Industry 4.0 Readiness Models: A Systematic Literature Review of Model Dimensions

Prospects and current scenario of industry 4.0 in Bangladeshi textile and apparel industry

This study aims to explore the scopes and challenges, rank the challenges, and provide strategic solutions for adopting Industry Revolution 4.0 (IR 4.0) in Bangladesh's textile and apparel industry. A random survey was administered to a total of 142 factories in Bangladesh. Both quantitative and qualitative methods of analysis were used in this study. The survey includes questions on important study variables, such as big data, smart factories, cyber-physical systems (CPS), the Internet of Things (IoT), interoperability, textile production, and industry performance. The Variable Destination Multiple Access (VDMA) Model has been adopted to design the questionnaire, focusing on qualitative and quantitative questions. The survey dataset was investigated through SmartPLS 4.0 by normality and confirmatory tests. Likert scale data have been analyzed through IBM SPSS software version 26.0 by the exploratory factor analysis method to rank the IR 4.0 adoption variables. Analysis of the survey data indicates the level of adoption of Industry 4.0 in terms of organizational strategy, investment, infrastructure, IT (Information Technology), Ready Made Garments (RMG) skilled workers, smart operations, and smart factories. The study shows that the variable "Review of the strategy using indicators" got the highest ranking in the external factor, 0.791. This clearly indicates that strategy formulation is the topmost priority among other IR 4.0 adoption variables. Consequently, "digital integration" got the lowest loading at 0.620, as IR 4.0 digital technology adoption is very low. The overall maturity level for IR 4.0 adoption in the Bangladesh textile and apparel industry is 1.91 on a 5-point scale, indicating a low adoption level. This study can help concerned policymakers and industrialists who want to implement Industry 4.0 in the textile and RMG sectors to stay competitive in the global market. Alongside this study, it also summarizes the IR 4.0 adoption level in 9 broad categories.

Applications of AI in oil and gas projects towards sustainable development: a systematic literature review

Oil and gas construction projects are critical for meeting global demand for fossil fuels, but they also present unique risks and challenges that require innovative construction approaches. Artificial Intelligence (AI) has emerged as a promising technology for tackling these challenges, and this study examines its applications for sustainable development in the oil and gas industry. Using a systematic literature review (SLR), this research evaluates research trends from 2011 to 2022. It provides a detailed analysis of how AI suits oil and gas construction. A total of 115 research articles were reviewed to identify original contributions, and the findings indicate a positive trend in AI research related to oil and gas construction projects, especially after 2016. The originality of this study lies in its comprehensive analysis of the latest research on AI applications in the oil and gas industry and its contribution to developing recommendations for improving the sustainability of oil and gas projects. This research's originality is in providing insight into the most promising AI applications and methodologies that can help drive sustainable development in the oil and gas industry.

Industry 4.0: critical investigations and synthesis of key findings

The concept of Industry 4.0 has been one of the most debated and trending topics over the last few years. Progressively, it has attracted the attention of academicians, practitioners, and policymakers worldwide. However, there needs to be more systematic review of research in the current literature that captures the current state of this new paradigm. This study aims to address this gap by conducting a comprehensive review of Industry 4.0 previous studies to identify its technological, organisational, and managerial enablers, as well as its implementation challenges and benefits. A systematic literature review was conducted, in which 244 peer-reviewed journal papers were analysed in the Scopus database until the end of May 2022. This study excluded conference papers, book chapters, and journal papers not written in English. The study indicated that industry 4.0 is still an immature topic, and applying this new paradigm is not a matter of technology only. Organisational and managerial aspects should be considered. Additionally, the transition towards Industry 4.0 is a complex task, many obstacles exist, and manufacturing companies should be aware of these challenges for successfully implementing this new paradigm. The obtained results in this study synthesise recent studies published on Industry 4.0 and provide a comprehensive picture of Industry 4.0 and potential research directions for future research. Also, this study offers significant guidelines for managers interested in implementing Industry 4.0.

