A labelling system and automation comparison index for industry 4.0 system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shailendra Kumar ◽  
Mohammad Asjad ◽  
Mohd. Suhaib
Keyword(s):  
Industry 4.0 ◽  
Manufacturing System ◽  
Threshold Value ◽  
Fuzzy Cognitive Maps ◽  
Automated System ◽  
Content Type ◽  
Level Of Automation ◽  
Industrial Sectors ◽  
Automation Level ◽  
Labelling System

Purpose This paper aims to put forward a labelling system capable of reflecting the level of different Industry 4.0 (I4.0)features present in a manufacturing system and further propose a comparative index to collectively estimate and compare the system automation level. Design/methodology/approach Data for the empirical study were collected from interactions with the practising managers and experts. A relationship among the six I4.0 features is developed with fuzzy cognitive maps. Findings The paper proposed a simple and easy-to-understand labelling system for I4.0 systems, which indicates the automation level in each of six dimensions of any manufacturing system. The system is further strengthened by a proposed automation comparative index (ACI), which collectively reflects the automation level on a scale of “0” to “1”. Thus, the labelling system and parameter could help in comparing the level of automation in the manufacturing system and further decision-making. Research limitations/implications Only seven industrial sectors are illustrated in the paper, but the proposed concept of the classification scheme and ACI find their applicability on a large spectrum of industries; thus, the concept can be extended to other industrial sectors. Furthermore, a threshold value of ACI is a differentiator between a I4.0 and other automated systems. Both aspects have the scope of further work. Practical implications The way and pace by which the industrial world takes forward the concept of I4.0, soon it will need a labelling system and a parameter to assess the automation level of any automated system. The scheme assesses the automation level present in a manufacturing system. It will also estimate the level of the presence of each of all six attributes of an I4.0 system. Both labelling system and ACI will be the practical tools in the hands of the practising managers to help compare, identify the thrust areas and make decisions accordingly. Originality/value To the best of the authors’ knowledge, this is the first study of its kind that proposed the labelling system and automation comparison index for I4.0 systems.

Total quality management 4.0: adapting quality management to Industry 4.0

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fabiane Florencio de Souza ◽  
Alana Corsi ◽  
Regina Negri Pagani ◽  
Giles Balbinotti ◽  
João Luiz Kovaleski
Keyword(s):  
Systematic Review ◽  
Quality Management ◽  
Industry 4.0 ◽  
Ecosystem Model ◽  
Future Research ◽  
Total Quality ◽  
Review Of The Literature ◽  
Content Type ◽  
Industrial Sectors ◽  
Data Collections

PurposeThe purpose of this article is to explore the new concept of TQM 4.0 as a way of adapting quality management (QM) in Industry 4.0 (I4.0), guiding industries to this new phase, which has generated adaptations in numerous areas, one of which is QM and human resources.Design/methodology/approachA systematic review of the literature was carried out. Methodi Ordinatio was applied to build the portfolio of articles with scientific relevance, which is the source of data collections and content analysis. To help out in the analysis, NVivo 12 and VOSviewer software programs were used.FindingsThe results demonstrate that when adapting the QM to the technologies of I4.0, the result is an ecosystem that supports the integration between technology, quality and people in the industrial scenario.Research limitations/implicationsThis article presents a systematic review of the literature, but without delving into specific issues such as the different industrial sectors and the culture of countries in which industries may be inserted, for example, which characterizes a limitation of this research.Practical implicationsThis study provides an ecosystem model that can guide future research, regarding the concept of TQM 4.0, in addition to pointing out some ways of combining technologies, quality and people in the industrial context.Originality/valueThis is one of the first articles to employ a systematic review of the literature using Methodi Ordinatio to build a bibliographic panorama on the intertwining of the themes total QM (TQM) and I4.0, focusing on the emerging concept of TQM 4.0.

Corporate survival in Industry 4.0 era: the enabling role of lean-digitized manufacturing

2019 ◽  
Vol 31 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Morteza Ghobakhloo ◽  
Masood Fathi
Keyword(s):  
Enterprise Resource Planning ◽  
Industry 4.0 ◽  
Manufacturing System ◽  
Resource Planning ◽  
Security And Privacy ◽  
Social Implications ◽  
Future Research ◽  
Manufacturing Firm ◽  
Content Type

