From its conception in 2011, and then its recommendations for implementation in 2013, Industry 4.0 has become a must researched and discussed topic globally. The vision of Industry 4.0 brings together the opportunity for many design principles, such as service-oriented architectures, decentralization of decision-making, interoperability of cyber-physical systems, virtualization of the physical world, real-time accessibility, and flexibility or cross-discipline for adaptation [1] .
The goal of Industry 4.0 is to generate value, improve operational effectiveness, create new products, services and business models, and develop problem-solving tools. Moreover, a recent study stated that Industry 4.0 holds the potential, and qualifies as a valuable practice that can meet the requirements and expectations for sustainability in three aspects, i.e. social, environmental, and economic [2] . Therefore, expectations seem optimistic about what relies ahead upon the future of industrialization.
Considerable amount of research has been done on discussing, developing, and applying tools, technologies and architectures for implementing Industry 4.0 (i.e. Internet of Things (IoT), Cyber-Physical Systems (CPS), Cloud computing, Big data, Information and Communication Technologies (ICT), Service-Oriented Architectures, etc.), yet there is a need for further aspects to take into consideration, i.e. the social consideration and preparation.
Human resources need to adopt and adapt themselves to this fast-paced Industrial Era. A study shows that the lack of qualified human workforce is among the top three challenges for companies to adopt Industry 4.0 [3] . Moreover, it has identified that one of the priority areas for research activities is the training and continuous development of the workforce. Education and adequate upskilling of students and employees are required for a proper Industry 4.0 criterion, such as future sustainability and creation of value. This requirement invites opportunities for new ways of tackling such an existing issue.
The goal of this paper aims to support the education and upskilling of the human workforce by providing a new perspective on the topic. This perspective was inspired by identifying existing challenges as well as recent educational efforts for future employees. It is appreciable to see that the
From its conception in 2011, and then its recommendations for implementation in 2013, Industry 4.0 has become a must researched and discussed topic globally. The vision of Industry 4.0 brings together the opportunity for many design principles, such as service-oriented architectures, decentralization of decision-making, interoperability of cyber-physical systems, virtualization of the physical world, real-time accessibility, and flexibility or cross-discipline for adaptation [1] .
The goal of Industry 4.0 is to generate value, improve operational effectiveness, create new products, services and business models, and develop problem-solving tools. Moreover, a recent study stated that Industry 4.0 holds the potential, and qualifies as a valuable practice that can meet the requirements and expectations for sustainability in three aspects, i.e. social, environmental, and economic [2] . Therefore, expectations seem optimistic about what relies ahead upon the future of industrialization.
Considerable amount of research has been done on discussing, developing, and applying tools, technologies and architectures for implementing Industry 4.0 (i.e. Internet of Things (IoT), Cyber-Physical Systems (CPS), Cloud computing, Big data, Information and Communication Technologies (ICT), Service-Oriented Architectures, etc.), yet there is a need for further aspects to take into consideration, i.e. the social consideration and preparation.
Human resources need to adopt and adapt themselves to this fast-paced Industrial Era. A study shows that the lack of qualified human workforce is among the top three challenges for companies to adopt Industry 4.0 [3] . Moreover, it has identified that one of the priority areas for research activities is the training and continuous development of the workforce. Education and adequate upskilling of students and employees are required for a proper Industry 4.0 criterion, such as future sustainability and creation of value. This requirement invites opportunities for new ways of tackling such an existing issue.
The goal of this paper aims to support the education and upskilling of the human workforce by providing a new perspective on the topic. This perspective was inspired by identifying existing challenges as well as recent educational efforts for future employees. It is appreciable to see that the
From its conception in 2011, and then its recommendations for implementation in 2013, Industry 4.0 has become a must researched and discussed topic globally. The vision of Industry 4.0 brings together the opportunity for many design principles, such as service-oriented architectures, decentralization of decision-making, interoperability of cyber-physical systems, virtualization of the physical world, real-time accessibility, and flexibility or cross-discipline for adaptation [1] .
The goal of Industry 4.0 is to generate value, improve operational effectiveness, create new products, services and business models, and develop problem-solving tools. Moreover, a recent study stated that Industry 4.0 holds the potential, and qualifies as a valuable practice that can meet the requirements and expectations for sustainability in three aspects, i.e. social, environmental, and economic [2] . Therefore, expectations seem optimistic about what relies ahead upon the future of industrialization.
