Defining SMEs’ 4.0 Readiness Indicators
Abstract
:1. Introduction
2. Research Background
2.1. The Industry 4.0 Readiness Aspects and Indicators
2.2. The Methodology for Aspects Identification
3. Research Design and Methodology
3.1. Step 1—Defining SMEs 4.0 Readiness Aspects
3.2. Step 2—Data Analysis and Reliability Test
3.3. Step 3—The Synthesis of SMEs 4.0 Readiness Indicators
4. Defining SMEs 4.0 Readiness Aspects
4.1. Data Collection
4.2. Industry 4.0 Aspects Identifications by Bibliometric Analysis
5. Data Analysis and Reliability Test
5.1. Industry 4.0 Diemension and Aspects Corelation
5.1.1. Organizational Resilience
5.1.2. Infrastructure System
5.1.3. Manufacturing Systems
5.1.4. Data Transformation
5.1.5. Digital Technology
5.2. Industry 4.0 Dimension Reliability Test
6. The Synthesis of SMEs 4.0 Readiness Indicators
6.1. Organizational Resilience
6.2. Infrastructure System
6.3. Manufacturing System
6.4. Data Transformation
6.5. Digital Technology
7. Application of an Example Case Study
7.1. Indicators Scoring
7.2. Example of Application
8. Discussion
9. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Organization Resilience | Business Model | Business Strategy | Supply Chain Management | Digital Transformation | Leadership | Organizational Structure | Human Resource | |
---|---|---|---|---|---|---|---|---|
Business Model | Pearson Correlation | 1 | 0.328 * | 0.465 ** | 0.560 ** | 0.449 ** | 0.585 ** | 0.348 * |
Sig. (1-tailed) | 0.029 | 0.003 | 0.000 | 0.004 | 0.000 | 0.022 | ||
Business Strategy | Pearson Correlation | 0.328 * | 1 | 0.778 ** | 0.564 ** | 0.472 ** | 0.488 ** | −0.066 |
Sig. (1-tailed) | 0.029 | 0.000 | 0.000 | 0.002 | 0.002 | 0.354 | ||
Supply Chain Management | Pearson Correlation | 0.465 ** | 0.778 ** | 1 | 0.671 ** | 0.522 ** | 0.536 ** | 0.072 |
Sig. (1-tailed) | 0.003 | 0.000 | 0.000 | 0.001 | 0.001 | 0.343 | ||
Digital Transformation | Pearson Correlation | 0.560 ** | 0.564 ** | 0.671 ** | 1 | 0.612 ** | 0.677 ** | 0.182 |
Sig. (1-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.151 | ||
Leadership | Pearson Correlation | 0.449 ** | 0.472 ** | 0.522 ** | 0.612 ** | 1 | 0.779 ** | 0.105 |
Sig. (1-tailed) | 0.004 | 0.002 | 0.001 | 0.000 | 0.000 | 0.278 | ||
Organizational structure | Pearson Correlation | 0.585 ** | 0.488 ** | 0.536 ** | 0.677 ** | 0.779 ** | 1 | 0.140 |
Sig. (1-tailed) | 0.000 | 0.002 | 0.001 | 0.000 | 0.000 | 0.215 | ||
Human resource | Pearson Correlation | 0.348 * | −0.066 | 0.072 | 0.182 | 0.105 | 0.140 | 1 |
Sig. (1-tailed) | 0.022 | 0.354 | 0.343 | 0.151 | 0.278 | 0.215 |
Infrastructure System | Infrastructure | Financial Resource and Investment | Standardization | Governance | |
---|---|---|---|---|---|
Infrastructure | Pearson Correlation | 1 | 0.457 ** | 0.361 * | 0.009 |
Sig. (1-tailed) | 0.004 | 0.020 | 0.480 | ||
Financial Resource and Investment | Pearson Correlation | 0.457 ** | 1 | 0.554 ** | 0.104 |
Sig. (1-tailed) | 0.004 | 0.000 | 0.280 | ||
Standardization | Pearson Correlation | 0.361 * | 0.554 ** | 1 | 0.234 |
Sig. (1-tailed) | 0.020 | 0.000 | 0.092 | ||
Governance | Pearson Correlation | 0.009 | 0.104 | 0.234 | 1 |
Sig. (1-tailed) | 0.480 | 0.280 | 0.092 |
Manufacturing System | Additive Manufacturing | Artificial Intelligence Technology | Logistics System | Collaborative Robot | Customized Product | Industrial Automation | Industrial Internet | Machine Monitoring System | Vertical and Horizontal Integration | |
