scholarly journals The road towards industry 4.0: a comparative study of the state-of-the-art in the Italian manufacturing industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ting Zheng ◽  
Marco Ardolino ◽  
Andrea Bacchetti ◽  
Marco Perona
Keyword(s):  
Technology Adoption ◽  
Comparative Study ◽  
Industry 4.0 ◽  
State Of The Art ◽  
Geographical Area ◽  
The State ◽  
Manufacturing Companies ◽  
Content Type ◽  
Business Functions ◽  
Italian Manufacturing Firms

PurposeThis paper has two objectives: first, to investigate the state-of-the-art of Industry 4.0 (I4.0) adoption in Italian manufacturing firms and, second, to understand variations in technologies implemented and business functions involved, benefits perceived, and obstacles encountered in I4.0 implementation over a three-year period.Design/methodology/approachThe approach adopted in this research is descriptive, nesting longitudinal features. The paper presents a descriptive survey of 102 Italian manufacturing companies. The authors also evaluated non-response biases. The longitudinal approach was achieved by comparing the responses of the 40 sub-samples in common with a second similar survey launched three years prior, which aimed to identify patterns of evolution in the adoption of the I4.0 paradigm.FindingsSurvey findings demonstrate that Italian manufacturing companies still have limited awareness of I4.0 technologies, and the adoption of I4.0 technologies differs per technology. Company size and information system coverage level are the two factors that impact the company's technology adoption level. The comparative study shows that knowledge and adoption increase in a three-year interval with an unbalanced involvement of business functions regarding the I4.0 transformation. Indeed, companies are still seeking I4.0 solutions to reduce costs and lead times primarily, and the benefits perceived by companies are shown to be related to the number of I4.0 technologies in use. Finally, when companies put the I4.0 technologies into practice, competence is constantly considered the most significant barrier.Research limitations/implicationsThis paper aims at conducting a thorough investigation into the development of I4.0 adoption in manufacturing companies. The main limitation of this study concerns the limited number of subjects involved in the longitudinal study (40) and the focus on a limited geographical area (Italy). In addition, more I4.0 technologies could also be incorporated into the survey protocol to gain further insight into I4.0 development.Originality/valueThe authors provide one of the first attempts to assess the variations of I4.0 implementation concerning technology adoption, business function involvement, and the alteration of benefits and obstacles. Several studies presented in the literature highlight the lack of longitudinal studies investigating the development of the I4.0 paradigm in a specific manufacturing context: this paper is the attempt at filling this gap.

scholarly journals Implementing Industry 4.0: assessing the current state

2020 ◽  
Vol 31 (5) ◽  
pp. 825-836
Author(s):  
Roland Ortt ◽  
Claire Stolwijk ◽  
Matthijs Punter
Keyword(s):  
Industry 4.0 ◽  
Large Scale ◽  
The State ◽  
Successful Implementation ◽  
Manufacturing Companies ◽  
Special Issue ◽  
Measurement Instruments ◽  
Content Type ◽  
Research Questions ◽  
Implementation Status