Considerable amount of research has been done on discussing, developing, and applying tools, technologies and architectures for implementing Industry 4.0 (i.e. Internet of Things (IoT), Cyber-Physical Systems (CPS), Cloud computing, Big data, Information and Communication Technologies (ICT), Service-Oriented Architectures, etc.), yet there is a need for further aspects to take into consideration, i.e. the social consideration and preparation.
Human resources need to adopt and adapt themselves to this fast-paced Industrial Era. A study shows that the lack of qualified human workforce is among the top three challenges for companies to adopt Industry 4.0 [3] . Moreover, it has identified that one of the priority areas for research activities is the training and continuous development of the workforce. Education and adequate upskilling of students and employees are required for a proper Industry 4.0 criterion, such as future sustainability and creation of value. This requirement invites opportunities for new ways of tackling such an existing issue.
The goal of this paper aims to support the education and upskilling of the human workforce by providing a new perspective on the topic. This perspective was inspired by identifying existing challenges as well as recent educational efforts for future employees. It is appreciable to see that the 48th SME North American Manufacturing Research Conference, NAMRC 48 (Cancelled due to identified efforts (section 3), although considerable, are not sustainable and compatible enough to address the identified challenges (section 2). To this end, we propose a flexible architecture that will aid education and training means to become more robust and compatible to address the future challenges in Industry 4.0. Figure 1 helps to visualize the attempt of this paper on mitigating the incompatibility between the two, existing challenges and identified efforts. The rest of the paper is summarized in the next lines. In section 2, existing challenges for future workers are described. Section 3 reviews the different attempts that have emerged to support the education and training of graduates for future manufacturing. In section 4, we present a novel architecture model that highlights a human-centric perspective for addressing the upskilling of workers. Besides, an example of an application is illustrated. Sections 5 and 6 give benefits, discussion, and conclusion.
This section identifies five main issues that the future workforce needs to be prepared to seek solutions. Such problems are of recently highlighted importance from different countries and institutions, mainly due to the fast-paced industrial development occurring worldwide. Therefore, we analyzed the skill and developing needs of the future workforce from these identified problems.
1. Skill gap and tech-changes unawareness. A significant amount of studies, reports, and documents from different nationalities, i.e. Europe, New Zealand, the US, have been appointing the absence of various types of competences in both graduates and existing workforce [4] - [6] . Such skills can vary from soft, technical, digital and even cognitive skills. Also, it was suggested that dissemination of the Industry 4.0 topic among younger generations is required because there is still an unfamiliar concept and technology awareness.
Aging Ageing population, ageing workforce. Different zones across the world are concerned of their ageing population, looking at the issue with special attention to those who are retiring from jobs. The problem arises since there are not enough employees in new generations taking over such job positions and activities. Places in Europe, Asian regions, and New Zealand have already started taking action. They are implementing initiatives and strategies to tackle this problem [7]- [9] . The consensus among these initiatives indicates that this problem threatens both labor productivity for a single company and the total factor productivity (TFP) growth of a country.
Compromised wellbeing. It has been recognized that wellbeing should aim for employees and society striving towards a balance between professional and personal lives. Presently, there are not only professional challenges to be addressed, but individual and social ones as well. Recent research recognizes that today chronic conditions, such as cancer, diabetes, dementia, and autoimmune disease, among others, are serious problems for a considerable amount of individuals in society [10]. Moreover, it has been detected that those physical conditions, along with emotional ones (i.e. stress, mental workload) are factors associated with reduced length of working life and ongoing absences at jobs [11] . Furthermore, issues like loneliness, anxiety, and suicide are emerging at higher rates around different countries, i.e. the US, the UK, Australia, New Zealand [12] - [14] , which affects not only society but the economy of the nation.
Volatility, Uncertainty, Complexity and Ambiguity (VUCA). Nowadays, organizations are facing the challenge of transiting from traditional ways of operation to more novel, dynamic, and adaptable processes brought by VUCA conditions [15] . These conditions impose some threat to companies for achieving high levels of flexibility, agility, and management of their operations and resources. This threat affects businesses and manufacturers alike, especially those seeking shelter under the scheme of Industry 4.0 and the future of manufacturing. Moreover, as production tools, machines, and systems, i.e. Cyber-Physical Systems, are increasing their level of complexity compared to previous Industrial Revolutions, companies could face difficulties in raising capital investments for both the machinery and the skilled workforce. The new perspective of future manufacturing is leading towards novel practices of creating value, going beyond the idea of mass production, which then brings opportunities and challenges for companies, in particular, small and medium enterprises (SME's) [16] .
