Demand analysis of intelligent manufacturing talents based on recruitment data Mining: A case study of enterprises in Fujian Province in China

Recruitment data source

Zhaopin, 51Job, and Boss Zhipin occupy a large share in the Internet recruitment platform, with a high user usage rate and visibility. Therefore, this paper chooses the above three third-party recruitment platforms as the sources of recruitment information collection

Recruitment data collection

Data acquisition can generally be captured through computer programming languages such as Python, or by using data collectors that follow the principle of crawling. This paper uses Houyi data collector to collect recruitment data, searches with keywords such as “intelligent manufacturing” and “intelligent production” on Zhaopin, 51 job and Boss Zhipin platform, and limits the region to Fujian Province in China, and retrieves recruitment information from September 2022 to September 2023. A total of 363 valid data were obtained (including 86 from Zhaopin recruitment, 105 from 51job, and 172 from Boss Zhipin).

Recruitment data preprocessing

First, duplicate data is processed. In order to increase the probability of recruitment information being read, enterprises may repeatedly publish similar or the same job demand information on the same or multiple recruitment websites, resulting in a large number of duplicate data on the recruitment platform. For duplicate data, this paper carries out de-processing based on the same company name and job title.

Second, the collected data is converted into a unified unit and format. In terms of salary range, the unit is uniformly converted into thousands/month. In terms of work experience, the minimum years of work experience given will be taken as the benchmark. The missing data in the field of work experience years will be supplemented by selecting items with “experience” from the job requirements. If all items are not explained, they will be considered as not requiring experience.

Finally, the information with missing data should be sorted out manually from the collected data, and the job requirements of specific companies should be supplemented by searching. The recruitment positions that are missing too much important information are deleted.

City area analysis of recruitment

The statistical results in Table 1 show that the demand for recruitment positions in coastal cities such as Fuzhou, Xiamen, and Quanzhou is relatively large, with a total of 64.74%. The above three cities have developed economies, high level of industrialization and information technology, and a relatively complete intelligent manufacturing supporting industrial chain, and there are more intelligent manufacturing job demands. As the location of intelligent manufacturing model enterprises such as Ningde Times, Ningde has a large demand for related jobs, accounting for 11.29%.

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Table 1.

Distribution of intelligent manufacturing recruitment positions.

Area/quantity	51Job	Zhaopin	Boss Zhipin	Total	Percent
Fuzhou	23	17	44	84	23.14%
Putian	1	2	5	8	2.20%
Xiamen	37	35	33	105	28.93%
Quanzhou	15	10	21	46	12.67%
Zhangzhou	2	9	16	27	7.44%
Longyan	1	3	24	28	7.71%
Sanming	0	2	10	12	3.31%
Nanping	0	2	10	12	3.31%
Ningde	26	6	9	41	11.29%

For intelligent manufacturing positions with recruitment needs, contingency table analysis is carried out on the recruitment platform where the information is located according to different regions. The results show that there are significant differences in the distribution of recruitment information platforms among different regions, as shown in Table 2 and Table 3.

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Table 2.

Region of the enterprise * Platform name cross-tabulation.

		Platform name			Total
		51Job	Zhaopin	Boss Zhipin
Enterprise location	Fuzhou	23	17	44	84
	Longyan	1	3	24	28
	Nanping	0	2	10	12
	Ningde	26	6	9	41
	Putian	1	2	5	8
	Quanzhou	15	10	21	46
	Sanming	0	2	10	12
	Xiamen	37	35	33	105
	Zhangzhou	2	9	16	27
Total		105	86	172	363

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Table 3.

Chi-square test.