Application of the Maturity Model in Industrial Corporations

Enterprises need to evaluate for themselves whether they are ready for Industry 4.0 to survive and develop in the era of the Fourth Industrial Revolution. Therefore, it is necessary to conceptualize or develop an Industry 4.0 readiness and maturity model with basic model dimensions. The present study aimed to review the maturity models available in the literature and to develop and implement a comprehensive maturity model that would eliminate the problems in the existing models. Most maturity models developed lack vital dimensions such as laws, incentives, and corporate culture. While developing the model, AHP and expert opinions were used to determine the dimension weights. The model was applied to 87 businesses in various industries at the Ankara Chamber of Industry Industrial Park in Turkey. The developed model calculates the maturity level of the enterprise for six dimensions. The data on 61 corporations where Industry 4.0 technologies were adopted were analyzed based on demographic variables such as the year of establishment, industry, size, capital, and turnover. These findings demonstrated that Industry 4.0 was introduced recently in Turkey and businesses are required to take further steps to keep up with the global digital transformation. Since the number of industries and corporations that are aware of the Industry 4.0 technologies is limited in Ankara, Turkey, only a few businesses adopted the Industry 4.0 technologies. This developed model will make an important contribution to the literature with its unique dimensions. It would pave the way for further research in various industries in Turkey and other nations where Industry 4.0 investments are new.

Technological Acceptance of Industry 4.0 by Students from Rural Areas

In this study, our objective was to identify the factors that explain the acceptance of Industry 4.0 technologies by technical students. Industry 4.0 is made up of a series of technologies, such as the Internet of Things; cyber-physical systems; big data, data analytics, or data mining; cloud computing or the cloud; augmented reality or mixed reality; additive manufacturing or 3D printing; cybersecurity; collaborative robots; artificial intelligence; 3D simulation; digital twin or digital twin; drones. We designed a theoretical model based on the technology acceptance model to explain the acceptance of these technologies. The study was carried out on a sample of 326 technical professional students. Students are considered ideal samples to test theoretical predictions regarding the relationships between variables in emerging technologies. The results show the positive effect of technological optimism on perceived usefulness and ease of use. However, there was not a direct effect on the attitude towards the use. A mediating effect was established. In addition, the facilitating conditions influence optimism and the ease of using the technology. These elements influence the attitude and intention to use, which is consistent with previous studies on technology acceptance. The results will guide the design of public policies to incorporate technologies into education.

Zombification and Industry 4.0—Directional Financialisation against Doomed Industrial Revolution

This contribution addresses the puzzle of whether Industry 4.0 is able to autochthonously bring back the real economy (non-financial corporate sector) into the consciousness of the financial sector. It is all the more important since the conventional wisdom over financialisation says that it cannot be reversed without re-establishing the command of the social and collective over the private and individual for the modern era. Our paper argues that a healthy diffusion of Industry 4.0 is doomed unless some directionality is set within the financialisation process. To this end, by building on the relevant lessons of complexity science, it investigates the complex nexus among financialisation, zombification and Industry 4.0 development, an aspect which is not even sporadically examined in the literature. After presenting a short stock take on excessive financialisation, the paper deciphers the main systemic channels of zombification affecting negatively the outlooks of Industry 4.0. Some important policy recommendations are drawn as well.

Analysis of Directional Activities for Industry 4.0 in the Example of Poland and Germany

An analysis of directional activities in Poland and Germany towards the implementation of Industry 4.0 was carried out by comparing the common sustainable development features. The value of production sold along with the benefits of its implementation are presented. The transformation map was characterized along with development areas and potential directions of automation and robotization. Technological possibilities were assessed, considering the production of robots. The execution of activities aimed at implementing solutions in the field of Industry 4.0 in Poland was indicated. The key information gleaned in this study is the awareness of the implemented features proving the fulfillment of conditions relating to Industry 4.0. Action towards the sustainable replacement of machines that require repair or regeneration is significantly related to thinking towards rationalizing the actions taken and assessing the financial capabilities of companies so as not to lead to their collapse. The article presents original research on the characteristics of selected production companies in Poland and Germany striving for digital maturity and the results of our hypotheses. The key direction should be activities aimed at developing a coherent strategy, the proper selection and evaluation of managers, focusing on communication, and the pursuit of intelligent products by creating appropriate integration standards that facilitate the implementation of an innovative process generating modern technologies.

