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Hello, my name is Arturo Lavalle and I am the head of the Research and Development department of Guglielmo Marconi University of Rome, Italy.
Industry 4.0 is an expression, which has become very popular over the last years into the political economic and social debates in Europe. It originates from the manufacturing sector particularly the German one where the term was coined in 2012 when the local government asked a group of industrial leaders and representatives of research to draft a plan for the future of national manufacturing and for maintaining the global competitiveness of the German Industry. Industry 4.0 describes the organization of production processes based on technologies and devices autonomously communicating with each other along the value chain, a model of the smart factory of the future in which computer driven systems control and monitor physical processes, create a virtual copies of physical objects and make decentralized decisions based on self-organization mechanisms. Generally speaking, Industry 4.0 is defined by the fourth industrial revolution where the real innovation, the disruptive innovation, is the capacity of technologies of producing services and products through the interaction, in form of networks, among visual object, physical goods, systems of memorization and calculations, communication devices and energy containers.
It is considered the fourth industrial revolution following the three previous ones. The first one characterized by steam power, which lead to the first industrialization since the late 1700s and onwards. The second one characterized by electricity combined with assembly lines during the 1800s onwards, and the third one characterized by the combination of IT and electronics with globalization, which started in 1970s.
Of course, if we consider the industrial revolutions in this way, it could be an oversimplification. In fact, economic historians have been debating whether this phenomenon is the continuation of the third or the begging of the fourth. In any case, the scope of the digital transformation justifies such a definition but it is important to underline that if compared to previous situations this phenomenon presents specific features and diverse scenarios, since the transformation is not quite characterized by new technologies but by existing technologies, combined and operating in a joint way. The repetitive effect of production on innovation has increased, it has a dimension interesting the whole supply chain and all the actors involved including consumers. Finally, it does not affect manufacturing only, but others sectors of economy including agriculture, tourism and public administration for instance. Anyways, before being technological this revolution is also and primarily cultural since it affects the way of thinking about industrial goods, the way of operating into the offices, the modality of working the factories. It concerns the relationship between man and machines and the structures of the factories that are increasingly flexible, sustainable and intelligent. Finally, it regards the relationship among enterprises, since it was born in the big industry; this revolution is rewarding also small and medium enterprises, modifying the supply chain and the set of competences, which are required in order to compete in the market. Surely, who will be moved in this innovative context will not have only a technical preparation and will not differ from the traditional learning methodologies.The Industrial productive system is quickly evolving thanks to the introduction of internet and the new technologies connected with the production and transformation processes as mentioned in the previous lesson.
What are the most important technologies characterizing the new revolution and the new Industry?
In order to answer this question, we can point out, in particular, nine enabling technologies that are transforming the Industrial Production.
The first one, Autonomous Robots. Robots interact and work safely together with humans learning from them. Robots, of course, cost less and have a greater range of capabilities/functions than those used in Industrial production today.
The second enabling technology is Simulation. It is generally used to assess real-time data and recreate physical world in a virtual model. Simulations can involve machines, products, or humans. Between intelligent and inter-connected equipment, simulations will increase the productivity and finally will optimize the industrial process’s achievements.
The third enabling technology is the Hotizontal and Vertical System Integration. Meaning that Integration of information and data is implemented in all the areas of the supply chain, thus as a cross-company, the departments, functions, and capabilities become much more cohesive and the industrial process benefit form a universal data-integration.
The next enabling technology is the Industrial Internet of things. It means that more devices will be enriched with embedded computing. Internet of things implies also to decentralize analysis and decision making process to enable real-time responses and a Multi-directional communication.
Then, Cybersecurity enabling technology. Safe, reliable communications, a complex identity to access data are essential in the new Industry era. New security rules are definitely required to protect data, more and more exposed to the dangers of external attacks. With the increased connectivity as well as the use of standard communication protocols the need to protect critical industrial data from cyber threats increases significantly.
The next, The Cloud. It means that Industry 4.0 fosters the implementation of cloud computing solutions and data management in open systems. Such technology allows the raise of data sharing across sites beyond company boundaries and minimizes reaction time to just several milliseconds.
Then the Additive Manufacturing. It means that Industry 4.0 engages systems of production that improve the resource efficiency of materials, as 3D-printer connected to software of digital development. At the same way, advanced manufacturing solutions ensures high-flexible and performing industrial process.
Later on the Augmented Reality. It means to use augmented reality systems to support production processes. It can support several services, or provide workers with real-time information to improve decision making and work procedures.
Finally the ninth enabling technology is Big Data and Analytics. It means that Industrial process need to make an analysis of a large amounts of data to optimize production processes. It is essential in the Industry 4.0 era, the storage, elaboration and assessment of data coming from many different sources in order to support real-time decision making.