	Value	df	Asymp. Sig. (2-sided)
Pearson chi-square	74.544a	16	0.000
Likelihood ratio	82.294	16	0.000
Number of valid cases	363

Recruiting enterprises, intelligent manufacturing positions and their salaries

Intelligent manufacturing involves the integration of a variety of complex systems, including intelligent equipment, industrial software, intelligent manufacturing system solutions and other subdivisions, the corresponding types of intelligent manufacturing jobs are more. Such as intelligent designers, intelligent project managers, intelligent engineers, intelligent technicians, machine vision application engineers, algorithm engineers, intelligent equipment development engineers, product managers (intelligent hardware, Internet of Things communication), digital product development engineers, and intelligent robot application engineers. From the recruitment needs of the three platforms, the top ranked intelligent manufacturing positions are mainly: intelligent project manager, mechanical design engineer, electrical engineer, weak current intelligent project manager, weak current intelligent design engineer, weak current intelligent technician, senior IE engineer, MES implementation consultant, image algorithm engineer, and intelligent technician.

The level of salary reflects the technical level of the position to some extent. The salary level distribution of the above intelligent manufacturing positions is shown in Figure 1, of which 7% are more than 20,000 yuan/month, and the positions in this area are mainly concentrated in the control and execution of industrial application software, simulation applications, data development, and system integration. The company is mainly engaged in software/Internet development, integrated circuits, lithium new energy, and other fields. Overall, the 7500–10,000-yuan range has the highest proportion of related intelligent manufacturing jobs.OPEN IN VIEWER

Educational requirements for intelligent manufacturing positions

Through the analysis of the education fields of intelligent manufacturing positions collected by Zhaopin, 51job, and Boss Zhipin, see Figure 2. After professional training, college and undergraduate graduates have a certain knowledge and practical basis, which can better meet the requirements of the post. Some of the more high-end composite intelligent manufacturing positions require master’s and doctoral degrees.OPEN IN VIEWER

For intelligent manufacturing positions with recruitment needs, contingency table analysis of their educational requirements is carried out according to their recruitment platform. The results show that there are differences in educational requirements among different recruitment platforms, as shown in Table 4 and Table 5.

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Table 4.

Platform name * Education cross-tabulation.

		Educational background						Total
		Undergraduate	Doctor	Junior college	Senior high school	Master	Education is not limited
Platform name	51Job	72	0	33	0	0	0	105
	Zhaopin	60	0	25	0	2	0	87
	Boss Zhipin	55	1	99	2	3	11	171
Total		187	1	157	2	5	11	363

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Table 5.

Chi-square test.

	Value	df	Asymp. Sig. (2-sided)
Pearson chi-square	57.491a	10	0.000
Likelihood ratio	65.177	10	0.000
Number of valid cases	363

Requirements for experience in intelligent manufacturing positions

When companies publish intelligent manufacturing recruitment positions, understanding the work experience of candidates is a very important part of the job. Some of the intelligent manufacturing positions in the above recruitment platform do not mark the requirement of experience, and the work experience requirements of some data in Zhaopin recruitment, 51job, and Boss Zhipin are detailed in Figure 3.OPEN IN VIEWER

Intelligent manufacturing requires industrial Internet, manufacturing, and R & D design industrial software skills, candidates should be able to provide appropriate solutions according to business needs, but also familiar with and maintain a variety of equipment and practical operation, practical operation proficiency needs time accumulation, which requires job seekers to have a certain amount of work experience. As shown in Figure 3, some enterprises require intelligent manufacturing personnel to have more than 5 years of work experience.

For intelligent manufacturing positions with recruitment needs, contingency table analysis is made on their experience requirements according to their recruitment platform. The results show that there are differences in experience requirements among different recruitment platforms, as shown in Table 6 and Table 7.

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Table 6.

Platform name * Experience cross-tabulation.

		Experience					Total
		No experience required	1–2 years	10 years and above	3–5 years	5–9 years
Platform name	51Job	3	24	7	33	38	105
	Zhaopin	26	14	2	20	8	70
	Boss Zhipin	18	58	1	48	21	146
Total		47	96	10	101	67	321

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Table 7.

Chi-square test.

