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Purpose The purpose of this paper is to aim at identifying the relationships between Industry 4.0 (I4.0) technologies and Lean Manufacturing (LM) practices. Design/methodology/approach A systematic literature review was conducted, in which 93 studies were analyzed according to their content and contextualization level. Findings In total, 9 I4.0 technologies and 14 LM practices were identified and categorized according to different levels of both value stream application and synergy. From the 126 pairwise relationships, 24 were classified as being of high synergy (e.g. relationship between Cyber-Physical Systems and value stream mapping), revealing the existence of a positive interaction between LPs and I4.0 technologies toward the achievement of a higher operational performance. Further, three future research opportunities were suggested: to validate the proposed synergies among LPs and I4.0 technologies; to distinguish the effects of relationships on all levels of flow; and to examine the effect of such relationships on operational performance. Originality/value With the emergence of the Fourth Industrial Revolution, the specificities on the relationship between LM and I4.0 still need further investigation. This paper provides a better understanding of existing literature related to I4.0, LM, and their relationship, as well as pointing out research gaps to encourage future works.

Purpose The purpose of this paper is to explore how rising technologies from Industry 4.0 can be integrated with circular economy (CE) practices to establish a business model that reuses and recycles wasted material such as scrap metal or e-waste. Design/methodology/approach The qualitative research method was deployed in three stages. Stage 1 was a literature review of concepts, successful factors and barriers related to the transition towards a CE along with sustainable supply chain management, smart production systems and additive manufacturing (AM). Stage 2 comprised a conceptual framework to integrate and evaluate the synergistic potential among these concepts. Finally, stage 3 validated the proposed model by collecting rich qualitative data based on semi-structured interviews with managers, researchers and professors of operations management to gather insightful and relevant information. Findings The outcome of the study is the recommendation of a circular model to reuse scrap electronic devices, integrating web technologies, reverse logistics and AM to support CE practices. Results suggest a positive influence from improving business sustainability by reinserting waste into the supply chain to manufacture products on demand. Research limitations/implications The impact of reusing wasted materials to manufacture new products is relevant to minimising resource consumption and negative environmental impacts. Furthermore, it avoids hazardous materials ending up in landfills or in the oceans, seriously threatening life in ecosystems. In addition, reuse of wasted material enables the development of local business networks that generate jobs and improve economic performance. Practical implications First, the impact of reusing materials to manufacture new products minimises resource consumption and negative environmental impacts. The circular model also encourages keeping hazardous materials that seriously threaten life in ecosystems out of landfills and oceans. For this study, it was found that most urban waste is plastic and cast iron, leaving room for improvement in increasing recycling of scrap metal and similar materials. Second, the circular business model promotes a culture of reusing and recycling and motivates the development of collection and processing techniques for urban waste through the use of three-dimensional (3D) printing technologies and Industry 4.0. In this way, the involved stakeholders are focused on the technical parts of recycling and can be better dedicated to research, development and innovation because many of the processes will be automated. Social implications The purpose of this study was to explore how Industry 4.0 technologies are integrated with CE practices. This allows for the proposal of a circular business model for recycling waste and delivering new products, significantly reducing resource consumption and optimising natural resources. In a first stage, the circular business model can be used to recycle electronic scrap, with the proposed integration of web technologies, reverse logistics and AM as a technological platform to support the model. These have several environmental, sociotechnical and economic implications for society. Originality/value The sociotechnical aspects are directly impacted by the circular smart production system (CSPS) management model, since it creates a new culture of reuse and recycling techniques for urban waste using 3D printing technologies, as well as Industry 4.0 concepts to increase production on demand and automate manufacturing processes. The tendency of the CSPS model is to contribute to deployment CE in the manufacture of new products or parts with AM approaches, generating a new path of supply and demand for society.