PurposeThe purpose of this paper is to introduce, summarize and combine the results of 11 articles in a special issue on the implementation of Industry 4.0. Industry 4.0 emerged as a phenomenon about a decade ago. That is why, it is interesting now to explore the implementation of the concept. In doing so, four research questions are addressed: (1) What is Industry 4.0? (2) How to implement Industry 4.0? (3) How to assess the implementation status of Industry 4.0? (4) What is the current implementation status of Industry 4.0?Design/methodology/approachSubgroups of articles are formed, around one or more research questions involving the implementation of Industry 4.0. The articles are carefully analyzed to provide comprehensive answers.FindingsBy comparing definitions systematically, the authors show important aspects for defining Industry 4.0. The articles in the special issue explore several cases of manufacturing companies that implemented Industry 4.0. In addition, systematic approaches to aid implementation are described: an approach to combine case-study results to solve new implementation problems, approaches to assess readiness or maturity of companies regarding Industry 4.0 and surveys showing the status of implementation in larger samples of companies as well as showing relationships between company characteristics and type of implementation. Small and large firms differ considerably in their process of implementing Industry 4.0, for example.Research limitations/implicationsThis special issue discusses implementation of Industry 4.0. The issue is limited to 11 articles, each of which with its own strengths and limitations.Practical implicationsThe practical relevance of the issue is that it focuses on the implementation of Industry 4.0. Cases showing successful implementation, measurement instruments to assess degree of implementation and advice how to build a database with cases together with large-scale studies on the state of implementation do provide a wealth of information with a large managerial relevance.Originality/valueThe paper introduces an original take on Industry 4.0 by focusing on implementation. The special issue contains both literature reviews, articles describing case studies of implementation, articles developing systematic measurement instruments to assess degree of implementation and some articles reporting large-scale studies on the state of implementation of Industry 4.0 and thereby combine several perspectives on implementation of Industry 4.0.

Debunking the myth of industry 4.0 in health care: insights from a systematic literature review

2020 ◽  
Vol 32 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Mauro Cavallone ◽  
Rocco Palumbo
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Health Services ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Industry 4.0 ◽  
Services Quality ◽  
State Of The Art ◽  
The State ◽  
Content Type

PurposeIndustry 4.0, artificial intelligence and digitalization have got a momentum in health care. However, scholars and practitioners do not agree on their implications on health services' quality and effectiveness. The article aims at shedding light on the applications, aftermaths and drawbacks of industry 4.0 in health care, summarizing the state of the art.Design/methodology/approachA systematic literature review was undertaken. We arranged an ad hoc research design, which was tailored to the study purposes. Three citation databases were queried. We collected 1,194 scientific papers which were carefully considered for inclusion in this systematic literature review. After three rounds of analysis, 40 papers were taken into consideration.FindingsIndustry 4.0, artificial intelligence and digitalization are revolutionizing the design and the delivery of care. They are expected to enhance health services' quality and effectiveness, paving the way for more direct patient–provider relationships. In addition, they have been argued to allow a more appropriate use of available resources. There is a dark side of health care 4.0 involving both management and ethical issues.Research limitations/implicationsIndustry 4.0 in health care should not be conceived as a self-nourishing innovation; rather, it needs to be carefully steered at both the policy and management levels. On the one hand, comprehensive governance models are required to realize the full potential of health 4.0. On the other hand, the drawbacks of industry 4.0 should be timely recognized and thoroughly addressed.Originality/valueThe article contextualizes the state of the art of industry 4.0 in the health care context, providing some insights for further conceptual and empirical developments.

Practices of preventive maintenance planning in discrete manufacturing industry

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Antti Salonen ◽  
Maheshwaran Gopalakrishnan
Keyword(s):  
Preventive Maintenance ◽  
Manufacturing Industry ◽  
State Of The Art ◽  
The State ◽  
Data Driven ◽  
Manufacturing Companies ◽  
Automotive Manufacturing ◽  
Content Type ◽  
Discrete Manufacturing ◽  
State Of Practice

PurposeThe purpose of this study was to assess the readiness of the Swedish manufacturing industry to implement dynamic, data-driven preventive maintenance (PM) by identifying the gap between the state of the art and the state of practice.Design/methodology/approachAn embedded multiple case study was performed in which some of the largest companies in the discrete manufacturing industry, that is, mechanical engineering, were surveyed regarding the design of their PM programmes.FindingsThe studied manufacturing companies make limited use of the existing scientific state of the art when designing their PM programmes. They seem to be aware of the possibilities for improvement, but they also see obstacles to changing their practices according to future requirements.Practical implicationsThe results of this study will benefit both industry professionals and academicians, setting the initial stage for the development of data-driven, diversified and dynamic PM programmes.Originality/ValueFirst and foremost, this study maps the current state and practice in PM planning among some of the larger automotive manufacturing industries in Sweden. This work reveals a gap between the state of the art and the state of practice in the design of PM programmes. Insights regarding this gap show large improvement potentials which may prove important for academics as well as practitioners.