Resources' utilization and climate change. A smart city, or a smart company, align to Industry 4.0 principles, should look for four main scenarios. The share of facilities (i.e. cars, machinery), the reduction of storage and resources, the implementation of service-oriented scenarios, and the promotion of accessibility instead of mobility. Holistic approaches, such as Smart Grids need to be explored to achieve these goals. These grids aim to reduce energy consumption, minimize faults and maintenance, distribute automation, increase flexibility and efficiency, and reduce costs through industrial wireless networks (IWNs) [17] . However, there is still some time and efforts required before achieving such grids at the scale of two or more companies. As per clime challenge, the United Nations has set paramount objectives to aboard urgent environmental challenges that pose risks to society, such as climate change [18] . They invite environmentally sustainable manufacturing practices that consider both consumers and the environment.
The new Industrial Revolution does disrupt not only businesses and manufacturing industries but also the educational system. Education is a major driver of economic growth. Education 4.0 is a new proposed term that highlights the evolution of education, going from the past to the traditional way, to the now foreseen education [19] . The concept includes seven facets of the future of education: content, means of learning, means of interaction, the flexibility of adaptation, means for supporting learning, and assessment methods. The concept of a teaching factory has also been suggested to facilitate the teaching, applicability, and training of Industry 4.0 principles under the idea of Education 4.0. The teaching factory concept could be implemented in laboratories at universities or in floor-shops at companies.
Although the framework of Education 4.0 offers some guidance on directing the future of teaching and training, there are still challenges in identifying the proper content to be taught that meet the needs in the job market. It has been repeatedly reported that the existing situation of labor offer, students and employees, does not meet the adequate criteria of skills to engage in the job demand. As previously stated in section 2, there is the demand for competences, such as soft skills (i.e. flexibility, decision-making, cooperation), hard skills (i.e. process understanding, interdisciplinary knowledge), digital skills (i.e. digital literacy and networks), and cognitive skills (i.e. problem-solving and analytical thinking). Moreover, emotional intelligence has also been identified as a need for engineering training [20] .
Some international programs and approaches have been proposed and set forward to address this educational issue. For example, a Japanese program looked at incorporating a new social perspective in their curricula to generate a practical and creative engineering experience, which involved various fields of application [21] . The program tried to emphasize the relationship between engineering and society. In Europe, a Turkish-German University elaborated a framework with three main aspects. (1) a curriculum that is highly focused on computing and ICT subjects; (2) a Visual Production Lab that is equipped with Lego Mindstorms, a drone, and 3D printers;
(3) a student club of Industry 4.0 that involves research projects and organization of conferences [22] . In Germany, special attention is paid to subjects that involve MINT (Mathematics, Information Technologies, Natural Sciences, and Technology), since it is thought that they are important for the invention of novel future technological developments [23] . The ELLI project is a German example of collaboration between three universities, and in its first stage, it has developed a network of virtual laboratories to increase the didactics of innovative education in Industry 4.0 technologies.
Another institution in Ireland has focused its attention on a post-program, which emphasizes interdisciplinary collaboration between the program and the local industry needs [24] . The program is carried out in a laboratory with the physical and digital twins of manufacturing cells, where students research theoretical and practical knowledge. Similarly, the program topics are technologically driven. On the other hand, the Swedish focus is more on research, innovation and PhD education with a program called Produktion2030. The aim is to develop six areas of manufacturing: sustainable environment, flexible production, virtual production, humans in the production system, product/production based services, and production development [25] .
The US focuses on developing STEM content (Science, Technology, Engineering, and Mathematics). For example, a program for training and upskilling high-school teachers on manufacturing education was created to introduce production and design topics to the high school curriculums [26] . However, a study found that undergraduate engineering programs have a considerable number of domain subjects (i.e., engineering sciences, process/product development, materials, quality), but they leave less room for others equally important for the future of manufacturing (i.e., innovation and entrepreneurship) [27] .