PurposeThe digital transformation under Industry 4.0 is complex and resource-intensive, making a strategic digitalization guideline vital to small and medium-sized enterprises' success in the Industry 4.0 transition. The present study aims to provide manufacturing small and medium-sized enterprises (SMEs) with a guideline for digital transformation success under Industry 4.0.Design/methodology/approachThe study first performed a content-centric literature review to identify digital transformation success determinants. The study further implemented interpretive structural modeling to extract the order at which the success determinants should be present to facilitate the SMEs’ digital transformation success optimally. The interpretive model and interpretive logic knowledge base matrix were also used for developing the digital transformation guideline.FindingsEleven success determinants are vital to SMEs’ digital transformation efforts. For example, results revealed that external support for digitalization is the first step in ensuring digital transformation success among SMEs, while operations technology readiness is the most inaccessible success determinant.Research limitations/implicationsThe study highlights the degree of importance of the 11 success determinants identified, which magnifies each determinant's strategic priority based on its driving power and dependence power. Theorizing the dependent variable of “digital transformation success” and quantitatively measuring the extent to which each success determinant contributes to explaining “digital transformation success” offers an exciting opportunity for future research.Practical implicationsDigital transformation success phenomenon within the Industry 4.0 context is significantly different from the digitalization success concept within the traditional literature. The digital transformation under Industry 4.0 is immensely resource-intensive and complex. Smaller manufacturers must have specific capabilities such as change management and digitalization strategic planning capability to reach a certain degree of information, digital, operations and cyber maturity.Originality/valueThe digital transformation success guide developed in the study describes each success determinants' functionality in relation to other determinants and explains how they might contribute to the digital transformation success within the manufacturing sector. This guide enables smaller manufacturers to better understand the concept of manufacturing digital transformation under Industry 4.0 and devise robust strategies to steer their digital transformation process effectively.

PurposeThe purpose of this paper is to investigate how much the Italian manufacturing companies are ready to be concretely involved in the so-called “Industry 4.0” (I4.0) journey. In particular, this paper focuses on analyzing the knowledge and adoption levels of specific I4.0 enabling technologies, also considering how organizations are involved and which are the main benefits and obstacles.Design/methodology/approachA descriptive survey has been carried out on a total of 103 respondents related to manufacturing companies of different sizes. Data collected were analyzed in order to answer five specific research questions.FindingsThe findings from the survey demonstrate that Italian manufacturing companies are in different positions in their journey toward the I4.0 paradigm, mainly depending on their size and informatization level. Furthermore, not all the business functions are adequately involved in this transformation and their awareness about this new paradigm seems quite low because of the absence of specific managerial roles to guide this revolution. Finally, there are strong differences concerning both benefits and obstacles related to the adoption of I4.0 paradigm, depending on the technology adoption level.Research limitations/implicationsFuture research should focus on developing case studies about pilot I4.0 practitioners in order to understand the root cause of successful cases. Both managerial and practical references should be developed, helping Italian manufacturing enterprises to consolidate and strengthen their position in global competitive market. Finally, it would be interesting to carry out the same study in other countries in order to make comparisons and suitable benchmark analyses.Originality/valueDespite scholars have debated about the adoption of technologies and the benefits related to the I4.0 paradigm, to the best of authors’ knowledge, only a few empirical surveys have been carried out until now on the adoption level of I4.0 principles in the manufacturing sector of a specific country.

Purpose The purpose of this paper is to contribute to the existing knowledge about the relationships between advanced manufacturing technology (AMT), lean manufacturing (LM), agile manufacturing (AM), and business performance. Design/methodology/approach A questionnaire-based survey was performed to collect data from 189 Iranian automobile part manufacturers. Statistical analysis of hypothesized relationships was conducted via partial least squares structural equation modeling. Findings AMT significantly contributes to the development of both LM and AM. These manufacturing systems can co-exist in one system, and LM is a precursor to AM. LM contributes to operational performance whereas AM improves marketing performance and financial performance. Research limitations/implications Relying on the cross-sectional data of this research, and lack of generalizability of findings are key limitations. An interesting direction for future research would be to empirically offer a hybrid lean-agile approach and further map the mechanism through which this hybrid approach can be achieved in practice. Practical implications Both LM and AM are information-intensive and highly supported by AMT. They contribute to different aspects of business performance. Pursuing both cost-leadership strategy and product mix flexibility is viable via hybridizing the lean and agile systems. Originality/value This study is among the first to address issues related to the lean-AM relationship among developing countries. This study is unique in the sense it shows the mechanism through which the value of AMT is truly transformed to performance improvement.