	Value	df	Asymp. Sig. (2-sided)
Pearson chi-square	68.500a	8	0.000
Likelihood ratio	65.292	8	0.000
Number of valid cases	321

Requirements for ability of intelligent manufacturing positions

Intelligent manufacturing positions require “digital technology + manufacturing” composite talents, involving research and development, marketing, production and manufacturing, supply chain and other modules, and have high requirements for the competency of talents. The abilities required for intelligent manufacturing recruitment positions in Zhaopin, 51job, and Boss Zhipin platforms are sorted out. See Table 8 for details, and the top 10 ability requirements are obtained, in order: communication ability, expression ability, learning ability, pressure resistance ability, analysis ability, innovation ability, professional ability, organization and coordination ability, data analysis ability, and management ability. Among them, communication ability, expression ability, learning ability, pressure resistance ability, analysis ability and innovation ability belong to the comprehensive quality, organization and coordination ability, and management ability emphasize management quality. Professional ability and data analysis ability focus on intelligent manufacturing business knowledge, intelligent manufacturing architecture and planning ability, professional technical skills in the application of digital information system tools, data operation and maintenance ability.

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Table 8.

Requirements for working ability of intelligent manufacturing positions recruited by Fujian enterprises on Zhaopin, 51job, and Boss Zhipin platforms.

Ability	Frequency
Communication ability	178
Expression ability	45
Learning ability	21
Pressure resistance ability	15
Analysis ability	11
Innovation ability	7
Professional ability	7
Organization and coordination ability	6
Data analysis capability	4
Management ability	4

Development stage of manufacturing industry

In the era of Internet big data, the technology of all walks of life is experiencing rapid development, and the manufacturing industry is no exception. As the foundation of the country and the foundation of a strong country, China’s manufacturing industry has gradually changed to “China’s intelligent manufacturing.” While the manufacturing industry continues to optimize and improve, it is also promoting the optimization and upgrading of the talent structure, the quality of talents required by enterprises is also gradually changing, intelligent manufacturing needs not simple basic physical labor, but a versatile “T” type of composite talents (especially high-level key talents) who understand both hardware and software. According to the “Manufacturing Talent Development Planning Guide” jointly issued by the Ministry of Education, the Ministry of Human Resources and Social Security, and the Ministry of Industry and Information Technology in China, China has a large talent gap in high-end CNC machine tools, robots and other fields. Whether in the field of CNC machine tools or robots, it is necessary for practitioners to work and study for a long time and focus, master a certain technical ability, understand the basic operation of enterprise machinery and have a certain practical experience in manufacturing enterprises. In the field of strategic emerging industries such as integrated circuits, cloud computing, big data, and robotics, the supply of intelligent talents in Fujian Province is more prominent, and the gap of “strategic” and “leading” talents is large.

Characteristics of the enterprise

From the perspective of enterprise size, the organizational structure of small enterprises is relatively simple, and fewer intelligent manufacturing talents need to be recruited. Medium-sized enterprises have a more complete department system, and need a certain number of intelligent manufacturing talents to meet the needs of enterprise production business. Large enterprises have a very perfect organizational structure and management system, and need to recruit more intelligent manufacturing talents for production and research and development, so as to provide more diversified intelligent products.

Small manufacturing enterprises are small in scale, the production field of enterprises is relatively basic products, and the degree of intelligence is low, such as many mold model production enterprises and electronic components assembly enterprises, the production technology level of enterprises is low, the number of high-tech equipment is small, such enterprises have low requirements for technical experience, and the required staff education and industry experience are not high. Large enterprises represent the research and development direction of the industry, and the products and equipment developed and manufactured have a higher degree of intelligence. The application of intelligent equipment, cloud computing, Internet of things and other technologies in the production process requires a high knowledge reserve and research and development technology experience, so the requirements for recruiting employees of this type of enterprise are relatively high. Taking the new energy unicorn company Ningde Times as an example, whether it is the power battery system or the industry’s advanced lithium battery materials, it is necessary to use advanced 5G network, cloud computing and artificial intelligence technology for research and development and manufacturing, the manufacturing process is relatively complex, and the product quality reaches a high standard, which puts high requirements on the quality of intelligent manufacturing talents.

