3.1. Frameworks of Employee Skills and Competencies in Industry 4.0
The range of competencies and skills frameworks built by researchers and scientists is aligned with their adopted research scope and research objectives. In the Acatech [
55] study (a study for the Industrie 4.0 platform), the skill profile of a next-generation technology-enabled worker is the focus in terms of the characteristics of learning the usability of Industry 4.0 technologies and the functions and possibilities of integrating digital and physical solutions in smart manufacturing, as well as understanding business networking. The set of proposed characteristics of an Industry 4.0 worker is closed by the social and environmental requirements to which the worker must constantly adapt, being aware of the changes taking place and the potential for technology to affect changes in the workplace and beyond (
Table 1).
In a scientific study by Ann et al. [
56], a team of researchers proposed a skill profile for the Industry 4.0 worker based on IT and mechatronics knowledge and a pledge of skills useful in handling new technology in programming, use of IoT, use of data, understating of process and the function of new technologies. The authors also stressed that employees of Industry 4.0 should have a positive attitude towards working in the smart manufacturing environments created by companies, i.e., “have an optimistic spirit”. Employers recruiting employees expect, apart from basic technical knowledge and digital skills, as well as experience in operating given installations and IT systems (for at least 2 years) and expertise in advanced knowledge, in particular, in the field of building smart manufacturing in enterprises (
Table 1).
Darwish and van Dyk [
57] are the authors of the industrial engineering model (original components of the model prepared by Darwish and van Dyk (2016) were presented in
Table 1). On the basis of this model, for the purpose of this publication, key segments of the competency profile of a 4.0 employee were distinguished. The segment of basic technical knowledge of employees in the area of cooperation with Industry 4.0 technologies was extended by management knowledge according to operational processes and technological installations at the particular levels of management in an organization. For an employee to participate in knowledge management, he or she should have conceptual skills, thinking, and perception connected with levels of digital business. Another segment of the competency profile is formed by human wellbeing and awareness according to the level of industrial development.
In the created environment of smart production, the employee must constantly adapt to new situations in the organisation and its smart environment. In addition to hard skills, the model of Darwish and van Dyk [
57] also includes social skills and behaviors, and human attitudes to industrial engineering. According to the model, the authors of the paper proposed three segments of employee skills: (i) technical skills in terms of the ability to operate enabling technologies of Industry 4.0; (ii) social and conceptual skills (iii) human attitudes and behaviors suitable for going on technological changes.
The three skill fields were also proposed in reference [
58]. According to reference [
59], a skill profile is composed of: (i) digital skills in the fields of Industry 4.0 programming and software engineering, data science, data and big data analytics, visualization, Internet of Things, IT architecture, and cybersecurity; (ii) project coordination skills such as product management, multi-project management, supply chain, and support services, logistics, (iii) soft skills including creativity, design, innovation, leadership (the full list is presented in
Table 1).
In Deloitte’s study [
60] four fields of the Industry 4.0 employee profile were presented, including: (i) workforce readiness, e.g., self-presentation, time management, (ii) soft skills including communication, critical thinking, creative thinking, collaboration, adaptability, initiative, leadership, social-emotional learning, teamwork, self-confidence, empathy, growth mindset, cultural awareness; (iii) technical skills, e.g., computer programming, coding, project management, financial management, mechanical functions, scientific tasks, technology-based skills, and other job-specific skills; (iv) entrepreneurship: initiative, innovation, creativity, industriousness, resourcefulness, resilience, ingenuity, curiosity, optimism, risk-taking, courage, business acumen, business execution (
Table 1).
According to [
61], the required skills for industrial employees in the Industry 4.0 environment are: the ability to solve problems, technical skills, analytic capacity, ability to use IT systems, lifelong learning, communication, ability to work in a team, worker openness to change, technical and management skills, openness to automatization, and openness to digitalization. Skills required for managerial staff in an Industry 4.0 environment are: social media skills, lifelong learning, ability to work in a team, the connection between technical and management skills, openness to change, openness to digitalization, involvement, striving for continuous improvement, creativity, creative thinking, self-discipline, self-management and openness to automation, (
Table 1). There is more and more a demand for production engineers who combine managerial knowledge with technical knowledge both in the small and medium-sized enterprises.