Industry 4.0 and business process management: state of the art and new challenges

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Patricia Bazan ◽  
Elsa Estevez
Keyword(s):  
Business Process ◽  
Industry 4.0 ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
State Of The Art ◽  
The State ◽  
Event Processing ◽  
Content Type ◽  
Software Ecosystems

PurposeThe objective of the work is to analyze the impact of the Internet of Things (IoT) concepts and associated technologies in the framework of organizations and the management of their processes and how event orientation, as well as the structure of said business processes, can play an important role in this new organizational model. The main contribution of this work is to present a conceptualization of the research, identify approaches and challenges that require further study, and as a result, a proposal for future research.Design/methodology/approachThe methodology comprises a qualitative analysis using secondary data. The approach relies on searches of scientific papers conducted in well-known databases, identifying research work around the IoT and Industry 4.0 applied to business process management. Based on the identified papers, the authors selected the most relevant and the latest publications, and categorized their contributions and findings based on open and selective coding. In total, the analysis is based on 95 papers that were selected and analyzed in depth.FindingsThe results of this research allow analyzing and ordering the existing contributions around Industry 4.0 and its impact on current organizations. The proposed conceptualization was derived from the analysis of the state of the research and identifies four categories: (1) improvements caused by Industry 4.0 and its impact on inter-organizational relations, (2) new architectural models and infrastructure of remote resources, their movement from the cloud to the edge and its effect on business processes, (3) context-aware concepts brought to business process management (BPM) linked to unstructured business processes and (4) complex event processing as a possible means for business processes sensitive to IoT signals.Practical implicationsThe construction of current software ecosystems is strongly affected by the variety of information sources that feed them, as well as their volume. In addition, business processes represent organizations internally and are challenged to transcend the limits of companies due to the mentioned changes in software ecosystems. Industry 4.0 in conjunction with BPM re-defines the business process management paradigm and leads them to acquire the dynamism and sensitivity to the context that they usually did not have, as well as force them to move toward distributed platforms.Originality/valueThis paper assesses the state of the art in Industry 4.0 and business process management. The area can be defined as the intersection of two bigger areas highly relevant for organizations; on the one hand, the management and execution of business processes; and on the other hand, new conceptual, technological and methodological challenges to information systems that have to become more sensitive to event processing and also have to consume a large volume of data permanently and ubiquitously.

Sociotechnical factors and Industry 4.0: an integrative perspective for the adoption of smart manufacturing technologies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Érico Marcon ◽  
Marlon Soliman ◽  
Wolfgang Gerstlberger ◽  
Alejandro G. Frank
Keyword(s):  
Technology Adoption ◽  
Industry 4.0 ◽  
Empirical Studies ◽  
Work Organization ◽  
Organizational Factors ◽  
Smart Manufacturing ◽  
Manufacturing Companies ◽  
Content Type ◽  
Manufacturing Technologies ◽  
Systemic View

PurposeAs the level of implementation of Industry 4.0 increases, misalignments between adopted technologies and organizational factors may result in benefits below expected. This paper aims to analyze how organizational factors can contribute to a higher level of adoption of Industry 4.0 technologies. The paper uses a sociotechnical perspective lens to achieve this aim.Design/methodology/approachUsing a sample of 231 manufacturing companies in Denmark, a leading country in Industry 4.0 readiness, the paper analyzes through cluster analysis and logistic regression whether the development of four sociotechnical dimensions – that is, Social, Technical, Work Organization and Environmental factors – in these companies can benefit the achievement of higher levels of Industry 4.0 technology adoption.FindingsThe results show that companies focused on the development of sociotechnical aspects generally present higher Industry 4.0 adoption levels. However, some sociotechnical factors are less supportive than others.Originality/valueBased on these results, practitioners can plan the adoption of advanced technologies, using a systemic organizational view. This study provides evidence on a growing field with few empirical studies available. The paper contributes by providing an analysis of a leading country in Industry 4.0 implementation, presenting a systemic view on technology adoption in the Industry 4.0 context.