Conditions of the talent market

According to the prediction of the Ministry of Human Resources and Social Security, by 2025, the demand for talents in the intelligent manufacturing industry will reach 9 million, the gap is 4.5 million, according to the same standard calculation, Fujian Province is expected to have a talent gap of about 250,000, talent shortage and fault problems cannot be ignored. In terms of the demand of the talent market, Fujian Province is short of high-quality talents in the fields of automation, artificial intelligence, software engineering, information engineering, and robot engineering. High-end positions in control and execution industrial application software, simulation applications, data development, and system integration are in great demand. In terms of the supply of the talent market, Fujian Province focuses on intelligent manufacturing of “robot engineering, artificial intelligence, intelligent manufacturing engineering, intelligent instruments and equipment, intelligent science and technology” and other undergraduate, master’s and doctoral majors, and its enrollment accounts for only 11%, 14%, 12% of related majors, talent training is insufficient, the lack of reserves, and the imbalance between market supply and demand is more prominent. In addition, although the employers of intelligent manufacturing related jobs generally have a good working environment, they are affected by the traditional prejudice against the manufacturing industry (manufacturing assembly line work is boring and unchallenging, the working environment is not good, and working in office buildings is more important), some young people, even if their majors meet the requirements of intelligent manufacturing positions, would rather choose live streaming sales, becoming internet celebrity anchors, opening Taobao stores, delivering takeout and express delivery than enter factories. This has led to insufficient talent reserves for team leaders in many intelligent manufacturing enterprises, and the recruitment of technical personnel has been ineffective.

Personal level

In today’s fierce job market, people with relevant expertise and skills are more competitive. From the results of the ability demand analysis, it can be seen that most enterprises have higher requirements for the communication ability, coordination ability, and teamwork of intelligent manufacturing talents.

Students can make full use of campus teaching resources, constantly enrich their own theoretical knowledge system, consult more professional teachers, and master the corresponding professional knowledge according to their own majors such as information technology, industrial equipment, and electrical automation.

The above analysis of the work experience of intelligent manufacturing demand positions shows that for intelligent manufacturing positions, enterprises prefer talents with rich work experience. Therefore, on the basis of consolidating professional theories, students should combine theory with practice, actively form a team with classmates, take the initiative to participate in internships, and participate in industrial practice activities in pairs. In the internship training of enterprises, students should improve their comprehensive quality, improve their problem thinking ability and teamwork ability, and cultivate their “craftsman spirit” and practical skills. Strive for technological excellence in the actual operation process. Only through a lot of practical work can we improve the practical problem solving ability. Internships can provide students with valuable practical opportunities and a better understanding of the business processes of related industries and companies. In the selection of internship practice time, current students should take into account both the winter and summer vacations, graduation, and other time periods, as well as the time points of professional cognition internship, course and professional practice, comprehensive assessment of professional basic skills, and comprehensive practice of the academic year. Long term and short-term should be combined, and wide range and profound fields should be combined. In the process of practice, students must pay attention to fully integrating the practical content with the theoretical knowledge they have learned, and approach it with questions in mind.

The employed intelligent manufacturing staff should actively participate in all kinds of skills training organized by the enterprise, and learn the current hot new technologies, new software and new methods in the manufacturing industry through a combination of online and offline methods, such as artificial intelligence, industrial Internet of Things, industrial robots, digital twins, additive manufacturing, and other digital manufacturing technologies. Apply these latest cutting-edge technologies to their actual work, meet the constantly updated career development needs, improve digital production skills and quality management capabilities, and become “high-quality talents” and “innovative talents.” Intelligent manufacturing involves multiple directions, such as production, manufacturing, and research and development, and these different work directions have different requirements for talents and work content. Therefore, on-the-job practitioners need to clarify their strengths, interests, and future development prospects of positions in related fields in actual work, so as to formulate clear career goals and plans, and progress toward intelligent manufacturing that suits them.