Cotet et al. [
62] realized the research of students’ specializations: Machine-tools, Robotics, Logistics. Researchers have built a profile of the skills of future employees of Industry 4.0. According to Cotet et al. (2017), the characteristics of students are creativity, independence, sophistication, intellectual curiosity, self-discipline, spirit of excellence, perseverance, empathy, empowerment, respect, personal affirmation, interpersonal skills (
Table 1).
In his white paper, Roland Berger [
63] (2016, p. 35) states there is a division of qualifications and skills into “more focus” and “less focus”. The segment of important qualifications and skills for Industry 4.0 was formed by the sub-segments of (i) ICT knowledge (the main knowledge about the usage of information technology, the possibility to interact and use computers and intelligent solutions such as: tablets, robots, etc., understanding the communication system—machine-to-machine, the usage of IT security solutions and careful data protection); (ii) data literacy (ability to analyse and process information and data obtained from technology, understanding of the implementation of visual output and decision-making systems, the usage of basic statistical knowledge). The “lesser” pole includes a sub-segment of technical knowledge, e.g., interdisciplinary and general knowledge of technology, specialised knowledge of production activities and processes, technical knowledge of machines to perform maintenance activities, and a sub-segment of personal skills, e.g., adaptability and capacity for change, decision-making, teamwork, communication skills, changing attitudes towards lifelong learning (
Table 1).
The World Economic Forum, based on the O*NET Content Model “Future of Jobs Survey” [
64], presented the following skills of Industry 4.0 workers: (i) cognitive analytics, (ii) physical skills, e.g., physical strength, manual dexterity, manual precision (iii) basic skills in two areas: “substantive skills” and “process skills”, (iv) cross-functional skills. The list in the last segment is the longest and consists of systems skills, complex problem-solving skills, technical skills, resource management skills, and social skills (
Table 1).
Reference [
65] pointed out that workers need specific knowledge and a new skill paradigm because the number of jobs with high levels of complexity is increasing significantly. The demand for new skills stems from (1) the increasing need for complex information integration and transparency; (2) the increasing automation and digitalization of production systems, (3) self-management and decision-making by objects (plants and machines), (4) digital communication and the popularization of mobile devices (5) interactive management functions and integration of computer and information systems (ICS), (6) personnel flexibility and multi-site and multi-tasking.
Some of the most important skills that should be needed to implement the Industry 4.0 conception include: computational thinking, (the ability to use the vast amounts of data into useful concepts to understand data-based solutions), technical and digital skills are needed in organization to implement real and virtual collaboration (the ability to collaborate in effective way with new technologies); cognitive load management (the ability to use and filter information according to its importance and this can lead to maximised cognitive functions); adaptive thinking (demonstrating the implementation of thinking and finding new solutions, which leads to the ability to determine the deeper sense of technological functions); design mindset (the ability to develop tasks then focus on the work processes that lead to achieving the desired results); and social intelligence (the possibility to convey new innovative concepts to others people, deeply and directly, and thus stimulates reactions) [
66].
In the ongoing revolutions, third and fourth, workers should think industrially, i.e., focus on understanding changes in manufacturing technologies and business processes [
67]. Industrial thinking is based on an active work attitude, active machine, and technological cooperation, complex problem solving, coordination with others (teamwork), creativity, critical thinking, judgment and decision-making, project management, self-management, negotiation, and people management. In Industry 4.0, the selections of industrial thinking should be supported by technical skills related to digital, e.g., programming languages, common operating systems, software proficiency, technical writing, data analysis.