Process optimization normally involves the combination of mathematical and statistical techniques which can be approached by distinct ways. Despite the fact that different methods can be found in the literature, the response surface methodology raised as one of the most effective ways for performing process optimization, by combining design and analysis of experiments, modeling techniques, and optimization methods. However, practical guidelines for response surface methodology and critical analysis of its applications are quite scarce. Thus, this paper aims to present the theoretical principles and practical guidelines for carrying response surface methodology as well as to provide empirical evidence on its critical aspects for manufacturing optimization. In order to accomplish with this objective, 49 papers published in the International Journal of Advanced Manufacturing Technology (IJAMT) from 2014 to 2017 were investigated and reproduced, allowing the analysis of 123 response surfaces. Surprisingly, more than 75.29% of the models have presented a saddle shape. The practical meaning of this finding is that the stationary point is not a suitable solution for the optimization of those surfaces. Besides, multiple response surfaces are more commonly found in the literature than individual ones. From this amount of papers, 71.88% of the works investigated have presented significant correlation with their peers and 87.61% have convexity incompatible with the optimization direction. Most of the optimization solutions have found outside of experimental region which reveals a preponderant neglect of the nonlinear constraints involving the definition of the experimental region. It was also verified that the proportion of functions in saddle format corresponds to 96.86% of the models estimated in flat regions. Moreover, it was found that the number of center points is commonly changed and all the manufacturing processes investigated are driven by at most five control parameters. Finally, considering the theoretical principles, the practical guidelines, and the obtained results, a follow-along example involving the optimization of AISI H13-hardened steel turning with PCBN wiper, previously published by the authors in IJAMT, was revisited by using response surface methodology. The results corroborated the proposed framework suitability.

PurposeAlthough the industrial application of drones is increasing quickly, there is a scarcity of applications in manufacturing. The purpose of this paper is to explore current and potential applications of drones in manufacturing, examine the opportunities and challenges involved and propose a research agenda.Design/methodology/approachThe paper reports the result of an extensive qualitative investigation into an emerging phenomenon. The authors build on the literature on advanced manufacturing technologies. Data collected through in-depth interviews with 66 drone experts from 56 drone vendors and related services are analyzed using an inductive research design.FindingsDrones represent a promising AMT that is expected to be used in several applications in manufacturing in the next few years. This paper proposes a typology of drone applications in manufacturing, explains opportunities and challenges involved and develops a research agenda. The typology categorizes four types of applications based on the drones’ capabilities to “see,” “sense,” “move” and “transform.”Research limitations/implicationsThe proposed research agenda offers a guide for future research on drones in manufacturing. There are many research opportunities in the domains of industrial engineering, technology development and behavioral operations.Practical implicationsGuidance on current and promising potentials of drones in manufacturing is provided to practitioners. Particularly interesting applications are those that help manufacturers “see” and “sense” data in their factories. Applications that “move” or “transform” objects are scarcer, and they make sense only in special cases in very large manufacturing facilities.Originality/valueThe application of drones in manufacturing is in its infancy, but is foreseen to grow rapidly over the next decade. This paper presents the first academically rigorous analysis of potential applications of drones in manufacturing. An original and theory-informed typology for drone applications is a timely contribution to the nascent literature. The research agenda presented assists the establishment of a new stream of literature on drones in manufacturing.

