Evaluating Industry 4.0 Implementation Challenges Using Interpretive Structural Modeling and Fuzzy Analytic Hierarchy Process

Bakhtari, Ahmad Reshad; Waris, Mohammad Maqbool; Sanín, Cesar; Szczerbicki, Edward

doi:10.1080/01969722.2020.1871226

Cited by 40 publications

(32 citation statements)

References 39 publications

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“…Thus, training and continuous professional development deserve special attention and importance for Industry 4.0 (Kaya et al, 2020;Schallock et al, 2018). Especially for manufacturing companies, Bakhtari et al (2021) present the lack of leadership from the management, lack of skills for training and education programs, and lack of qualified workforce as the main challenges in implementing Industry 4.0.…”

Section: Theoretical Background Industry 40 and Trainingmentioning

confidence: 99%

Training for Industry 4.0: a systematic literature review and directions for future research

Cazeri

Santa-Eulalia

Serafim

et al. 2022

BJO&PM

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Goal: This study aims to identify, synthesize and classify the main features explored by current research encompassing training for Industry 4.0 and propose directions for future research. Design / Methodology / Approach: The methodological procedure was oriented by a systematic literature review (PRISMA) methodology and followed by content analysis. After a review of academic databases, 78 papers dealing with training for Industry 4.0 were included and classified based on topics related to the science of training and Industry 4.0. Results: Most of the studies in training for Industry 4.0 are oriented to undergraduate and graduate students (in an educational approach) or industrial employees (in an enterprise approach) and, in general, they explore technical, technological, and human oriented subjects. There is a lack concerning studies targeting managers who deal with Industry 4.0 and few studies consider content related to Industry 4.0 impact on business models, sustainability, corporate social responsibility, and other related concepts. Limitations of the investigation: The main limitation is related to the database selection criteria. Search in non-indexed databases, book chapters, and non-English language are not included in this study. Practical Implications: The findings presented in this paper are relevant for researchers and academics as they can serve as a guide for future research work. Consultants, professionals, and trainers can enhance their courses by including currently less explored content or target audiences. Originality/Value: No similar papers were found in scientific databases and this reinforces this manuscript's originality and contribution.

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Section: Theoretical Background Industry 40 and Trainingmentioning

confidence: 99%

Training for Industry 4.0: a systematic literature review and directions for future research

Cazeri

Santa-Eulalia

Serafim

et al. 2022

BJO&PM

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“…For research using respondents from expert groups, including the FISM method, the ideal number of experts is between three and seven people (Hora, 2004). Some FISM-based studies used less than ten respondents, such as Lee, Kang and Chang (2011); Kumar, Luthra and Haleem (2013); Balaji et al (2016); Das, Azmi and James (2020); Bakhtari et al (2021). Given that the results depend upon the judgments of the experts who make decisions, the respondents must possess sufficient knowledge of the study context, as indicated by the length of their hands-on experience, which should not be less than ten years in more than two BOT projects.…”

Section: Data Collectionmentioning

confidence: 99%

Ranking Risks of BOT Toll Road Investment Projects in Indonesia Using Fuzzy Interpretive Structural Modelling

Pramudya

Wibowo

2022

CEB

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The Government of Indonesia implemented the Build, Operate, and Transfer (BOT) model, relying on private investment to bridge the financing gap in developing public infrastructure facilities, including toll roads. Toll road investments, like other greenfield infrastructure projects, are typically characterized by high project risk, which discourages private sector investment. Many previous studies have investigated the various risk events in toll road investment projects, but only a few have assessed the interrelationships of risk events in the Indonesian context. This study fills this knowledge gap by determining which risk event influences other events most. Fuzzy interpretive structural modelling combined with the matrix impact of cross-references multiplication applied to a classification method was used to determine the hierarchy of risk events and analyze their influences on other risk events. A total of fourteen risk events were identified and analyzed. An unclear output specification was found to be the most significant risk event, with the biggest driving power affecting other risks. The findings and limitations of this study point the way forward for future research.

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“…Czech Republic [12], Germany [13], Italy [20]). To account for this gap, different methods are employed in previous researches for barriers prioritizing, such as DEMATEL [5,21], ISM [17], ISM-ANP [18], AHP [22], Fuzzy AHP [23,24], Hesitant fuzzy AHP [25], Fuzzy MICMAC [26], Fuzzy ANP [11], GREY-DEMATEL [2,10], BWM [15]. However, most of these studies have employed methods that account for uncertainty in human decision-making; yet they do not focus on how to cater to reliability in decision-making.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This extensive literature review helped identify a total of 54 Barriers which are presented in Table 1. Environmental side effects and polluting emissions [13,15,28] Production waste [3,28] Lack of clarity in defining return on investment [11,24] Lack of clearly defined economic benefits [6,10,11,22] Long and uncertain amortization [28] Risk of false investments [3,17,28] Shortage of financial resources or investments [5,7,10,11,15,24,28] Too late investments [28] Production process-related costs [13] Government law/regulation [1,3,5,6,11,17,23,29] Lack of coordination and collaboration among supply chain partners [1,5,15] Lack of standards [1, 6, 7, 10, 11, 20, 22-24, 26, 28] Legal and Contractual Uncertainty [1,11,17,20,22,26,28] Lack of management support [1,3,<...>…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying and Prioritizing Barriers of Industry 4.0 Adoption, Using Fuzzy Delphi and Group ZBWM: A Case Study in an Emerging Economy

Dahooie

Habibollahi

Qorbani

2021

Lecture Notes in Operations Research

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In the era of digitalization, the biggest challenge is to eliminate barriers of Industry 4.0 (I4.0) adoption, which maybe even difficult to predict. Successful I4.0 technology implementation can boost productivity, achieve optimum resource management, and meet dynamic customer needs through customized mass production. Studies indicate that the drawbacks of I4.0 adoption vary significantly in different circumstances. To elaborate, new technology implementation may pass a smoother process in developed countries. Although, there might be some different facilitation in developing countries and emerging economies. This research aims to identify the barriers and challenges of I4.0 adoption and prioritize them. For this purpose, at first, a list of potential risks is recognized by a comprehensive literature review. Then, the Fuzzy Delphi method (FDM) is used to assess and finalize the related barriers. Subsequently, the barriers are weighted to the experts' opinion. With the intention to increase the consistency of the study results in this stateof-the-art inquiry and consider the uncertainty and reliability of decision makers' perspectives, Z numbers are incorporated into BWM. Finally, improved group Z-BWM is conducted to find the most relevant barriers in Goldiran (LG-Gplus) company, as a case study in Iran, an emerging economy. The results indicated that lack of financial resources has the highest importance. The result may help DMs and industrial managers in the home appliance industry in Iran to find out the actual barriers in implementing I4.0 technologies and focus their attention on how to obtain the significant advantages of the fourth industrial revolution by a successful I4.0 adoption.

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Evaluating Industry 4.0 Implementation Challenges Using Interpretive Structural Modeling and Fuzzy Analytic Hierarchy Process

Cited by 40 publications

References 39 publications

Training for Industry 4.0: a systematic literature review and directions for future research

Training for Industry 4.0: a systematic literature review and directions for future research

Ranking Risks of BOT Toll Road Investment Projects in Indonesia Using Fuzzy Interpretive Structural Modelling

Identifying and Prioritizing Barriers of Industry 4.0 Adoption, Using Fuzzy Delphi and Group ZBWM: A Case Study in an Emerging Economy

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