Purpose The purpose of this paper is to demonstrate how small manufacturing firms can leverage their Information Technology (IT) resources to develop the lean-digitized manufacturing system that offers sustained competitiveness in the Industry 4.0 era. Design/methodology/approach The study performs an in-depth five years case study of a manufacturing firm, and reports its journey from failure in the implementation of enterprise resource planning to its success in integrating IT-based technology trends of Industry 4.0 with the firm’s core capabilities and competencies while pursuing manufacturing digitization. Findings Industry 4.0 transition requires the organizational integration of many IT-based modern technologies and the digitization of entire value chains. However, Industry 4.0 transition for smaller manufacturers can begin with digitization of certain areas of operations in support of organizational core strategies. The development of lean-digitized manufacturing system is a viable business strategy for corporate survivability in the Industry 4.0 setting. Research limitations/implications Although the implementation of lean-digitized manufacturing system is costly and challenging, this manufacturing strategy offers superior corporate competitiveness in the long run. Since this finding is rather limited to the present case study, assessing the business value of lean-digitized manufacturing system in a larger scale research context would be an interesting avenue for future research. Practical implications Industry 4.0 transition for typical manufacturers should commensurate with their organizational, operational and technical particularities. Digitization of certain operations and processes, when aligned with the firm’s core strategies, capabilities and procedures, can offer superior competitiveness even in Industry 4.0 era, meaning that the strategic plan for successful Industry 4.0 transition is idiosyncratic to each particular manufacturer. Social implications Manufacturing digitization can have deep social implications as it alters inter- and intra-organizational relationships, causes unemployment among low-skilled workforce, and raises data security and privacy concerns. Manufacturers should take responsibility for their digitization process and steer it in a direction that simultaneously safeguards economic, social and environmental sustainability. Originality/value The strategic roadmap devised and employed by the case company for managing its digitization process can better reveal what manufacturing digitization, mandated by Industry 4.0, might require of typical manufacturers, and further enable them to better facilitate their digital transformation process.

Weak GDP may delay policymakers’ ‘Industry 4.0’ plans

2019 ◽  
Keyword(s):  
Industry 4.0 ◽  
Customer Value ◽  
Capital Investment ◽  
Potential Growth ◽  
Content Type ◽  
Data Services ◽  
Industrial Sectors ◽  
Property Data ◽  
The Social ◽  
Development Processes

Significance This spending is needed as manufacturers are under pressure to re-engineer their businesses by deploying technologies to enhance productivity and develop and scale new products and data-based services under the rubric of 'Industry 4.0'. Impacts Technologies will revolutionise every aspect of industry from materials, product development, processes, networks and client interactions. Customer solutions based on intellectual property, data, services, skills and other intangibles will be critical sources of value creation. Capital investment is falling amid rising cashflow pressures and competition and faltering demand; this could reduce potential growth. Slower growth will worsen differences between firms that successfully adopt technologies to enhance customer value and those that do not. Governments will face rising pressure to respond to the social impacts of changes affecting their industrial sectors and to protect jobs.

Exploring relationships for integrating lean, environmental sustainability and industry 4.0

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lígia Lobo Mesquita ◽  
Fabiane Letícia Lizarelli ◽  
Susana Duarte ◽  
Pedro Carlos Oprime
Keyword(s):  
Environmental Sustainability ◽  
Industry 4.0 ◽  
Empirical Studies ◽  
Unified Framework ◽  
Content Type ◽  
Industrial Sectors ◽  
Lean Practices ◽  
And Cluster Analysis ◽  
Organizational Results ◽  
Main Components

Purpose This paper aims to thoroughly identify the forms of integration between Lean, Industry 4.0 (I4.0) and environmental sustainability (ES) by examining the relationships between these three constructs, deepening understanding surrounding the theme and evolving the construction of a framework that can aid managing industrial production processes. Design/methodology/approach A systematic literature review (SLR) was the method used to identify the relationships for integration in the current literature. The SLR was supported by content and cluster analysis. The analyzes identified relationships at two levels. The first level observed relationships for constructs and variables. The second, at the level of constructs and components, which detail the variables. This study also proposes an integrated conceptual framework showing these relationships at the construct, variable and component levels. Findings The results show how these three constructs are related and the study concludes by stating that there is stronger integration among I4.0 technologies and Lean practices for reaching ES. The SLR identified the main components that allowed for this integration, i.e. I4.0 technologies, Big Data, the internet of things and Lean practices, like reducing waste and customer needs. Practical implications From an academic standpoint, this study proposes new lines of research lines that have not been explored thus far, and can be developed via empirical studies, at the strategic and operational levels among different industrial sectors. Also, this study can help managers understand the integrations between Lean practices and I4.0 technologies to achieve better operational and environmental organizational results. Originality/value To the best of the knowledge, this study is the first of its kind using SLR to integrate Lean approaches, ES and I4.0 and to propose a unified framework to help managers and academics understand these relationships.