Purpose The purpose of this paper is to increase the understanding of how companies can implement rapid manufacturing (RM) (i.e. the use of additive manufacturing (AM) technologies for final part production) for mass customisation (MC), drawing upon the experiences of firms in the dental sector (one of the major users of AM technologies). Design/methodology/approach A framework for implementation of RM for MC was developed from the literature to guide the data gathering. Data from six case companies in the dental sector implementing RM for MC, supplemented with insights from their respective AM machine providers and software companies, were used to analyse how companies implement RM for MC and what considerations and challenges they face in the process. Findings The study shows how implementation of RM for MC entails different considerations depending on the stage of implementation and maturity of involved technologies. In total, 26 challenges have been identified that seem to play a crucial role in implementation. The paper suggests that RM can enable MC in manufacturing by achieving both a high number of units produced and as well as a high level of customisation of each product. Originality/value Based on the review of the literature, no case studies exist that investigate companies implementing RM for MC despite literature having suggested RM as an enabler for MC in manufacturing for many years.

Purpose In recent years, Industry 4.0 has received immense attention from academic community, practitioners and the governments across nations resulting in explosive growth in the publication of articles, thereby making it imperative to reveal and discern the core research areas and research themes of Industry 4.0 extant literature. The purpose of this paper is to discuss research dynamics and to propose a taxonomy of Industry 4.0 research landscape along with future research directions. Design/methodology/approach A data-driven text mining approach, Latent Semantic Analysis (LSA), is used to review and extract knowledge from the large corpus of the 503 abstracts of academic papers published in various journals and conference proceedings. The adopted technique extracts several latent factors that characterise the emerging pattern of research. The cross-loading analysis of high-loaded papers is performed to identify the semantic link between research areas and themes. Findings LSA results uncover 13 principal research areas and 100 research themes. The study discovers “smart factory” and “new business model” as dominant research areas. A taxonomy is developed which contains five topical areas of Industry 4.0 field. Research limitations/implications The data set developed is based on systematic article refining process which includes the keywords search in selected electronic databases and articles limited to English language only. So, there is a possibility that other related work may not be captured in the data set which may be published in other than examined databases and are in non-English language. Originality/value To the best of the authors’ knowledge, this study is the first of its kind that has used the LSA technique to reveal research trends in Industry 4.0 domain. This review will be beneficial to scholars and practitioners to understand the diversity and to draw a roadmap of Industry 4.0 research. The taxonomy and outlined future research agenda could help the practitioners and academicians to position their research work.

Purpose Adopting additive manufacturing (AM) can be challenging, especially in small- and medium-sized enterprises (SMEs) and as part of the supply chains of larger firms. The purpose of this paper is to explore SMEs’ perspectives on the adoption of AM in their specific supply chain positions. The paper develops new knowledge on the challenges SMEs face across the supply chain and the actions they need to promote the adoption of AM. Design/methodology/approach An exploratory interview-based research design is used. In total, 17 interviews were conducted and analyzed in four types of SMEs in their specific positions in AM supply chains. The challenges of adopting AM were mapped, and actions to promote AM adoption were identified. Findings SMEs in different supply chain positions experience different challenges when adopting AM. Strategic and operative actions are suggested as key solutions to overcome the challenges. The benefits of AM on a large scale will be achieved only if the broader supply chain adopts AM technology and experiences its benefits. Research limitations/implications The research is limited by its single-country context, its focus on SMEs, and the selection of early-phase AM-adopter firms. The findings imply a need to understand AM adoption as a shared concern and systemic innovation in the supply chain, instead of just a firm-specific implementation task. Practical implications The findings offer a framework for categorizing AM adoption challenges and propose ways to overcome the challenges of adoption. Originality/value The study reveals that AM adoption is not only a technology issue, but also an issue of strategic, organizational and operational challenges across the supply chain. It shows that when adopting AM, SMEs face particular challenges and require specific solutions according to their supply chain position.