---|---|---|---|---|---|---|---|---|---|---|
Additive Manufacturing | Pearson Correlation | 1 | −0.181 | −0.092 | −0.249 | −0.104 | −0.140 | −0.313* | −0.092 | −0.040 |
Sig. (1-tailed) | 0.152 | 0.302 | 0.078 | 0.278 | 0.215 | 0.036 | 0.303 | 0.415 | ||
Artificial Intelligence Technology | Pearson Correlation | −0.181 | 1 | 0.819 ** | 0.427 ** | 0.821 ** | 0.742 ** | 0.408 ** | 0.710 ** | 0.733 ** |
Sig. (1-tailed) | 0.152 | 0.000 | 0.006 | 0.000 | 0.000 | 0.008 | 0.000 | 0.000 | ||
Logistics System | Pearson Correlation | −0.092 | 0.819 ** | 1 | 0.451 ** | 0.895 ** | 0.689 ** | 0.295 * | 0.562 ** | 0.799 ** |
Sig. (1-tailed) | 0.302 | 0.000 | 0.004 | 0.000 | 0.000 | 0.045 | 0.000 | 0.000 | ||
Collaborative Robot | Pearson Correlation | −0.249 | 0.427 ** | 0.451 ** | 1 | 0.534 ** | 0.746 ** | 0.435 ** | 0.235 | 0.396 * |
Sig. (1-tailed) | 0.078 | 0.006 | 0.004 | 0.001 | 0.000 | 0.005 | 0.090 | 0.012 | ||
Customized Product | Pearson Correlation | −0.104 | 0.821 ** | 0.895 ** | 0.534 ** | 1 | 0.746 ** | 0.426 ** | 0.526 ** | 0.780 ** |
Sig. (1-tailed) | 0.278 | 0.000 | 0.000 | 0.001 | 0.000 | 0.006 | 0.001 | 0.000 | ||
Industrial Automation | Pearson Correlation | −0.140 | 0.742 ** | 0.689 ** | 0.746 ** | 0.746 ** | 1 | 0.424 ** | 0.643 ** | 0.571 ** |
Sig. (1-tailed) | 0.215 | 0.000 | 0.000 | 0.000 | 0.000 | 0.006 | 0.000 | 0.000 | ||
Industrial Internet | Pearson Correlation | −0.313 * | 0.408 ** | 0.295 * | 0.435 ** | 0.426 ** | 0.424 ** | 1 | 0.124 | 0.234 |
Sig. (1-tailed) | 0.036 | 0.008 | 0.045 | 0.005 | 0.006 | 0.006 | 0.243 | 0.099 | ||
Machine Monitoring System | Pearson Correlation | −0.092 | 0.710 ** | 0.562 ** | 0.235 | 0.526 ** | 0.643 ** | 0.124 | 1 | 0.482 ** |
Sig. (1-tailed) | 0.303 | 0.000 | 0.000 | 0.090 | 0.001 | 0.000 | 0.243 | 0.003 | ||
Vertical and Horizontal integration | Pearson Correlation | −0.040 | 0.733 ** | 0.799 ** | 0.396 * | 0.780 ** | 0.571 ** | 0.234 | 0.482 ** | 1 |
Sig. (1-tailed) | 0.415 | 0.000 | 0.000 | 0.012 | 0.000 | 0.000 | 0.099 | 0.003 |
Digital Literacy | Big Data Analytics | Circular Economy | Information System | Radio Frequency Identification | Tracking System | Cybersecurity | Predictive Maintenance | |
---|---|---|---|---|---|---|---|---|
Big Data Analytics | Pearson Correlation | 1 | −0.081 | 0.585 ** | 0.692 ** | 0.473 ** | 0.579 ** | 0.432 ** |
Sig. (1-tailed) | 0.325 | 0.000 | 0.000 | 0.002 | 0.000 | 0.005 | ||
Circular Economy | Pearson Correlation | −0.081 | 1 | −0.091 | 0.168 | 0.036 | −0.152 | 0.084 |
Sig. (1-tailed) | 0.325 | 0.305 | 0.171 | 0.420 | 0.195 | 0.318 | ||
Information System | Pearson Correlation | 0.585 ** | −0.091 | 1 | 0.413 ** | 0.387 * | 0.413 ** | 0.398 ** |
Sig. (1-tailed) | 0.000 | 0.305 | 0.008 | 0.012 | 0.008 | 0.010 | ||
Radio Frequency Identification | Pearson Correlation | 0.692 ** | 0.168 | 0.413 ** | 1 | 0.721 ** | 0.503 ** | 0.634 ** |
Sig. (1-tailed) | 0.000 | 0.171 | 0.008 | 0.000 | 0.001 | 0.000 | ||
Tracking System | Pearson Correlation | 0.473 ** | 0.036 | 0.387 * | 0.721 ** | 1 | 0.572 ** | 0.462 ** |
Sig. (1-tailed) | 0.002 | 0.420 | 0.012 | 0.000 | 0.000 | 0.003 | ||
Cybersecurity | Pearson Correlation | 0.579 ** | −0.152 | 0.413 ** | 0.503 ** | 0.572 ** | 1 | 0.336 * |
Sig. (1-tailed) | 0.000 | 0.195 | 0.008 | 0.001 | 0.000 | 0.026 | ||