The presented list is not exhaustive. Researchers are constantly adding to the skills and qualifications profile of the Industry 4.0 workforce. Companies that transform to Industry 4.0 still need their employees to have specific new skills and knowledge. Comparing the list of employee skills and competencies (
Table 1), it was found that authors [
55,
56,
57,
58,
59,
60,
63,
64] point to knowledge of Industry 4.0 technologies as a key competency area. Worker knowledge of applied industrial solutions builds their digital skills over time, which are related to operating cyber-physical production systems.
According to reference [
61], the digitality of employees is defined by openness to novelty and the acquisition of skills to work with new technologies. Reference [
62] analyzes the characteristics of students who, in time, will become employees of companies transposing to Industry 4.0. The characteristics that allow students to adapt to the new smart environment are exposed. In addition to the key skills segment, referred to as digital or technical, another segment is the social and teamwork segment. In references [
55,
58,
59,
61,
63,
64], communication and collaboration are discussed. In Industry 4.0, technology operators exchange knowledge about new solutions and thus become more familiar with the possibilities of new technologies. The third segment is personal skills, where creativity, critical thinking, inquisitiveness, etc. are important characteristics. The three segments of skills and competencies can be considered as the architecture of the Industry 4.0 employee profile. The development of employee skills focuses on digitalization. This digitalization should lead to the improved performance of industrial production systems, the efficiency of manufacturing and supporting processes, and the effectiveness of operative management [
68,
69]. Highly qualified staff should possess an openness to change, a strong ability to transfer knowledge and teamwork, and the ability to self-manage [
70,
71,
72,
73].
The responsibility for providing the right workforce for Industry 4.0 rests with education and policy. Nowadays, policymakers and educators can play a key role in organizations, especially in preventing the obsolescence of competence. They should be responsible for knowledge and skill development, and continuously updating all aspects required by the current and future labour market [
74]. In the fourth industrial revolution, the demand for computer scientists and digital operations technologists is growing rapidly [
65]. Companies need computer scientists, PLC programmers, robot programmers, software engineers, data analysts, cyber security electronics technicians, automation technicians, manufacturing technicians with digital skills, and production engineers to build smart manufacturing. Modern education courses should include subjects in: big data analytics, data science, advanced simulation, data communication, virtual plant modeling, novel human-machine interfaces, networks and system automation, real-time inventory, digital-to-physical transfer technologies (e.g., 3D printing), process quality control, and closed-loop integrated product logistics optimization systems and management systems [
75,
76]. Reference [
61] showed that the greatest demand was for mechatronics and electromechanics (78%) and data analysts and cyber security experts (75%) in the segment of SME under study. Furthermore, there was high demand for logisticians, process engineers, information and communication technology engineers, and machine operators. Generally, employees with technical skills are needed. According to Saniuk et al. (2021) technical skills are the most desirable (91% of respondents). Otherwise, the ability to solve problems (82%), ability to use IT systems (76%), analytic capacity (74%) and communications (72%) are also expected. Moreover, Saniuk noted that respondents also highlighted the need for lifelong learning (71%) [
61].
3.2. Frameworks for Skills and Capabilities of Operator 4.0
Another area of research was the competency requirements of Operator 4.0 (O4.0). Quoting from Romero et al., O4.0 as “a smart and skilled operator who performs not only cooperative work with robots but also “work aided” by machines if and as needed” [
12,
77]. Romero et al. in 2016 presented the first and in-depth analysis of the new concept of ‘Operator 4.0’, exploring a set of key enabling technologies that can support them. The researchers identified eight typologies of operators: (1) super-strength operator; (2) augmented operator; (3) virtual operator; (4) healthy operator; (5) smarter operator; (6) collaborative operator; (7) social operator; and (8) analytical operator [
77]. In terms of the Compass Capabilities of Operator 4.0, four directions of capabilities are proposed: (i) cognitive capabilities, (ii) sensorial capabilities, (iii) physical capabilities, (iv) interaction capabilities [
78]. Particular capabilities are assigned technologies with which O4.0 works. In terms of cognitive capabilities, these technologies are: cloud computing, simulation, virtual reality, and artificial intelligence. Technologies that can enhance the worker’s sensorial capabilities are: personal activity trackers, health monitoring sensors, Internet of Things (IoT), posture sensors, and other sensors. When an operator uses their physical capabilities in the workplace, they can work with exoskeletons, collaborative robots, control devices, actuators and teleoperated systems. Interaction capabilities are needed in cooperative work with human-machine interfaces, augmented reality, mobile devices, and intelligent personal assistants.