Disentangling the link between ICT and Industry 4.0: impacts on knowledge-related performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marco Bettiol ◽  
Mauro Capestro ◽  
Eleonora Di Maria ◽  
Stefano Micelli
Keyword(s):  
Information And Communication Technologies ◽  
Technology Use ◽  
Industry 4.0 ◽  
Quantitative Research ◽  
Digital Technologies ◽  
Survey Method ◽  
Manufacturing Companies ◽  
Content Type ◽  
Ict Industry ◽  
Italian Manufacturing Firms

PurposeIndustry 4.0 technologies are promising to increase manufacturing companies' performance through the new knowledge that such digital technologies allow to create and manage within the firm boundaries and through customer interactions. Despite the great attention on the Industry 4.0 adoption paths, little is known about the relationships with previous waves of digital technologies, namely, information and communication technologies (ICTs), and how different groups of both types of technologies link to knowledge and its related performances.Design/methodology/approachThe study employed a quantitative research design using a survey method. Submitting the questionnaire to entrepreneurs, chief operation officers or managers in charge of the operational and technological processes of Italian manufacturing firms, 206 respondents stated that their firm has adopted at least one of the seven Industry 4.0 technologies investigated.FindingsThe findings of the study highlight the positive relationship between ICT and Industry 4.0 technologies in terms of both intensity and groups of technologies (Web-based, Management and Manufacturing ICT; Operation, Customization and Data-processing 4.0), and how technologies affect knowledge-related performances in terms of products and processes, job-learning, product-related services and customer involvement.Originality/valueThis study is one of the first attempts to link groups of ICT to groups of Industry 4.0 technologies and to explore the effects in terms of knowledge-related performances as a measure of technology use. The study shows strong path dependency among ICT, Industry 4.0 and knowledge performance, enriching the literature on technological innovation and knowledge management.

An experimental study on feature-based SLAM for multi-legged robots with RGB-D sensors

2017 ◽  
Vol 44 (4) ◽  
pp. 428-441 ◽  
Author(s):  
Michał R. Nowicki ◽  
Dominik Belter ◽  
Aleksander Kostusiak ◽  
Petr Cížek ◽  
Jan Faigl ◽  
...  
Keyword(s):  
Performance Metrics ◽  
State Of The Art ◽  
Building Blocks ◽  
Bundle Adjustment ◽  
The State ◽  
Legged Robots ◽  
Evaluation Methodology ◽  
Walking Robots ◽  
Content Type ◽  
Feature Based

Purpose This paper aims to evaluate four different simultaneous localization and mapping (SLAM) systems in the context of localization of multi-legged walking robots equipped with compact RGB-D sensors. This paper identifies problems related to in-motion data acquisition in a legged robot and evaluates the particular building blocks and concepts applied in contemporary SLAM systems against these problems. The SLAM systems are evaluated on two independent experimental set-ups, applying a well-established methodology and performance metrics. Design/methodology/approach Four feature-based SLAM architectures are evaluated with respect to their suitability for localization of multi-legged walking robots. The evaluation methodology is based on the computation of the absolute trajectory error (ATE) and relative pose error (RPE), which are performance metrics well-established in the robotics community. Four sequences of RGB-D frames acquired in two independent experiments using two different six-legged walking robots are used in the evaluation process. Findings The experiments revealed that the predominant problem characteristics of the legged robots as platforms for SLAM are the abrupt and unpredictable sensor motions, as well as oscillations and vibrations, which corrupt the images captured in-motion. The tested adaptive gait allowed the evaluated SLAM systems to reconstruct proper trajectories. The bundle adjustment-based SLAM systems produced best results, thanks to the use of a map, which enables to establish a large number of constraints for the estimated trajectory. Research limitations/implications The evaluation was performed using indoor mockups of terrain. Experiments in more natural and challenging environments are envisioned as part of future research. Practical implications The lack of accurate self-localization methods is considered as one of the most important limitations of walking robots. Thus, the evaluation of the state-of-the-art SLAM methods on legged platforms may be useful for all researchers working on walking robots’ autonomy and their use in various applications, such as search, security, agriculture and mining. Originality/value The main contribution lies in the integration of the state-of-the-art SLAM methods on walking robots and their thorough experimental evaluation using a well-established methodology. Moreover, a SLAM system designed especially for RGB-D sensors and real-world applications is presented in details.

