researchers, other approaches on boundary objects support more interdisciplinary operations, imposing new, open and ephemeral links between stakeholders (Foley 2016). This world to be explored by science, common to these two approaches, would have required a more in-depth anthropology because it would have required a return to the fundamentals between the goals (which vary according to the reading scales) and the means to achieve them, whether it be process engineering or other science-objects, whose autonomy depends on the sciences that contribute to its development (but is it mutual?).

The difficulty of improving and developing the structures of scientific research is not new. The change must be explained according to criteria of various origins, the robustness of which is sometimes questionable, which leads to modest potential added values, because sometimes they are based on foundations far from rationality. Indeed, the value of the importance of the research activity is undemonstrable, because the objectives of science itself are also undemonstrable. This results in problematic demonstration difficulties. Mahé (2002) considers, for example, that “the conservatism of science is not so much a rejection of change, as this need for consensual norms without which science could not be achieved.”

But what about engineering sciences, of which process engineering is a part? While some of its fields may invest fundamental knowledge, the objects on which the PE sciences focus go beyond this, leading to the consideration of these devices and installations as unknown objects on which a specific scientific investigation approach can focus (Leonelli 2007; Frezza et al. 2013). “The reason for this is due to many factors, in particular uncertainties about the relationships between the various elements. In other words, we do not control everything and we cannot predict everything from the behavior of something complex” (Guy 2012). In this open context, engineering sciences make it possible to master new application fields, with different scales of complexity, with the ultimate goal of operating in accordance with an objective, that is a utility function. “If it is useful to take up a specific validation approach for these new domains, it is because there new properties are emerging for them, although the underlying elementary level is known” (Guy 2012).

It is necessary to appreciate the difference between these two visions of deepening and science-object, requiring a more or less important epistemological approach that enriches both and must be privileged according to the target envisaged. These aspects will be discussed in a specific chapter. The concept of a process is omnipresent in PE sciences. It is based on an abstract framework for modeling processes of all kinds from unit operations (the notion of sequential and parallel “decomposability” according to Lahtinen and Stenvall (2017)).

“The usefulness of the latter [science] is obvious, while that of the former is experience: any new knowledge that may lead to original applications or to the advancement of existing applications” (Piganiol 2004). In essence, the linear stereotype, “science finds, industry applies, man adapts” (slogan of the Chicago World Expo in 1933, cited by (Bourg and Schlegel 2001)), remains particularly vivid because we want to believe in it, because it seems so simple and easy to hear (especially for those who, from basic science, have never developed deep interactions with the socio-economy). Should we accept the opinion of Thierry Gaudin (1978) who writes: “In a way, research is in a fetal situation: an umbilical cord feeds it regularly; well in the warmth, it perceives the noise of the deafened and distant world. From the bottom of her lap, she is fantasizing: the confrontations she imagines are about principles: they are absolute fights, reflecting the uniqueness of her diet. Dissatisfied, she turns around and exhausts herself in internal struggles over dreamlike issues; by conservation reflex, she becomes incomprehensible and incommensurable, takes refuge in an extreme status or its suppression would be equivalent to denying a concept, a metaphysical crime”?

Whatever the model, to guide themselves along their quest, the researcher generally needs to define a scientific framework for action in a structure likely to support them in their intellectual and moral evolution or to make them evolve according to specific imperatives, whilst bearing meaning. To achieve this objective, “reference groups” (Childers and Rao 1992) are involved, which influence behavior through social interaction by being:

• – a source of knowledge and information, constituting a reference on what has been successfully done (chess expertise is generally not available); it can now be profoundly improved thanks to digital technologies (Rosolen et al. 2018);
• – a reference for action allowing for assessment, status and career;
• – a vector for the expression of values (lasting belief deserving personal investment) defining “belonging”.