As a conclusion we can highlight that in a scenario characterized by a new economy it is essential for the University, students and academics to be aware of the potential of Industry 4.0 in order to rediscover a new future growth.

Hello, my name is Alessandra Pieroni and I’m a professor in Computer Science Engineering at Guglielmo Marconi University, Rome, Italy.
Concerning the work organization, we know that the smart factory represents a step forward from more traditional automation to a fully connected and flexible system — An environment where the use of a constant stream of data from connected operations and production systems is adopted to learn and to adapt the factory to new demands.
We can image the smart factory as a flexible system able to self-optimize performances across a wide network, to learn from new conditions in real or near-real time, and autonomously run entire production processes.
In this context, the Industry 4.0-based Smart Factory should be: connected, optimized, Transparent, Proactive and Agile.
As said above, the smart factory requires the underlying processes and materials to be connected to generate the data that are required to make real-time decisions.
An optimized smart factory allows operations to be executed with minimal manual intervention and high reliability.
In the smart factory, the collected data are transparent, in other words real-time data visualizations can transform data captured from processes or products and convert them into workable actions, either for humans or autonomous decision making.
In a proactive system, the system should anticipate and act before the arising of issues or challenges, rather than simply reacting after they occur. This characteristic means identifying anomalies, refresh the inventory, identifying and predictively addressing quality and safety issues.
Agile flexibility allows the smart factory to adapt to schedule and product changes with minimal intervention. Thanks to the above-mentioned features, the Industry 4.0-based smart factories are able to self-configure the equipment and material flows depending on the product and schedule changes, and then see the impact of those changes in real time.
The INDUSTRIE 4.0 revolution connects the embedded system production technologies and the smart production processes to lead the factory towards a new technological age able to radically transform industry and production value chains and business models
Concerning the needed competences, we know that a smart factory does not necessarily translate into a fully automated factory. People are expected to still be in the center of the operational process.
However, the smart factory can cause profound changes in the operations and IT organizations, resulting in a new assessment of roles to support new processes and capabilities.
As mentioned above, some roles may no longer be necessary as they may be replaced by robotics (physical and logical), process automation, and Artificial Intelligence.
Other roles, indeed, might be increased with new capabilities such as virtual/augmented reality and data visualization.
New roles will emerge: managing changes to people and processes will require an agile, adaptive management capability, able to face any requirements of the new smart factory solution.
This transformation of the work environment will necessarily change the job profiles and therefore requires employees to be outfitted with a wide range of competencies. In the Industry4.0-based smart factory, a wide range of work profiles will require a higher education, while the workforce-base will be mostly replaced by automated processes.
Thus, the success of any industry depends not only on the machines deployed for manufacturing but also on the labor force employed. For the World Economic Forum, indeed, it is important that the employees have the required skill-sets to operate efficiently. The required capabilities are: Abilities (in terms of Cognitive Analytics, Physical Abilities and Systems Skills), Basic Skills (in terms of Content Skills, Process Skills and Complex Problem Solving Skills) and Cross-function Skills (in terms of Social Skills, Resource Management Skills and Technical Skills).

The use of enabling technologies connected with the new generation entails specific technical skills. New business models and the inclusion in highly competitive markets imply advanced managerial competences. The complexity of productive processes and organizational models ask for new transversal skills.
When we speak about a competences’ model, we mean a valid, observable and measurable list of abilities, competencies and characteristics demonstrated by the behavioral results within a specific working context performance. In other terms, a competences model is a set of competences including key behavioral characteristics that are necessary to excel in a specific role performance.
This concept perfectly matches within the industry 4.0 needs, it contributes to identify the necessary competencies for a precise role within an approach focused on excellence. Highly competitive businesses, high level markets, make the tension towards excellence, essential. The creation of a competence model requires technical tools that could be different depending on their business. However, it is possible to point out common features.
The logical structure could be based on a top down model of competences, meaning that it starts with the manager role who is responsible for the other collaborators. Medium-large industrial realities usually prefer this approach.
In the Core Competency Framework we can list the technical and the leadership competencies strictly linked to the technical and leadership behaviors. On the contrary, smaller industrial realities, in which the organizational structure is not so complex and the managerial role is quite reduced, prefer a bottom up approach that starts from the analysis of experience and competences of collaborators.
On this stage, It could be useful to analyze a general model of competence strictly connected with Industry 4.0, a model that could be adopted in each industrial sector, any company that decides to choose the principles of the new paradigm and develops the enabling technologies.
Eight competences requested for the Industry 4.0 are then mentioned. For each of them, is possible to mention the competency dimension and the list of competences detected. We will mention just a few examples.
The first one, leading and deciding. For example, deciding and initiating, decision making and taking responsibility. Leading and supervising
And the second one, supporting and cooperating. For example working with people, teamwork, collaborating/communicating with others. Adhering to principles and values.