As an overlook, it can be seen that most educational efforts found in the streamline of literature tend to be technologicalbased (i.e., computational) or subject-based (i.e., engineering), rather than competency-based (i.e., cognitive). The efforts in literature seem to be mainly hard-skill driven, that is, specific skills to do a job. Therefore, these programs, whether for education or training, might become more robust by considering an approach that focuses on competence development more broadly and specifically at the same time.
There is an urgency to meet the needs of individuals, i.e., those in section 2. The ideas of professional preparation mentioned in section 3 barely support the five issues as a whole. Therefore, there is an opportunity for improvement in the approach to meet such requirements.
This section aims to make contributions towards improving such an approach. The idea is the creation of a mediating architecture by driving attention to the content to be taught and learned or to the issue and challenge to be solved. This approach is by considering a competency-based model, which involves the age range and the context of the environment. Therefore, from a human-centric perspective, the first thing to do in our approach is to identify what basic skills constitute a worker and systematically classify them.
In this section, we have identified five main competences that could comprise any person or worker, where every competence is supposed to serve a singular function different from one another. At the same time, two main classifications have been inferred.
A) Inner-self interaction competences. They can be seen as the core competences in any person, as they support internal thinking and controlling before any interaction or engagement into an activity to the outer world.
1. Self-awareness. It is the capacity to recognize that oneself is in consciousness above her/his mind. Therefore, the person can recognize and act upon such acknowledgement. A well-known competence for this capacity is Emotional Intelligence (EI), as this is the ability to control and discriminate the use of one's emotional status [28] . In other words, it is the ability to control self emotions, i.e. stress or anxiety, and also to understand them in other individuals.
2. Cognitive functioning. It is the ability to understand the physical world through the processes of the mind, and it supports the capacity of learning of the person [29] . The bestknown competence is Intelligent Quotient (IQ), which normally measures capacities like memory, math, reading/literacy, coordination, and analytical thinking. B) Outer-world interaction competences. They allow the capacity to interact with the external environment through outputs or actions. There are two main ways of doing this, interacting with people, and carrying out a job or task.
3. Interacting with people can be supported by the application of soft or social skills [30] . These skills allow the person to communicate, work, and collaborate with others.
4. Performing a job or task can be developed by the application of hard or technical skills [31] , and most people must have a certain degree of these by the time they go to a new position or role.
5. The new age of digital technology is pushing and making people to become digitally interactive. The competences that support this interaction of the modern world are called digital skills, and they allow the operation of digital technologies and systems to carry out any given activity [32] .
In this sense, five main competences have been identified that support human understanding, development, and action towards a given activity (see Figure 2 ). 
We used the Reference Architecture Model for Industry 4.0 (RAMI 4.0) [33] as a reference model to create a humanoriented architecture. Nevertheless, in this case, instead of being a technological and business-driven framework, the proposed architecture displays a human-centric perspective.
The model is divided into three spheres or variables: the Competence Layer, the Lifetime Cycle & Value Stream axis, and the Zone Levels axis (see Figure 3) .
The Competence Layer represents the vertical axis with the previously stated competences (self-awareness, cognitive, soft, hard, and digital).
The Life Cycle & Value Stream axis represents the commonly known life stages of a person during a lifetime. There is the assumption of creation, maintenance, and use of value (i.e. experience) accumulated through time. The stages are divided into childhood (3-11 years), adolescence (12-20 years), early adulthood (21-35 years), midlife (36-50 years), and mature adulthood (50+).
The Zone Level axis reflects the different scenarios from which a person can interact and perform activities. These context-based scenarios are divided into individual (solo), family, society, workplace, natural environment, and international world.
The idea for the RHAM is to be able to map crucial aspects of the human ecosystem to support the understanding and development of a person or group of people. This identification should facilitate dynamics and adaptability to offer education and training according to the needs involved considering the competence, the age, and the context. 
The proposed model allows flexibility to customize the educational or training content according to the needs. The method of application of the RHAM can be from two angles. First, it can be applied directly to an existing problem, and second, it can be applied to a current or expected educational program.
The following list of question have to be considered and answered to apply the developed architecture from an existing issue point of view (see Figure 4 ). The following number of questions have to be considered and answered to apply the developed architecture from the view of an expected educational or training program (see Figure 5 ). The following scenarios were created to try to display its applicability at this stage. For these examples, only two issues mentioned in section 2 are considered.