scholarly journals The State-of-the-Art Technology of Currency Identification

2017 ◽  
Vol 9 (3) ◽  
pp. 58-72 ◽  
Author(s):  
Guangyu Wang ◽  
Xiaotian Wu ◽  
WeiQi Yan
Keyword(s):  
Feature Extraction ◽  
New Zealand ◽  
Comparative Study ◽  
State Of The Art ◽  
The State ◽  
Classification Algorithms ◽  
Security Issue ◽  
The Public ◽  
Us Dollar ◽  
Chinese Yuan

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

A new correlation-based approach for ensemble selection in random forests

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mostafa El Habib Daho ◽  
Nesma Settouti ◽  
Mohammed El Amine Bechar ◽  
Amina Boublenza ◽  
Mohammed Amine Chikh
Keyword(s):  
State Of The Art ◽  
Ensemble Methods ◽  
The State ◽  
Ensemble Classifiers ◽  
Content Type ◽  
Pruning Method ◽  
Ensemble Selection ◽  
Small Ensemble ◽  
Short Time ◽  
Pruning Techniques

PurposeEnsemble methods have been widely used in the field of pattern recognition due to the difficulty of finding a single classifier that performs well on a wide variety of problems. Despite the effectiveness of these techniques, studies have shown that ensemble methods generate a large number of hypotheses and that contain redundant classifiers in most cases. Several works proposed in the state of the art attempt to reduce all hypotheses without affecting performance.Design/methodology/approachIn this work, the authors are proposing a pruning method that takes into consideration the correlation between classifiers/classes and each classifier with the rest of the set. The authors have used the random forest algorithm as trees-based ensemble classifiers and the pruning was made by a technique inspired by the CFS (correlation feature selection) algorithm.FindingsThe proposed method CES (correlation-based Ensemble Selection) was evaluated on ten datasets from the UCI machine learning repository, and the performances were compared to six ensemble pruning techniques. The results showed that our proposed pruning method selects a small ensemble in a smaller amount of time while improving classification rates compared to the state-of-the-art methods.Originality/valueCES is a new ordering-based method that uses the CFS algorithm. CES selects, in a short time, a small sub-ensemble that outperforms results obtained from the whole forest and the other state-of-the-art techniques used in this study.

The State-of-the-Art Technology of Currency Identification

2018 ◽  
pp. 252-269
Author(s):  
Guangyu Wang ◽  
Xiaotian Wu ◽  
WeiQi Yan
Keyword(s):  
Feature Extraction ◽  
New Zealand ◽  
Comparative Study ◽  
State Of The Art ◽  
The State ◽  
Classification Algorithms ◽  
Security Issue ◽  
The Public ◽  
Us Dollar ◽  
Chinese Yuan

The security issue of currency has attracted awareness from the public. De-spite the development of applying various anti-counterfeit methods on currency notes, cheaters are able to produce illegal copies and circulate them in market without being detected. By reviewing related work in currency security, the focus of this paper is on conducting a comparative study of feature extraction and classification algorithms of currency notes authentication. We extract various computational features from the dataset consisting of US dollar (USD), Chinese Yuan (CNY) and New Zealand Dollar (NZD) and apply the classification algorithms to currency identification. Our contributions are to find and implement various algorithms from the existing literatures and choose the best approaches for use.

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