An exploration of organizational readiness factors for Quality 4.0: an intercontinental study and future research directions

Purpose

Quality 4.0 incorporates the role of automation and digitization and provides competitive advantage for organizations by enhancing customer experience and increase profitability. The purpose of this study is to critically examine the organizational readiness factors for the successful implementation of Quality 4.0 implementation and assess their importance.

Design/methodology/approach

This study applies a quantitative research methodology to examine readiness factors of Quality 4.0 in organizations by 147 senior management professionals in various organizations including manufacturing and service companies in America, Asia and Europe participated through an online survey.

Findings

The readiness factors for Quality 4.0 were critically ranked amongst manufacturing and service organizations by senior management professionals from three continents. Five significant reasons for non-adoption of Quality 4.0 were lack of resources, inability to link Quality 4.0 with the corporate strategy and objectives, lack of understanding of benefits, high initial investment and the current quality management strategy and methods are already delivering good results hence unsure of the need for Quality 4.0. The handling of big data in quality management was the most important factor for adopting Quality 4.0, irrespective of the size and nature of the organization. More accuracy and less errors and improved decision-making the factors of adopting Quality 4.0 in service sector were not significant for manufacturing sector. Small and medium-sized enterprises (SMEs) reported that costs and time savings over the long run were not so significant.

Practical implications

This study is focussed on the significance of pros and cons of adopting Quality 4.0 in organizations. Senior managers in both large and SMEs can benefit immensely from understanding before investing heavily towards implementing Quality 4.0. The importance of identified organizational readiness factors for the successful adoption of Quality 4.0 can be used as indicators to understand how ready an organization is to implement Quality 4.0. The top three readiness factors for the successful adoption of Quality 4.0 were identified as: top management commitment, leadership and organizational culture. Improved understanding of the readiness factors can be highly beneficial to senior quality professionals in both manufacturing and service companies in the journey towards successful implementation of Quality 4.0.

Originality/value

This is the first empirical study on assessing Quality 4.0 readiness factors at an intercontinental level and therefore serves as a foundation for many future studies. The study provides a theoretical foundation for the Quality 4.0 in terms of organizational readiness for successful adoption and overcoming implementation challenges. During the planning, implementation and progress review of Quality 4.0, review the readiness factors while planning and resourcing a Quality 4.0 implementation strategy to ensure effective performance.

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

The birth of mass production started in the early 1900s. The manufacturing industries were transformed from mechanization to digitalization with the help of Information and Communication Technology (ICT). Now, the advancement of ICT and the Internet of Things has enabled smart manufacturing or Industry 4.0. Industry 4.0 refers to the various technologies that are transforming the way we work in manufacturing industries such as Internet of Things, cloud, big data, AI, robotics, blockchain, autonomous vehicles, enterprise software, etc. Additionally, the Industry 4.0 concept refers to new production patterns involving new technologies, manufacturing factors, and workforce organization. It changes the production process and creates a highly efficient production system that reduces production costs and improves product quality. The concept of Industry 4.0 is relatively new; there is high uncertainty, lack of knowledge and limited publication about the performance measurement and quality management with respect to Industry 4.0. Conversely, manufacturing companies are still struggling to understand the variety of Industry 4.0 technologies. Industrial standards are used to measure performance and manage the quality of the product and services. In order to fill this gap, our study focuses on how the manufacturing industries use different industrial standards to measure performance and manage the quality of the product and services. This paper reviews the current methods, industrial standards, key performance indicators (KPIs) used for performance measurement systems in data-driven Industry 4.0, and the case studies to understand how smart manufacturing companies are taking advantage of Industry 4.0. Furthermore, this article discusses the digitalization of quality called Quality 4.0, research challenges and opportunities in data-driven Industry 4.0 are discussed.