In this publication, there is a proposition as to how to develop final projects in engineering science. Those projects can be used as a form of learning. They can contain the following main skills and scope of knowledge: supervision, advanced automation, robotics, and industrial network communications, including: sensors system integration, computer simulations and modelling of processes, actuators, programming, etc. Di Pasquale et al. [
79], also based on the classification developed by Romero and team (2016) [
67] analysed the influence of new technologies on operators’ work. With the increasing interest of companies in implementing the enabling technologies of I4.0 in maintenance activities, O4.0 needs to continuously develop its skills. Tartora et al. [
80] performed a complete literature review in the field of research: Maintenance in I4.0. The authors identified several research topics, and one of them (Topic 3) was: Measuring and Improving Maintenance Operator Performance. In this topic, the authors highlighted maintenance training by using VR in the development of machine operator skills. Industrial training with VR technology is a key form of machine operator skills in the digital factory. The usage of VR can be used for the creation of a useful environment through the use of appropriate computer technology. This usage can lead to the development of the condition in the case of an interactive 3D world. In this environment, objects have a sense of deep spatial presence [
81]. The usage of the new training method leads to the situation in which the operator can interact with its prospective work object. This interaction can be done even without the direct presence of the training object. This usage can give the organization the chance to train workers at any desired place. Maintenance and industrial training by the broad usage of VR technology leads to the development of motor skills and cognitive skills for performing a task. In the same publication, Augmented Reality (AR) technology is used in the development of human maintenance operations through a mobile or wearable device to plan and perform maintenance tasks. The work by using enabling technologies is easier efficiently and in an easier way, increasing the productivity of the system. Through simple instructions, the work is easier to understand also for an unskilled operator [
82]. This does not mean that in smart factories, unskilled operators will be employed but that enabling technologies of I4.0 will safeguard the process against human error. In modern factories, job rotation of operators is possible (within a given group of I4.0 technologies). Full knowledge of the control principles of the technologies of a given class is required for job-switching. Position crossing, which consists in moving employees on positions forming a production line or a production nest layout, is possible within a given group of I4.0 technologies. Crossing used to be, in a nutshell, “a quick tour of the organization” or, more modernly, “cross-training” [
83]. Nowadays, I4.0 technology crossing is a component of knowledge management and skills development programmes for 4.0 operators. Technology crossing helps employees to better understand the I4.0 process technologies used in a given company. Crossing consists of the employee mastering to a satisfactory degree the performance of operations at all or selected positions of the production cycle, both preceding a given (actual) workstation and positions occurring after it [
84]. The wide spectrum of support for the 4.0 operator from I4.0 technologies and information and communication systems builds its technological and IT multidisciplinarity [
85].
Many technological solutions are applied in smart manufacturing, so I4.0 Operators can be teachers of machines equipped with AI algorithms, mentors of digital solutions, leaders of smart manufacturing projects, technology controllers, robot assistants, information systems programmers, machine learning programmers, managers for mobile robots, cyber-physical systems analysts, machine-to-machine liaisons, artificial intelligence operators, CAD operators, wireless computer network operators, computer application operators, etc. As I4.0 technology develops, operators will perform more and more new functions. Knowledge of enabling technologies of I4.0 and successively acquired knowledge of technological operations management will be useful in this assumption of functions. New technologies have made it possible for operators to access, store and process large amounts of data collected from different complementary sources, both internally and externally, to processes [
86].