University level

As the main channel of conveying talents to manufacturing enterprises, colleges, and universities bear the key responsibility of cultivating and incubating manufacturing talents. After mechanization and automation upgrade, now the manufacturing industry is moving toward the digital and intelligent era, colleges and universities should keep pace with the times, fully communicate with industry enterprises, according to the requirements of the industrial chain and innovation chain, combined with the actual production of first-line, optimize the setting of professional disciplines and training programs to meet the requirements of the transformation and upgrading of the manufacturing industry in Fujian Province.

The analysis results of Fujian Province enterprises’ “job requirements” for intelligent manufacturing positions on the above three recruitment platforms show that different manufacturing enterprises have different requirements for job seekers’ knowledge reserve. For example, some companies prefer research and development business, and more emphasis on intelligent manufacturing personnel need to have electronic information, computer science, and other professional knowledge. Some companies prefer production business, more need intelligent manufacturing personnel with mechanical or automation knowledge and practical ability. Therefore, on the basis of the existing core courses of intelligent manufacturing related majors, colleges and universities, according to the needs and trends of the industry, should enrich professional elective courses in different fields for digitalization and systematization, such as electronic information and production line automation, to expand students’ interdisciplinary knowledge and cultivate comprehensive and composite intelligent manufacturing talents with innovative ability.

The analysis results of Fujian enterprises’ “work experience” of intelligent manufacturing positions on the three major recruitment platforms above show that work experience is one of the important factors. Therefore, in the teaching process, it is very important to improve the practical level and enrich the internship experience of students majoring in intelligent manufacturing. Schools can add more opportunities for business practice related to smart manufacturing career skills. Improve students’ working awareness and practical ability through the combination of production and study. Guide students to obtain intelligent manufacturing professional qualification certificates such as senior CNC milling worker, senior CNC turning worker, senior assembly fitter, information engineer, maintenance electrician, industrial robot operation, industrial Internet implementation, and network engineer. Integrate the training content of vocational qualification certificate into the content of intelligent manufacturing professional courses, realize the synchronization of professional course examination and vocational qualification certificate preparation, comprehensively master theoretical knowledge and practical skills, and organically combine academic education and vocational education to create a team of undergraduate preparatory technicians who meet the needs of enterprises and have high practical ability.

Actively guide students to participate in various industry competitions sponsored by intelligent manufacturing related industry associations and benchmarking enterprises, so that students can apply their knowledge in practice and improve the level of intelligent manufacturing skills. The school can also invite professionals in the intelligent manufacturing industry to conduct special training, share practical cases and their own career experience, and help students better understand and master intelligent manufacturing skills to adapt to industry changes.

Strengthening the construction of teachers is also a top priority, and colleges and universities should focus on the improvement of teachers’ practical level. The manufacturing industry has very high requirements for practical work ability, and when colleges and universities recruit intelligent manufacturing teachers, they should give priority to dual-professional talents with rich practical experience and solid professional foundation. After professional teachers enter the profession, they should be arranged to enter the corresponding manufacturing enterprise practice, and provide them with more opportunities to participate in enterprise practice and school-enterprise exchanges.

Enterprise level

Manufacturing enterprises can fully communicate with universities, deeply participate in all aspects of application-oriented intelligent manufacturing talent training, and establish a training mechanism for the integration of production and education, so that enterprises can play an important role in the orientation of talent training types, training program formulation, practical course setting and arrangement, and teaching evaluation.

The same type of manufacturing enterprises should establish industry associations, jointly organize the professional ability training of employees in the industry, provide a variety of intelligent manufacturing technology training courses, so that employees can keep up with the pace of intelligent manufacturing era, improve work skills, and improve work efficiency. With the theme of “the spirit of engineers and craftsmen,” various scientific and technological cultural activities should be organized in the industry association, and high-end manufacturing talents in the association should be invited to share their work experience, spread the spirit of craftsmen, and cultivate the enthusiasm of employees. It can be considered to set up an intelligent manufacturing Internet sharing platform, and the leading enterprises of intelligent manufacturing will take the lead in formulating industry standards, which will be shared on the platform and promoted to other related enterprises.