Predictive Maintenance | Pearson Correlation | 0.432 ** | 0.084 | 0.398 ** | 0.634 ** | 0.462 ** | 0.336 * | 1 |
Sig. (1-tailed) | 0.005 | 0.318 | 0.010 | 0.000 | 0.003 | 0.026 |
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Author(s) | Method | Approach |
---|---|---|
del Río González, 2005 [25] | Interviews | The factors influencing clean technology adoption. |
Nemoto et al., 2010 [26] | Literature Review | The factors used to decide to adopt a new technology. |
Darbanhosseiniamirkhiz et al., 2012 [27] | Literature Review | The critical factors that influence the adoption of AMTs and identify hurdles and barriers. |
Sadeghi et al.,2012 [28] | Fuzzy-AHP | Develop a model to evaluate factors affecting Iranian high-tech SME’s success. |
Palacios-Marqués et al., 2014 [29] | Structural Equation Modelling (SEM) | Analyzing factors affecting Web knowledge exchange in SMEs. |
Bayarçelik et al., 2014 [30] | AHP | Determining innovation factors for SMEs. |
Arifin, 2015 [31] | Literature Review | The determinant factors of technology adoption at firm level. |
Osorio-Gallego et al., 2016 [32] | Questionnaire | Analyze the factors that influence the adoption of ICT by SMEs. |
Hassan, 2017 [33] | Questionnaire research | Factors affecting cloud computing adoption in small and medium enterprises (SMEs). |
Raut et al., 2017 [34] | Literature Review and expert opinion | Critical success factors of cloud computing adoption in the MSMEs. |
Hsu et al., 2017 [35] | QFD and fuzzy MADM methods | Suggested factors for improving the sustainability SMEs. |
Blatz et al., 2018 [36] | Questionnaire | The development of digital maturity level of SMEs. |
Danvila-del-Valle et al., 2019 [37] | Bibliometric analysis | Consider human capital and performance by evaluating research on the area of human resources training. |
Sony et al., 2020 [38] | Literature Review | Identifies success factors for implementation of Industry 4.0. |
Moeuf et al., 2020 [39] | Delphi | Identifies success factors, risks, and opportunity of Industry 4.0 in SMEs. |
Gajdzik et al., 2020 [40] | Bibliometric analysis | Identifying key scientific problems of the sustainable development in Industry 4.0. |
Method | Systematics | Reduce Cognitive Bias | Trace the Aspects Linkages | Allow the Hidden and Unexpected Aspects |
---|---|---|---|---|
Bibliometric | ✓ | ✓ | ✓ | ✓ |
Expertise | ✓ | |||
Interview | ✓ | ✓ | ✓ | |
Literature | ✓ | ✓ | ||
Questionnaire | ✓ | ✓ |
Database | Scopus, ISI Web of Science |
---|---|
Time Limitation | 2008–2020 |
Category | Engineering; Computer Science; Business Management and Accounting; Decision Sciences; Mathematics; Social Sciences; Materials Science; Energy; Environmental Science and related. |
Source | Article; Book and Book Chapter |
Language | English |
Keywords Search | Industry 4.0, Smart Manufacturing, Smart Factory, Maturity, Readiness, Assessment, Roadmap, Implementation, Strategy, Factor Successful, Critical Factor, Indicator |
ID | Aspects | Occurrences | Relevance Score |
---|---|---|---|
1 | additive manufacturing | 28 | 0.6743 |
2 | artificial intelligence technology | 56 | 0.2877 |
3 | blockchain technology | 18 | 0.4721 |
4 | business model | 73 | 1.4799 |
5 | business strategy | 13 | 0.6441 |
6 | circular economy | 17 | 1.6295 |
7 | cloud manufacturing | 153 | 0.3343 |
8 | collaborative robot | 77 | 0.6114 |