Industry 4.0 is building demand for many fourth-generation industrial technology operators. Rupper et al. (2018) [
52] based on Romero et al. [
77], performed a full analysis of the technological cooperation of Operator 4. 0 and identified the following types of operators: analytical operator (works in big data environment), augmented operator (works in AR), collaborative operator (responsible for connectivity, collaboration of technologies), healthy operator (measurement of physiological parameters), smarter operator (Chatbot and AI provide support to operators), social operator (is responsible for Facebook and Social Manufacturing (SocialM), super-strength operator (navigation, safety, etc.), virtual operator (works in HR field). Each of these types of operators must have competencies and skills appropriate to the technological field [
87,
88]. Gehrke [
89] lists three levels for building human–intelligent technology collaborations. The first basic layer is formed by the human-operated technologies together with the organisation and working conditions, as well as forms of cooperation inside and outside the enterprise. The second layer is determined by the tasks to be performed by employees in collaboration with the technology. The third layer is the requirements set for employees to operate a given class (group) of devices in the form of a set of necessary skills and position qualifications.
Operators 4.0 should work in groups (teams) with autonomy to act and space to use talent, creativity, and initiatives in the context of technological innovation. The basic determinant of O4.0 work should be a strong focus on innovation and analytical and conceptual work. The authors of Reference [
90] proposed the estimate of operator skills in such categories: basic knowledge, aircraft maintenance workload, other workloads, self-development, problem-solving skill, problem-solving attitude, responsibility, teamwork, work quality, reliability, and attendance rate. Innovation skills include creativity and initiative. Stimulating creativity through the use of creative techniques can help to achieve these competencies. Creative techniques can be a valuable tool to improve operator team performance.
In the smart environment being created, there are many teams of operators within each main category: machine operators, maintenance operators, production operators, process operators. Operators in the smart environment work in teams and communicate using mobile devices. Operators are equipped with mobile devices integrated with machine communication capabilities and computerised data analysis systems. Communication between employees and operational teams takes place remotely. The online form of communication, compared to face-to-face communication, complements and improves the collaboration of machine operators [
91]. Many decisions rest on small teams of operators led by highly qualified engineers (operations team leaders). Control teams are located in control rooms or decision-making centres where many process operations are coordinated. Leading operator teams should be characterised by technological expertise with knowledge of such areas as additive manufacturing, 3D modelling, data analysis, computer programming and machine learning [
92].
In the development of operators’ competencies and skills in companies transforming to Industry 4.0, a holistic approach should be adopted, i.e., a systemic approach with a servant leadership style, inspirational, coaching [
93,
94]. The leader, e.g., of teams of operators of a given technology or the leader of a given smart manufacturing project, is an authority for the other team members. Strategic thinking, change management, teamwork, and networking are key characteristics of leaders [
95,
96,
97,
98,
99]. Team leaders of smart manufacturing operators should be authentic, i.e., have advanced knowledge of working with new technologies of Industry 4.0 [
100,
101,
102].
In operator relationships with Industry 4.0 technologies, trust is gradually built between team members, and the exchange of knowledge and experience gained from working with advanced technological installations and information systems grows [
103,
104,
105]. Operators of new technologies must break down any barriers that may arise when using new technologies. The whole process of holistic learning in the cyber-physical systems being created is designed to comprehensively develop operators’ skills at every level of operating new technologies and prepare operators to think independently, as well as to overcome possible adversities (problems) [
106]. On the one hand, automation facilitates operators’ work; on the other hand, it requires them to continuously learn how to co-operate with I4.0 technologies [
107]. In Industry 4.0, human–machine integration is stronger than up to now [
107]. Operators of I4.0 technologies are increasingly taking on independent managerial roles for smart production, operation of information and communication systems, data processing, and others [
88,
105]. On the operational level of production and technology, Industry 4.0 is blurring the distinction between technical and managerial positions through new technology functions, e.g., hazard prediction, selection of optimal operating parameters by the machine.