Digital Transformation Models for the I4.0 Transition: Lessons from the Change Management Literature

The growing diffusion of digital technologies, especially in production systems, is leading to a new industrial paradigm, named Industry 4.0 (I4.0), which involves disruptive changes in the way companies organize production and create value. Organizations willing to seize the opportunities of I4.0 must thus innovate their processes and business models. The challenges that companies must face for the transition towards I4.0 paradigm are not trivial. Several digital transformation models and roadmaps have been lately proposed in the literature to support companies in such a transition. The literature on change management stresses that about 70% of change initiatives—independently of the aim—fail to achieve their goals due to the implementation of transformation programs that are affected by well-known mistakes or neglect some relevant aspects, such as lack of management support, lack of clearly defined and achievable objectives and poor communication. This paper investigates whether and to what extent the existing digital transformation models (DTMs) and roadmaps for I4.0 transition consider the lessons learnt in the field of change management. To this aim, a Systematic Literature Review to identify existing models and roadmaps is carried out. The results obtained by the review are discussed under the lens of the change-management literature. Based on that, the shortcomings and weaknesses of existing DTMs are pinpointed. Extant DTMs mainly focus on digital transformation initiatives carried out in manufacturing companies; they do not cover all the phases of the digital transformation process but rather focus on the definition of the I4.0 vision, strategy and roadmap. Little attention is devoted to the implementation and consolidation of digital change. Change management lessons are considered to a limited extent, based on which, some suggestions for better dealing with digital transformation initiatives are discussed. The paper contributes to advancing knowledge on models and approaches to support organizations in managing digital transformation. The identification of change management activities that a digital transformation initiative should involve as well as the suggestions on how to effectively deal with it can be used by managers to successfully lead the I4.0 transition journey in their organizations.

How does performance vary between early and late adopters of Industry 4.0? A qualitative viewpoint

Purpose

Industry 4.0 is a new trend among organizations. Some organizations have been early adopters or later adopters of Industry 4.0. The purpose of this paper is to investigate how performance effects vary between early and late adopters of Industry 4.0.

Design/methodology/approach

This study applies a qualitative research methodology using grounded theory. 14 senior management professionals who have implemented Industry 4.0 participated in this study through a theoretical and snowball sampling approach. These professionals were from manufacturing and service sectors, from North America, Europe and Asia. The study used semi structured open-ended interviews to capture the organizational performance on operational, financial, environmental and social dimensions.

Findings

The findings were analyzed in terms of four broad themes which emerged from the interviews. In operational performance the operational and implementation cost will be higher for early adopters. The late adopters may enjoy the advantage in terms of improved business models. In terms of financial performance, the early adopters may see a marginal increase in profit and increased stock price compared to late adopters. The performance on the environmental dimension will see early adopters enjoying material efficiency, energy savings and an improved image of the company compared to late adopters. In social performance, the early adopters will provide a better quality of work life, safer manufacturing environment. However, the resistance from labor unions will be higher for early adopters compared to late adopters.

Practical implications

Organizations must decide the timing of implementation of Industry 4.0. This study will act as a guide wherein they can decide to be an early adopter or late adopter based on knowledge of the resulting performance consequences.

Originality/value

This is the first paper that studies the performance effects of early versus late adopters of Industry 4.0.

Development and Validation of Industry 4.0 Readiness Scale — A Formative Model

The purpose of this paper is to develop a suitable formative scale for Industry 4.0 readiness assessment and validate in the Indian steel manufacturing sector. For this, a literature review was undertaken to identify the relevant dimensions and items to assess the Industry 4.0 readiness at micro-level. Further, a pilot study and content validity were undertaken with experts from the industry and academia to find out the relevance of the dimensions and their items. The index thus developed was administered among top-level managers from steel manufacturing organizations and the data was analyzed using PLS-SEM. The findings revealed the most important parameters — strategy & organization; business model; manufacturing & operations; supply chain; products & services along with 21 indicators to be significant in all cases to assess Industry 4.0 readiness.

A Review of Attacks, Vulnerabilities, and Defenses in Industry 4.0 with New Challenges on Data Sovereignty Ahead