9 | customized product | 11 | 1.3406 |
10 | big data analytic | 25 | 0.3971 |
11 | data acquisition | 16 | 0.888 |
12 | data connected | 19 | 0.7684 |
13 | data management | 9 | 1.4141 |
14 | cybersecurity | 7 | 0.8387 |
15 | digital transformation | 56 | 1.3022 |
16 | financial resource and investment | 47 | 0.7214 |
17 | governance | 55 | 0.6979 |
18 | human resource | 15 | 0.901 |
19 | industrial automation | 14 | 0.7769 |
20 | infrastructure | 7 | 2.0728 |
21 | information system | 26 | 0.6179 |
22 | leadership | 54 | 0.9993 |
23 | logistics system | 5 | 1.0985 |
24 | industrial internet | 209 | 0.2643 |
25 | machine monitoring system | 51 | 0.3855 |
26 | organizational structure | 41 | 0.5835 |
27 | predictive maintenance | 55 | 0.6987 |
28 | radio frequency identification | 14 | 0.3858 |
29 | real time data | 13 | 1.0773 |
30 | real time monitoring | 13 | 0.4867 |
31 | standardization | 21 | 0.7706 |
32 | supply chain management | 6 | 5.0001 |
33 | tracking system | 13 | 1.4012 |
34 | vertical and horizontal integration | 15 | 0.7538 |
Dimension/Pillar | Industry 4.0 Contributions | Aspects | Exemplary Publication |
---|---|---|---|
Organizational Resilience | The communication with the interdisciplinary department and worker to leadership or manager. Intra-firm and inter-firm departments communication and stakeholders. |
| Birkel et al., 2019 [10]; Brooks et al., 2015 [18]; Haseeb et al., 2019 [54]; Kiel et al., 2017 [57]; Pereira et al., 2017 [6]; Schumacher et al., 2016 [14]; Zhong et al., 2017 [3] |
Infrastructure System | The standard for exchanging data from production and the process have safety, quality/health, and standard regulations. |
| Agca et al., 2017 [13]; Braccini et al., 2019 [58]; Guedria et al., 2009 [53]; Kiel et al., 2017 [57]; Lichtblau et al., 2015 [12]; Muller et al., 2019 [59]; Stock and Seliger, 2016 [60] |
Manufacturing System | Reduce lead time, costs, defect rates, heavy labor and incidents. Increase quality of employee satisfaction. |
| Fatorachian et al., 2018 [61]; Gokalp et al., 2017 [21]; Issa et al., 2017 [22]; Lacoste, 2016 [62]; Lichtblau, 2015 [12]; Lu, 2017 [63]; Pereira et al., 2017 [6]; Kliestik et al., 2020 [64] |
Data Transformation | Predictive maintenance and support the decisions-making based on data structure. Optimize resources and reducing environmental impact. |
| Agca et al., 2017 [13]; Chonsawat et al., 2018 [9]; Hofmann et al., 2017 [65]; Kiel et al., 2017 [57]; Lichtblau et al., 2015 [12], Muller et al., 2020 [66]; Qian et al., 2107 [67] |
Digital Technology | Business opportunities. Increase time to market. Reduce unwilling to pay sufficient money for products and services. Understand customer problems and expectations |
| Braccini et al., 2019 [58]; Brettel et al., 2014 [68]; Ciasullo et al., 2013 [69]; Dombrowski et al., 2017 [70]; Leyh et al., 2016 [15]; Muller et al., 2018 [71]; Viharos, 2017 [20] |
Dimensions | Cronbach’s Alpha | N of Items |
---|---|---|
All aspects | 0.926 | 23 |
Organizational Resilience | 0.898 | 6 |
Business Model | ||
Business Strategy | ||
Digital Transformation | ||
Leadership | ||
Organizational Structure | ||
Supply Chain Management | ||
Infrastructure System | 0.757 | 3 |
Infrastructure | ||
Financial Resource and Investment | ||
Standardization | ||
Manufacturing System | 0.780 | 5 |
Logistics System | ||
Collaborative Robot | ||