In order to attract and retain excellent intelligent manufacturing talents, Fujian Province should take technical personnel service work as a breakthrough point, conduct in-depth investigations into the actual needs of talents, and comprehensively grasp the difficulties and challenges faced by skilled talents. Taking this as a starting point, we will continue to build an innovative talent development platform and create a good growth environment.

Enterprises should combine their own characteristics, combined with the characteristics of the industry, choose the right way to attract talents. For example, small businesses with lower wage levels can focus on providing living security such as education and healthcare to address the concerns of their employees. Through flexible work arrangements, offer options such as remote work and flexible working hours to meet the needs and lifestyles of different employees. Use flatter management structures and faster decision-making processes to meet the needs of employees. Large enterprises should provide incentive stock incentives or profit sharing plans to make employees feel that they are a part of the company’s success and can benefit from its growth. Enterprises should clearly demonstrate to employees the pathways for their growth and promotion within the company, provide training and learning resources, and support their career development.

Social dimension

In the past, the manufacturing industry has long been dominated by low-end production, so it has been labeled with special labels such as poor working environment and low social status, and the existence of these “biases” makes the manufacturing industry less attractive than the Internet, finance and other industries. Therefore, in terms of social dimensions, it is necessary to strengthen public opinion propaganda, produce promotional videos and graphic materials, and showcase high-tech and innovative achievements in the manufacturing industry. Guide the public to recognize the importance of manufacturing to social development through social media, television advertisements, and public lectures. Organize open day activities in primary and secondary schools, universities, and residential areas, inviting the public to visit factories and learn about production processes.

Therefore, at the social level, we should take the “Fourteenth Five-Year Plan” intelligent manufacturing development plan as the overall guidance, build a high-quality intelligent manufacturing talent team with high standards, and improve the all-round talent training system to support the intelligent manufacturing development plan. Vigorously promote the development prospects and potential of intelligent manufacturing, guide job seekers to choose the development of intelligent manufacturing, and effectively enhance practitioners’ sense of achievement, sense of belonging and happiness.

Specific can be started from the following aspects. Manufacturing talents should adhere to the combination of technical level and wage grade, and implement the scientific salary of professional skills; According to the actual situation of enterprises, scientifically set the proportion of skill wages in the salary system of intelligent manufacturing positions. Through the construction of reasonable salary increase mechanism, the scientific salary grade planning is carried out for talents of different levels. For “high-end intelligent manufacturing talents,” enterprises should provide competitive and attractive salary treatment, and the government should provide corresponding salary and skill subsidies, achieve “enterprise to give a little, the government to make up a little,” play the policy dividend, and support more manufacturing enterprises to introduce high-quality talents.

Second, improve the personnel training system, establish a more complete policy system for the work of skilled personnel, guide them to participate in vocational skills training, and give vocational skills training subsidies according to the skill level obtained. For employees involved in key positions of intelligent manufacturing such as high-end machinery and equipment, intelligent manufacturing production lines, intelligent logistics, and CNC factories, the government can formulate special support policies, grant employment subsidies to enterprises. The amount of subsidies is issued according to a certain proportion of the salary paid by enterprises before tax, and a subsidy limit is set. The subsidy is linked to the employee’s employment year to enhance the stability of the enterprise’s technical personnel.

Third, national exchanges and cooperation in the field of intelligent manufacturing strategy are of great significance. We should actively introduce foreign advanced intelligent manufacturing technology, effectively learn, utilize and optimize innovation, give full play to both domestic and international markets, broaden the international vision of intelligent manufacturing talents, and promote the leapfrog development of intelligent manufacturing technology.