Graduation Intelligent Manufacturing System (GiMS): an Industry 4.0 paradigm for production and operations management

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daqiang Guo ◽  
Mingxing Li ◽  
Ray Zhong ◽  
G.Q. Huang
Keyword(s):  
Real Time ◽  
Production Planning ◽  
Operations Management ◽  
Industry 4.0 ◽  
Production Management ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Content Type ◽  
Intelligent Manufacturing System ◽  
And Control

PurposeThe purpose of this paper is to develop an intelligent manufacturing system for transforming production management and operations to an Industry 4.0 manufacturing paradigm.Design/methodology/approachA manufacturing mode-Graduation Manufacturing System is designed for organizing and controlling production operations. An Industrial Internet of Things (IIoT) and digital twin-enabled Graduation Intelligent Manufacturing System (GiMS) with real-time task allocation and execution mechanisms is proposed to achieve real-time information sharing and production planning, scheduling, execution and control with reduced complexity and uncertainty.FindingsThe implementation of GiMS in an industrial company illustrates the potential advantages for real-time production planning, scheduling, execution and control with reduced complexity and uncertainty. For production managers and onsite operators, effective tools, such as cloud services integrates effective production and operations management strategies are needed to facilitate their decision-making and daily operations at the operational level.Originality/valueThis paper presents an Industry 4.0 paradigm-GiMS, which aims to explore Industry 4.0 technologies opportunities on operations and production management, especially on production planning, scheduling, execution and control.

scholarly journals Connectivity as a Design Feature for Industry 4.0 Production Equipment: Application for the Development of an In-Line Metrology System

2021 ◽  
Vol 11 (3) ◽  
pp. 1312
Author(s):  
Ana Pamela Castro-Martin ◽  
Horacio Ahuett-Garza ◽  
Darío Guamán-Lozada ◽  
Maria F. Márquez-Alderete ◽  
Pedro D. Urbina Coronado ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Design Feature ◽  
Production Equipment ◽  
Smart Manufacturing ◽  
Process Data ◽  
Industrial Sectors ◽  
Advanced Manufacturing Technologies ◽  
Manufacturing Technologies ◽  
Equipment Application ◽  
The Impact

Industry 4.0 (I4.0) is built upon the capabilities of Internet of Things technologies that facilitate the recollection and processing of data. Originally conceived to improve the performance of manufacturing facilities, the field of application for I4.0 has expanded to reach most industrial sectors. To make the best use of the capabilities of I4.0, machine architectures and design paradigms have had to evolve. This is particularly important as the development of certain advanced manufacturing technologies has been passed from large companies to their subsidiaries and suppliers from around the world. This work discusses how design methodologies, such as those based on functional analysis, can incorporate new functions to enhance the architecture of machines. In particular, the article discusses how connectivity facilitates the development of smart manufacturing capabilities through the incorporation of I4.0 principles and resources that in turn improve the computing capacity available to machine controls and edge devices. These concepts are applied to the development of an in-line metrology station for automotive components. The impact on the design of the machine, particularly on the conception of the control, is analyzed. The resulting machine architecture allows for measurement of critical features of all parts as they are processed at the manufacturing floor, a critical operation in smart factories. Finally, this article discusses how the I4.0 infrastructure can be used to collect and process data to obtain useful information about the process.

scholarly journals Evaluation of a New Immunochromatography Technology Test (LDBio Diagnostics) To Detect Toxoplasma IgG and IgM: Comparison with the Routine Architect Technique

2017 ◽  
Vol 55 (12) ◽  
pp. 3395-3404 ◽  
Author(s):  
Caroline Mahinc ◽  
Pierre Flori ◽  
Edouard Delaunay ◽  
Cécile Guillerme ◽  
Sana Charaoui ◽  
...  
Keyword(s):  
Western Blot ◽  
Sensitivity And Specificity ◽  
Blot Analysis ◽  
False Positive ◽  
Automated System ◽  
University Hospitals ◽  
Content Type ◽  
Automated Screening ◽  
Commercial Kits ◽  
Fully Automated System