Operators are subjected to tests to assess their psychophysical characteristics before working with a given technology. The results of the tests provide an answer to the question of a person’s ability to cooperate with increasingly intelligent machines and devices. Smart manufacturing technology operators are required to have perceptiveness and accuracy in action, analytical skills, the ability to assess the situation in relation to the problem, divisibility and concentration of attention, responsibility, good eye-hand coordination, having and developing technical interests, and above all, readiness to work in a smart work environment and smart space [
106,
107,
108,
109]. Operators have to move in the area of many knowledge fields—knowledge-related fields—such as computer science, automation, electrical engineering, electronics, mechanics, robotics, optics and photonics, sensorics and engineering, e.g., quality engineering, information technology engineering, precision engineering, and automation and robotics, as well as management and decision-making techniques [
16,
110]. This means that operators must continuously improve their skills [
110,
111]. The list of competencies and skills of O4.0 is open, although key components of the profile can be identified (
Table 2).
3.3. Frameworks for Skills of Employee in Steel Industry on the Way to I4.0
In the fourth industrial revolution, modular and multi-profile competencies of steel industry employees are needed. The steel industry is transforming from level 3.0 to 4.0 by realising an increasing scope of digitalisation and implementing Industry 4.0 technologies [
112,
113,
114]. The profile of a metallurgical technology operator should be specialised and, at the same time, flexible in order to be able to freely operate a given technological installation. According to the document of the European Commission [
92], the shaped skills concept for a steel industry worker takes the shape of the letter “T”. The arrangement of “T” competencies includes: technical skills (base of the letter “T”, digital and soft skills (arms of the letter “T”). A metallurgical engineer must be familiar with new technical and technological solutions taking into account computerisation of processes, automation and robotisation of activities. The adopted concept of the letter “T” for the competencies of a steelworker refers to people with specialised skills in one specific area and general skills in other areas. The European Commission has engaged in a number of initiatives to bridge the gap between the needs of Industry 4.0 and the availability of a skilled workforce. The European Steel Skills Agenda (abbreviation: ESSA), which was launched in January 2019, proposes a competency profile for the Industry 4.0 worker. Part of the programme is a market study of the steel industry workforce. The participants of the research were from seven countries: Finland, France, Germany, Italy, the Netherlands, Poland, and Spain. On the basis of interviews with experts, scientists, steel mill workers, and social organisations, a new profile of the steel industry worker was developed. The research analysed current and future workforce skills needs. The research resulted in the pilot development of modules and tools to build awareness and implementation of new workforce skills for a globally competitive steel industry—more information about the project is at:
https://www.estep.eu/essa/essa-project/ (accessed on 15 February 2022) [
115].
The competencies of a metallurgist are built up by individual areas of specialisation within metallurgical skills, which can be grouped as follows: (i) a package of basic knowledge in metallurgy, physics, chemistry, mechanics and other scientific disciplines related to metallurgy; (ii) information and computer technology skills, computer programming, use of open data and data analysis (iii) understanding of statistical coefficients, statistical models, statistical prediction, (iv) collaboration with technologies I 4. 0, which are increasingly equipped with artificial intelligence (AI) algorithms, (v) cognitive skills, such as: critical thinking, creativity, logical reasoning, inquiry, knowledge compilation, problem recognition, problem solving and decision-making, (vi) social skills, such as: interpersonal communication, teamwork skills, leadership and employee management, effective teamwork, emotional intelligence, entrepreneurship and others, (vii) knowledge of cyber security procedures for in-service systems and digital industrial technologies.
Steel industry workers should be able to adapt to changing technological and process conditions in the ongoing fourth revolution. Employees of steel mills, apart from general knowledge of metallurgy, material science, physics, chemistry, and other related fields, are required to know the technologies supporting steel production, such as: mechatronics, metrology, computer science, electrical engineering, micro- and nanoelectronics, nanotechnology, industrial biotechnology, photonics. Basic knowledge shall include: steel melting techniques, steel melting temperatures, steel enrichment processes, deoxidation and desulphurisation processes, hydrogen and nitrogen removal processes, decarbonisation, etc. The knowledge package of a steelworker is referred to as STEM, i.e., Science, Technology, Engineering, and Mathematics [
116].