Customized Product | ||
Industrial Automation | ||
Industrial Internet | ||
Data Transformation | 0.740 | 4 |
Cloud Manufacturing | ||
Data Acquisition | ||
Data Connected | ||
Real Time Data | ||
Digital Technology | 0.840 | 5 |
Big Data Analytics | ||
Information System | ||
Tracking System | ||
Predictive Maintenance | ||
Cybersecurity |
Dimension | Aspects | Readiness Approach | Example Indicators |
---|---|---|---|
Organizational Resilience | Business Model | Digital business model and service which implications Industry 4.0 [59]. | # Level of ability to achieving to digital platform |
Business Strategy | A strategy, plan, and plan for long-term business competition [72,73]. | % of achieving a strategy goal # Level of ability to implement Industry 4.0 strategy across the business | |
Digital Transformation | Digital in designing to formulate creating marketing products [74]. | # Level of ability to create digital product value % of customer from digital marketing | |
Leadership | An awareness of SME leadership [75]. | # Level of ability to lead achieve a goal % of Industry 4.0 expertise leadership | |
Organizational Structure | The organizational structures open and flexible, environment and culture [76] | # Level of adjustment for a change % of worker achieve Industry 4.0 goal | |
Supply Chain Management | Co-creation value of internal and external stakeholders [77]. | # Level of cooperation with stakeholders % of real-time integrated planning | |
Infrastructure System | Infrastructure | An equipment infrastructure is an important requirement [78]. | % of capital in infrastructure assets |
Financial Resource and Investment | Financial and investment capital improve products or processes [79]. | % of capital R&D % of capital allocated in Industry 4.0 project | |
Standardization | Standardizations in operation, product and process [80]. | % of standards for digital communication channels % of Standard equipment and production | |
Manufacturing System | Logistics System | The transport system in different operation area [81]. | % of automated the material containers and carriers at workstations |
Collaborative Robot | Industrial robots working alongside humans to share their workload [82]. | % of labor productivity % of production efficiency # ability of robotic and human interaction | |
Customized Product | A customized product and flexible production [83]. | % of customized product % of adjusting the customized production | |
Industrial Automation | An adaptation of automated and robotic manufacturing [84]. | % of automated production # OEE | |
Industrial Internet | A solution to provider in automation and production systems of data collection and data transmission [85]. | % of machines automatic exchange data % of the machine and system integrated cross area | |
Data Transformation | Cloud Manufacturing | Technology-driven flexible computing, capabilities for big data and intelligent applications [86]. | % of data storage on cloud # cloud storage capacity |
Data Acquisition | A collect data from modern while still directly connected to the sensor [87]. | % of automatic data collection % of real-time data collection | |
Data Connected | Data sharing among the resources [88]. | % of automatic data connection % of real-time data connection | |
Real Time Data | Real-time data management [89]. | % of automatic real-time data monitoring # Level of capability of real-time data | |