ABSTRACTA study comparing the ICT (immunochromatography technology)ToxoplasmaIgG and IgM rapid diagnostic test (LDBio Diagnostics, France) with a fully automated system, Architect, was performed on samples from university hospitals of Marseille and Saint-Etienne. A total of 767 prospective sera and 235 selected sera were collected. The panels were selected to test various IgG and IgM parameters. The reference technique,ToxoplasmaIgGII Western blot analysis (LDBio Diagnostics), was used to confirm the IgG results, and commercial kits Platelia Toxo IgM (Bio-Rad) and Toxo-ISAgA (bioMérieux) were used in Saint-Etienne and Marseille, respectively, as the IgM reference techniques. Sensitivity and specificity of the ICT and the Architect IgG assays were compared using a prospective panel. Sensitivity was 100% for the ICT test and 92.1% for Architect (cutoff at 1.6 IU/ml). The low-IgG-titer serum results confirmed that ICT sensitivity was superior to that of Architect. Specificity was 98.7% (ICT) and 99.8% (Architect IgG). The ICT test is also useful for detecting IgM without IgG and is both sensitive (100%) and specific (100%), as it can distinguish nonspecific IgM from specificToxoplasmaIgM. In comparison, IgM sensitivity and specificity on Architect are 96.1% and 99.6%, respectively (cutoff at 0.5 arbitrary units [AU]/ml). To conclude, this new test overcomes the limitations of automated screening techniques, which are not sensitive enough for IgG and lack specificity for IgM (rare IgM false-positive cases).

The impact of project methodologies on project success in different project environments

2016 ◽  
Vol 9 (2) ◽  
pp. 364-388 ◽  
Author(s):  
Robert Joslin ◽  
Ralf Müller
Keyword(s):  
Project Success ◽  
Research Model ◽  
Content Type ◽  
Industrial Sectors ◽  
Project Environment ◽  
Project Governance ◽  
The Impact ◽  
Matching Techniques ◽  
The Relationship ◽  
Practical Implications

Purpose – The purpose of this paper is to qualitatively validate the constructs of a theoretically derived research model while gaining insights to steer the direction of a greater study on methodologies, their elements, and their impact on project success. In doing so, to investigate whether different project environments, notably project governance, impacts the relationship between methodologies and project success. Design/methodology/approach – A deductive approach was applied to validate a theoretically derived research model. In total, 19 interviews across 11 industrial sectors and four countries were used to collect data. Pattern-matching techniques were utilized in the analysis to deductively validate the research model. Findings – There is a positive relationship between project methodology elements and the characteristics of project success; however, environmental factors, notably project governance, influence the use and effectiveness of a project methodology and its elements with a resulting impact on the characteristics of project success. Research limitations/implications – Project governance plays a major role in the moderating effect of a project methodology’s effectiveness. Contingency theory is applicable to a project’s methodology’s selection and its customization according to the project environment. Practical implications – Understand the impact of project methodologies and their elements on the characteristics of project success while being moderated by the project environment, for example, the risk of suboptimal project performance due to the effectiveness of methodology elements being negatively impacted by the project environment. Originality/value – The impact of a project methodology (collection of heterogeneous-related elements) on the characteristics of project success is identified while being moderated by the project environment, notably project governance.

Bulk and block holders herding behaviour

2018 ◽  
Vol 7 (2) ◽  
pp. 150-171
Author(s):  
Ganesh R. ◽  
Naresh Gopal ◽  
Thiyagarajan S.
Keyword(s):  
Economic Performance ◽  
Institutional Investors ◽  
Design Methodology ◽  
Indian Market ◽  
Foreign Investors ◽  
Content Type ◽  
Industrial Sectors ◽  
Block Data ◽  
Block Holders

Purpose The purpose of this paper is to examine industry herding among the institutional investors and to find whether their herding behaviour is intentional or unintentional. Design/methodology/approach The study uses Lakonishok et al. (1992) model to examine the presence of industry herding behaviour among institutional investors. To determine whether the herding observed is intentional or unintentional, herding measure is regressed with volatility, volume, beta and return. The period of the study is from 1 April 2005-31 March 2015. Findings The findings of the study showed that though institutional investors have herding tendency towards most of the industries, in the overall period industry herding was not significant. The herding found in some industrial sectors was linked to economic performance of those sectors in India during the period of study and hence the herding was unintentional in nature. Research limitations/implications This is the first attempt to study industry herding among institutional investors and their intent in Indian market ever since the country opened its market to foreign investors in a big way. Present study is limited to the use of only bulk/block data instead of the entire trading data for the period. Originality/value This study is the first attempt to investigate industry herding behaviour of institutional investors in the market using their bulk and block trading data. The herding observed in well performing industries has been shown to be unintentional and hence rational. The results indicate that the entry of big institutional investors, including foreign institutions into the Indian market has not destabilised the market by irrational herding.

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