And the third one, interacting and presenting. For example, relating and networking, persuading and influencing, presenting and communicating information.
The fourth one, analyzing and interpreting. For example, writing and reporting, applying expertise and technology, and then analyzing.
And then the fifth one, creating and conceptualizing.
The sixth one, organizing and executing.
The seventh, adapting and coping.
An finally the last competence, number eight, enterprising and performing which includes for example, achieving personal work goals, entrepreneurial and commercial thinking.
Then, at this stage, we can underline three steps for the detection of competences requested in the Industry 4.0. The first step, mapping of existing competences in the work population. The second step, competences requested by the new productive processes. And the third step, identification of possible lacks to cope with.
The first one, on the basis of the analysis we can find a comprehensive map of the existing competences in the active population.
The second step, is the analysis of competences requested by the new productive processes needs to be carried on together with the first. In fact both steps developed allows to make the third, the crucial one.
The third step consists of identifying the competences’ gaps on the basis of the first two phases. At the end of the three steps, the company will have either the list of missing competences or the existing ones.

Welcome! I am Michele Petrocelli, and we are going to talk about creativity, starting with an analysis of Economy 4.0 and the effects of the fourth industrial revolution on the work market and labor market, and the works and jobs of the future.
Therefore, our topics today are; first, what is going on in the labor market? What are going to be the jobs of the future and future of our jobs? Above all, the key skills of the next future in labor market.
The forth-industrial revolution also called the new machine age revolution is going to change our lives. We know we have many advantages, many economic advantages because we have an increasing productivity of efficiency and effectiveness of our production and we reduced risks and fatigue. In addition, we can use big data; big data gives us the possibility measure phenomena as never before and we can use machines for decisions because machines can maximize rationality and rapidity of decisions. However, the problem is that what is happening to the work force and to the jobs now? According to the World Economic Forum’s Report on the future of jobs, current trends could lead to a net employment impact of more than 5.1 million job loss. This is the difference between 7.1 million gross loss and gain of 2 million jobs, new jobs. We are currently facing a situation of future unemployment also known as technological unemployment. Also in this case scenario, economist are in disagreement, but economist are always in disagreement. We have an optimistic point of view and a pessimistic point of view about the same phenomenon.
Optimistic economist say, no this is not a problem it is like in the past we already had three different industrial revolutions and we never really had unemployment, technological unemployment. This is worth mentioning because the increasing productivity will create new markets, jobs and so the new jobs will provide new opportunities, thanks to which we will be able to recover from the job loss caused by the transition to automation and in the machine age. The pessimistic economist say, ok this is true in the past it happened but it is different, very different now, mainly because the change was so rapid. If the transition is too rapid, we will not be able to convert the works into new workers, we will not be able to provide them the right skills for the new system. While we cannot determine whose point of view is right, the only point on which both parties have agreed is that we are going to have a great skill gaps. Meaning that the skills people currently have are different from the skills needed in the new market.
Moving on, the next question is what are those new skills and in particular, how can we develop them? So first of all, we can ask ourselves what role will machines have in the productivity market and what will human beings will still be able to do better. Obviously, machines are going to be better as long as we talk about efficiency and productive tasks, when we have a large number of cases and solid statistics. In addition, when we have problems solving tasks, however they have to be connected with known problems. Humans are still better when we speak about non-efficient and productive jobs, where we have completely new tasks, without statistics, without any history. Human beings are still better when we speak about creativity, empathy, problem solving, ethics, morals and justice. So here, you can see what the top ten skill according to the Economic Forum will be in 2020. We still have complex problem solving, critical thinking or lateral thinking, creativity and a completely new one, emotional intelligence. We had it in the top ten in 2015 and lastly, cognitive flexibility which is also a new skill. Hence, above all, we have to develop creativity and lateral thinking.
However, what is creativity? To explain what creativity is in my opinion I am going to tell you a very old ad famous story, the story of the 17 Camels. A man in the Middle East died and he wanted to divide his 17 camels in his will, amongst his three sons. But, according to the law, 1/2 to the first son, 1/3 to the second son and 1/9 to the third son. However, you know this is impossible because 17 cannot be divided neither by two, nor by a third or a ninth. Therefore, they went to the oldest women in town, and she said I do not know the solution but I can give you my camel. Now they have 18 camels and 18 can be divided by two, so nine camels went to the first son, it is also divisible by three so six camels went to the second son. Lastly, it is divisible by nine so two camels went to the third son. Now you can make the sum. Nine plus six plus two, we will end up with 17, one camel left over to give back to the old woman. So you have the solution. It‘s a lateral thinking solution. No machine will be able to find this kind of solution. This is creativity, this is lateral thinking.

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