The concepts brought by Industry 4.0 have been explored and gradually applied.The cybersecurity impacts on the progress of Industry 4.0 implementations and their interactions with other technologies require constant surveillance, and it is important to forecast cybersecurity-related challenges and trends to prevent and mitigate these impacts. The contributions of this paper are as follows: (1) it presents the results of a systematic review of industry 4.0 regarding attacks, vulnerabilities and defense strategies, (2) it details and classifies the attacks, vulnerabilities and defenses mechanisms, and (3) it presents a discussion of recent challenges and trends regarding cybersecurity-related areas for Industry 4.0. From the systematic review, regarding the attacks, the results show that most attacks are carried out on the network layer, where dos-related and mitm attacks are the most prevalent ones. Regarding vulnerabilities, security flaws in services and source code, and incorrect validations in authentication procedures are highlighted. These are vulnerabilities that can be exploited by dos attacks and buffer overflows in industrial devices and networks. Regarding defense strategies, Blockchain is presented as one of the most relevant technologies under study in terms of defense mechanisms, thanks to its ability to be used in a variety of solutions, from Intrusion Detection Systems to the prevention of Distributed dos attacks, and most defense strategies are presented as an after-attack solution or prevention, in the sense that the defense mechanisms are only placed or thought, only after the harm has been done, and not as a mitigation strategy to prevent the cyberattack. Concerning challenges and trends, the review shows that digital sovereignty, cyber sovereignty, and data sovereignty are recent topics being explored by researchers within the Industry 4.0 scope, and GAIA-X and International Data Spaces are recent initiatives regarding data sovereignty. A discussion of trends is provided, and future challenges are pointed out.

Conceptualizing Industry 4.0 readiness model dimensions: an exploratory sequential mixed-method study

Purpose

Organizations use Industry 4.0 readiness models to evaluate their preparedness prior to the implementation of Industry 4.0. Though there are many studies on Industry 4.0 readiness models, the dimensions of readiness differ. Besides, there is no study empirically validating the readiness model in different sectors or types of organization. The purpose of this study is to conceptualize the dimensions of the Industry 4.0 readiness model and subsequently evaluate the criticality of these dimensions in manufacturing, service, small and medium-sized enterprises (SMEs) and large enterprises (LEs).

Design/methodology/approach

The study uses an exploratory sequential mixed method design. In phase one, 37 senior managers participated through a purposive sampling frame. In phase two, 70 senior managers participated in an online survey.

Findings

The results of the study indicated that the Industry 4.0 readiness model has 10 dimensions. Further, the criticality of the dimensions as applied to different sectors and type of organizations is put forward. This study will help manufacturing, services, SMEs and LEs to evaluate Industry 4.0 readiness before commencing the deployment of Industry 4.0.

Practical implications

The findings can be very beneficial for Industry 4.0 practitioners and senior managers in different organisations to understand what readiness dimensions need to be considered prior to implementation of Industry 4.0 technology.

Originality/value

This paper makes an attempt to conceptualize the Industry 4.0 readiness model and utilizes an exploratory mixed method for critically evaluating the dimensions related to the model.

Industry 4.0 Readiness of Technology Companies: A Pilot Study from Malaysia

Industry 4.0 has the potential to cause both evolutionary (operational) and revolutionary (strategic) changes, but assessing the readiness of companies towards Industry 4.0 has largely been a challenge. Industry 4.0 readiness is also important as it is the first step for companies that want to adopt Industry 4.0 technologies. This paper pilot surveys 100 technology companies in Malaysia to understand their overall readiness towards Industry 4.0. In particular, this research paper contributes to the assessment of Industry 4.0 readiness in terms of seven key areas: (i) Market pressure, (ii) risk-taking, (iii) knowledge, (iv) management support, (v) competencies, (vi) motivation and (vii) freedom. These findings can act as stepping stones for managers and companies that are aiming towards the implementation of Industry 4.0 readiness.

Embracing Industry 4.0: Empirical Insights from Malaysia

Industry 4.0 revolution, with its cutting-edge technologies, is an enabler for businesses, particularly in reducing the cost and improving the productivity. However, a large number of organizations are still too in their infancy to leverage the true potential of Industry 4.0 and its technologies. This paper takes a quantitative approach to reveal key insights from the companies that have implemented Industry 4.0 technologies. For this purpose, 238 technology companies in Malaysia were studied through a survey questionnaire. As technology companies are usually the first in line to adopt new technologies, they can be studied better as leaders in adopting the latest technologies. The findings of this descriptive study surfaced an array of insights in terms of Industry 4.0 readiness, Industry 4.0 technologies, leadership, strategy, and innovation. This research paper contributes by providing 10 key empirical insights on Industry 4.0 that can be utilized by managers to pace up their efforts towards digital transformation, and can help the policymakers in drafting the right policy to drive the digital revolution.