It is on these bases, without us noticing it, that the research system changes without any clear breakdowns, trying to optimize people and resources. However, at the interface between what is fundamental and what is applied, are the Sciences for Engineering, defined by Ramunni (1995) as the history of a meeting between science and society:

It can be very difficult to publish nil or negative results, even if they are often very important. This created an opportunity for predatory publishers, who do not care about the importance or even the validity of the results, to sell a fake publisher’s title to authors. (Anderson 2019)

But how can they be real politicians, when their very dogmatic formation locks them in the ‘sacred’ texts, keeps them away from the culture of risk and innovation? Faced with ‘badly posed’ problems, which are the lot of the real world, they remain without solutions, because the poorly posed problems are outside the dogma! (Descusse 2019)

Knowing what you know is probably being able to mobilize results, data and facts, but it is also and above all to perceive which questions are at the root of our surveys and which are the methods for reaching a reliable answer. (Girel 2017)

France is even consistently distinguished by its reluctance to reform itself and its commitment to the precautionary principle. We still have […] scientists and a very high level of research. But we did not want to turn it into an economic weapon, we did not know how to do it. (Nora 2015)

This transition facilitated by this quotation will make it possible to introduce some reminders on the functioning of research in general (of which PE is a natural part). First of all, research will not escape the exponential increase in publications (all fields combined), which will raise the question of the relevance of scientific work but above all, the difficulty of reading, understanding and filtering work to derive applications in engineering sciences, or even further from practical applications (see Figure I.1).

In recent decades, the pressure to produce high-quality, validated research has increased. “While this is unlikely to decrease over the next decade, the way they conduct research and develop and maintain skills will change. In particular, the way they collaborate is likely to see dramatic changes” (Anderson 2019). But what will “scientific success in PE” look like in the future? This is an issue that, in this book, is the subject of our interest.

According to the same source, the pressure, reflected in the results presented in Figure I.2, is expected to continue with different origins. A relevant question is whether or not competition leads causally to excellence. Another debate that should be initiated is the quest for funding that takes time and requires evidence (translated into scientific publications) which itself is time-consuming, even if it is integrated into research missions (Dussutour 2017).

Although healthy competition for resources, posts and funding can be considered normal, downstream questions arise about the effects of lobbies, the understanding of disruptions to be made, the risk-taking and foresight of principals who must support (but not only) disruptive aspects related to divergent research increasingly claimed as positive in this highly disrupted world. For Alberts et al. (2014), this state “removes the creativity, cooperation, risk-taking and original thinking necessary to make fundamental discoveries.”

Nevertheless, Stengers (2006) vividly reminds us that “for the hen left free to search as she wishes for her eggs, which are golden due to the techno-industrial innovations that result from them, general progress results and justifies that the state authorities feed the hen. Rather, the knowledge regime is characterized by new and massively intense relationships between academic, state, military and industrial interests.” There is probably a need for a broadening of the scope, because not everything can come from academic research.

Nevertheless, process engineering as a transfer science is located at the interface between academia and industry. Its success in terms of transfers can be associated with a radical innovation difficulty because it does not strictly correspond to a demand from socio-economic circles. On these bases studied by Horckmans (2016), the process engineering sciences rarely develop their own questions (this is therefore outside Le Hir’s (2004) wish).

In the field of processes, interdisciplinary convergence is often necessary. Yegros-Yegros et al. (2015) conducted a study on the relationship between interdisciplinary research and the impact of citations, a measure that can have an effect on the attraction of young researchers to a discipline. What these authors show is that “very low or very high degrees of IR reduce the impact of citations, while some average degrees of IR, which we have called proximal interdisciplinarity, tend to have a higher impact on citations.” Should we in PE, because optimization is part of the toolbox, seek to optimize links with other disciplines?

In addition, scientists have many devices at their disposal to increase their efficiency: research networks, artificial intelligence and mathematical modeling algorithms, increasingly sophisticated measuring instruments, etc. At the same time, current affairs requires a look at the future of employment, competitiveness, material and energy reserves and global warming (De Perthuis 2009), etc. Will we be able to escape all the paradoxical injunctions presented in a very summarized way in the Introduction to this volume?