Digital Technology | Big Data Analytics | Data analysis and support to use and manage large amounts of data [90]. | % of data solution implemented across business. # Level of data analytics capability. |
Information System | Interaction between software and business analysis functionality [91]. | % of usage automatic transfer order to production | |
Tracking System | Real-time object detection and tracking [92]. | % of real-time automatic tracking % of material deliveries is monitored in real-time | |
Predictive Maintenance | The predictive maintenance to increase productivity and machine quality [93]. | % of routine machine # rate of fixing broken | |
Cybersecurity | Data security and IT security [94]. | % of replacement software % of area implemented the IT security |
Dimension | Aspects | Indicators | Score |
---|---|---|---|
Organizational Resilience | Business Model | # ability to achieving to digital platform | 2 * |
Business Strategy | % of achieving a strategy goal | 20% | |
# ability to implement Industry 4.0 strategy across the business | 20% | ||
Digital Transformation | % of customer from digital marketing | 10% | |
Leadership | # ability to lead achieve a goal | 3 * | |
Organizational Structure | % of worker achieve Industry 4.0 goal | 40% | |
Supply Chain Management | % of real-time integrated planning | 20% | |
Infrastructure System | Infrastructure | % of capital in infrastructure assets | 40% |
Financial Resource and Investment | % of capital allocated in the Industry 4.0 project | 60% | |
Standardization | % of Standard equipment and production | 60% | |
Manufacturing System | Logistics System | % of automated the material containers and carriers at workstations | 10% |
Collaborative Robot | # ability of robotic and human interaction | 1 * | |
Customized Product | % of customized product | 20% | |
Industrial Automation | % of automated production | 20% | |
Industrial Internet | % of production machines automatic exchange data | 20% | |
Data Transformation | Cloud Manufacturing | % of data storage on cloud | 10% |
Data Acquisition | % of automatic data collection | 10% | |
% of real-time data collection | 20% | ||
Data Connected | % of real-time data connection | 10% | |
Real Time Data | % of automatic real-time data monitoring | 20% | |
Digital Technology | Big Data Analytics | % of data solution implemented across business | 10% |
Information System | % of usage automatic transfer order to production | 20% | |
Tracking System | % of real-time automatic tracking | 10% | |
Predictive Maintenance | % of routine machine | 60% | |
Cybersecurity | % of area implemented the IT security | 10% |
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Chonsawat, N.; Sopadang, A. Defining SMEs’ 4.0 Readiness Indicators. Appl. Sci. 2020, 10, 8998. https://doi.org/10.3390/app10248998
Chonsawat N, Sopadang A. Defining SMEs’ 4.0 Readiness Indicators. Applied Sciences. 2020; 10(24):8998. https://doi.org/10.3390/app10248998
Chicago/Turabian StyleChonsawat, Nilubon, and Apichat Sopadang. 2020. "Defining SMEs’ 4.0 Readiness Indicators" Applied Sciences 10, no. 24: 8998. https://doi.org/10.3390/app10248998
APA StyleChonsawat, N., & Sopadang, A. (2020). Defining SMEs’ 4.0 Readiness Indicators. Applied Sciences, 10(24), 8998. https://doi.org/10.3390/app10248998