One challenge was to meet the skill gap and the lack of knowledge of Industry 4.0 among young generations. Therefore, the application of the RHAM to tackle this problem may be suggested as follows:
Example 1: What is the existing problem? R= Skill gap and lack of knowledge of Industry 4.0
What is the age range that involves the problem? R= 12-20year-old (adolescence)
What is the zone levels involved/affected? R= The workplace and individual
What are the self-awareness skills needed to support the adolescences on the problem? R= Emotional awareness along with its personal and labor importance What are the cognitive skills needed to support the adolescences on the problem? R= Industry 4.0 concepts and ideas, and involvement of abstract reasoning and analytical thinking
What are the soft skills needed to support the adolescences on the problem? R= Willingness and openness to interact with others in person as well as through devices
What are the hard skills needed to support the adolescences on the problem? R= Manufacturing processes and humanmachine interactions. 6 Emmanuel Flores et al. / Procedia Manufacturing 00 (2019) 000-000 What is the existing problem? R= Ageing workforce retiring What is the age range that involves the problem? R= 50+ (mature adulthood)
What is the zone levels involved/affected? R= The workplace and society
What are the self-awareness skills needed to support the mature adults on the problem? R= Positive social outlook and motivation towards labor activity What are the cognitive skills needed to support the mature adults on the problem? R= Learning by reading/listening and decision-making What are the soft skills needed to support the mature adults on the problem? R= Teamwork and flexibility What are the hard skills needed to support the mature adults on the problem? R= Human-machine interactions and digital network interactions
What are the digital skills needed to support the adolescences on the problem? R= Industry 4.0 technologies (3D printing, VR, AR, etc.) The application of the RHAM could find similar examples and practices for other types of challenges or issues that need to be addressed, such as those described in this paper. Equivalently, the approach for the re-consideration of an expected educational program can be evaluated through the inclusion of the RHAM method.
It is not implied that in the two presented examples, the whole answer or solutions to solve the picked problems are given. Rather, it is just a way to show some potential solutions, but most importantly, it is to show the type of analysis for which the RHAM can be used. It is also important recognizing that, due to limiting space, it is difficult to explore other forementioned issues or educational programs as examples.
The developed model interconnects different elements that support the understanding of a human-centric perspective. This approach gives opportunities to provide a common understanding of human requirements for future practical cases, such as educational programs, technological tools, or social/industrial challenges. Some benefits can be pointed as follows:
• It can mediate between the two angles, the existing challenges and the expected educational/training programs. In addition, this work goes in hand with the perspective and framework presented by Shamim et al. [34] . The RHAM fits within such a framework of conditions required to work with change and development for Industry 4.0 from a human management perspective. Within that framework is required to work on peoples' capabilities to bring up innovation, as the first step. Then, it is possible to work on smart and business operations. Consequently, that leads to meeting Industry 4.0 requirements. Finally, the management of learning and knowledge created during such processes takes place. The whole process recycles after that (see Figure 8 ). In this perspective, this paper aims to contribute with an option in developing peoples' capabilities and competences 
Due to existing issues and threats already discussed in previous sections, most educational and training programs need to embrace an open and collaborative content with multiple disciplines involved, not only technical ones. Moreover, most educational programs present a subject or technological-based approach, not a skill-based focus. According to the 2019 World Manufacturing forum report, the industry needs not only technical expertise but generalist know-how in different other domains [35] . That leaves opportunities to look at the development of the workforce from another perspective. Therefore, the presented work aims to support the upskilling of human labor, namely students or employees, amidst the existing wave for future industry, i.e. Industry 4.0.
Reference Human-centric Architecture Model, the proposed architecture aims to become a tool for the visualization of gaps and needs in three aspects for humans: competences, life stages, and environment of the application. In this sense, it may become a mediator between the existing or foreseen challenges and the educational training programs, in a human sense. From this generic model, customization or personalization of the content can be feasible according to the needs and particular cases. Examples of this have been discussed for tackling some of the existing challenges that were identified for the workforce. The model offers the opportunity for the inclusive and holistic development of means or tools to support education and training for human capital from a skilled-based perspective. However, there is still a need for further research for exploring this model, and considering a human-centric approach, that is, the needs of people.
Future research aims at bringing the model to an empirical laboratory application, i.e. software program, which can be carried out as a part of a prototype project for measuring its applicability with consideration of different skills, issues, and educational programs.