A very important skill of a modern engineer in the conditions of Industry 4.0 is creativity. This trait is necessary for the engineer to create new and innovative solutions. Creativity is a creative attitude; innovative, a mental process involving the generation of new ideas, concepts or new associations, connections to existing ideas and concepts. Creative thinking is thinking that leads to original and innovative solutions. An alternative, more everyday definition of creativity states that it is simply the ability to create something new [
109,
117,
118]. Creativity consists of many subskills such as making connections, making observations, asking questions, experimenting, and networking [
119,
120,
121,
122]. On the basis of the European ESSA document [
115], a list of key competencies and skills of a steelworker was prepared, which is presented in the form of
Table 3.
The list is not exhaustive and closed because the rapidly changing environment requires steelworkers to have dynamic competencies with characteristics that enable them to adapt to change. The term dynamic competency was used in 1997 by D.J. Teece et al. [
123] and denotes an employee who is able to comfortably navigate through multiple tasks, respond to problems and implement change. The hallmarks of a dynamic competency are [
124] the ability to understand the environment (‘sense’) and the ability to seize opportunities (‘seize’). To meet the demands of rapidly evolving industrial technologies, metallurgical companies recruit engineers in many specialties, ranging from metallurgical engineers to high technology engineers. In addition to traditional metallurgical occupations such as metallurgist, welder, locksmith, electrician, mechanic, steel industry employers demand: programmers, IT specialists, designers, analysts, mechatronic engineers, laboratory technicians, machine operators, production operators, IC system operators, etc. At higher levels of specialisation, the most sought-after digital skills include 3D design, computer modelling, machine learning, computer simulation, data analytics [
11,
12,
52,
77].
Table 4 summarises the occupational skills of the steel industry workforce, divided into focused technical manufacturing competencies and digital competencies. The technological solutions used increasingly rely on synergies between the different competencies of individual workers and teams of operators and IT specialists [
125].
Workers’ knowledge of cyber-physical production systems can be named “digital knowledge”, and we can also think about competencies in this area as a conception of “digital competencies” [
69]. The analysis of this knowledge can include the following areas: assembly, production, logistics, quality management, as also auxiliary areas, which can include, for example: production planning, production preparation, and production maintenance. Therefore, we can observe a growing demand in the industry for engineers who have the ability to combine information technology with automation robotics in new technology conception like mechatronics. It can be observed that engineers are preferred in organizations implementing Industry 4.0 due to the high importance of production and the high importance of securing its development technically. According to this, an engineer 4.0 (Industry 4.0 engineer) can be named as someone who moves without a problem at the interface between two conceptions: cyber and physical. Furthermore, engineers 4.0 should combine the knowledge of a specific manufacturing process in the industry, such as tuning a machine and working with robots. In addition, it is useful to have high IT skills ranging from the basic level (e.g., using operating interfaces and spreadsheets) to the advanced level (e.g., advanced analysis and programming skills) [
85,
87,
109].
In particular, it is highly beneficial for organisations to combine digital knowledge with employee creativity. Creativity is going beyond what is known, common, and obvious; breaking down or reorganizing one’s thoughts on a topic, undertaken to gain new and deeper insights into its nature; “escaping from stagnant thinking”; a way of thinking that involves finding particular relationships between elements and combining them in unprecedented ways resulting in breaking down a learned pattern of thinking and using the knowledge held to generate new ideas. An employee who is creative can create new solutions in terms of the processes they are involved in or the IT solutions they use [
126,
127]. He/she will be able to improve production processes in an innovative way, e.g., in terms of using new technologies, digitalization of processes, robotics, etc.