scholarly journals Analysis and Evaluation of Indian Industrial System Requirements and Barriers Affect During Implementation of Industry 4.0 Technologies

2021 ◽  
Author(s):  
ABINASH JENA ◽  
Saroj Kumar Patel
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Research Work ◽  
Global Market ◽  
Manufacturing Industries ◽  
Industrial System ◽  
Data Set ◽  
Term Survival ◽  
Automatic Data ◽  
System Requirements

Abstract In recent years, competition among the Indian Manufacturing Industries (IMI) has increased enormously in the global market. The current uncertainty in the market context is characterised and governed by the customised requirements of the customers. Thus, the manufacturing system in the industries should be capable of adapting the parameters like flexibility in scalability, variety, agility, system responsiveness, inter-connectivity, automatic data exchange with communication among the manufacturing systems, transparency and human-machine interaction, which are the main components and principles of Industry 4.0 (I4.0). Thus, adopting I4.0 plays a vital role to corroborate and its long-term survival in the global marketplace. However, very few research work considerations contribute to the issues induced during the adoption of I4.0 in manufacturing industries. This paper aims to minimise the gap between the existing Industrial System Requirements (ISR) and the challenges faced during the implementation of I4.0 technologies in existing Industries. The identified ISR and barriers were evaluated and analysed based on the data set collected from a questionnaire-based survey. Fuzzy multi-criteria analysis is conducted to identify the most weighted SR and barriers and ranked them concerning their importance. Furthermore, the inter-item correlation between both of them is analysed. This research work offers the researchers, practitioners, and industrialists an opportunity to formulate MCDM problems through numerous case studies, prioritising the top barriers and system requirements and the inter-relationship shared between them.

scholarly journals Redistributed manufacturing system under uncertain evaluation using multi criteria decision making

2021 ◽  
Vol 12 (3) ◽  
pp. 3895-3908
Author(s):  
Ponugupati Narendra Mohan Et.al
Keyword(s):  
Decision Making ◽  
Research Work ◽  
Dynamic Programming Algorithm ◽  
Big Data Analytics ◽  
Global Market ◽  
Programming Algorithm ◽  
Multi Criteria Decision Making ◽  
Firm Level ◽  
Data Set ◽  
Value Analysis

Man In recent day’s occurrence of a global crisis in Environmental (Emission of pollutants) and in Health (Pandemic COVID-19) created a recession in all sectors. The innovations in technology lead to heavy competition in global market forcing to develop new variants especially in the automobile sector. This creates more turbulence in demand at the production of new models, maintenance of existing models that are obsolete while implementation of Bharat Standard automobile regulatory authority BS-VI of India. In this research work developed a novel model of value analysis is integrated by multi-objective function with multi-criteria decision-making analysis by incorporating the big data analytics with green supply chain management to bridge the gap in demand to an Indian manufacturing sector using a firm-level data set using matrix chain multiplication dynamic programming algorithm and the computational results illustrates that the algorithm proposed is effective.

The Application of the Positive Semi-Definite Kernel Space for SVM in Quality Prediction

2020 ◽  
Vol 13 (2) ◽  
pp. 228-233
Author(s):  
Wang Meng ◽  
Dui Hongyan ◽  
Zhou Shiyuan ◽  
Dong Zhankui ◽  
Wu Zige
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Industrial Revolution ◽  
Feature Space ◽  
Mixed Data ◽  
Smart Manufacturing ◽  
Additive Constant ◽  
Kernel Space ◽  
Data Set ◽  
Low Dimensional

Background: A transformation toward 4th Generation Industrial Revolution (Industry 4.0) is being led by Germany based on Cyber-Physical System-enabled manufacturing and service innovation. Smart manufacturing is an important feature of Industry 4.0 which uses the networked manufacturing systems for smart production. Current manufacturing systems (5M1E systems) require deeper mining of the data which is generated from manufacturing process. Objective: To map low-dimensional embedding into the input space would meet the requirement of “kernel trick” to solve a problem in feature space. On the other hand, the distance can be calculated more precisely. Methods: In this research, we proposed a positive semi-definite kernel space by using a constant additive method based on a kernel view of ISOMAP. There were 6 steps in the algorithm. Results: The classification precision of KMLSVM was better than SVM in the enterprise data set, in which SVM selected the RBF kernel and optimized its parameters. Conclusion: We adopted the additive constant method in kernel space construction and the positive semi-definite kernel was built. The typical mixed data set of an enterprise was used in simulation. We compared the SVM and KMLSVM in this data set and optimized the SVM kernel function parameters. The simulation results demonstrated the KMLSVM was a better algorithm in mix type data set than SVM.

Analysis and synthesis of Industry 4.0 research landscape

2019 ◽  
Vol 31 (1) ◽  
pp. 31-51 ◽  
Author(s):  
Aniruddha Anil Wagire ◽  
A.P.S. Rathore ◽  
Rakesh Jain
Keyword(s):  
Industry 4.0 ◽  
English Language ◽  
Semantic Analysis ◽  
Research Work ◽  
Academic Community ◽  
Future Research ◽  
Data Set ◽  
Content Type ◽  
Research Areas ◽  
Research Themes

PurposeIn 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/approachA 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.FindingsLSA 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/implicationsThe 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/valueTo 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.

A Method for Performing Forging Operation: A Perspective of Industry 4.0

2021 ◽  
Vol 14 ◽  
Author(s):  
Bhaveshkumar N. Pasi ◽  
Subhash K. Mahajan ◽  
Santosh B. Rane
Keyword(s):  
Industry 4.0 ◽  
Large Scale ◽  
Research Work ◽  
Rejection Rate ◽  
Lower Number ◽  
Manufacturing Industries ◽  
Working Environment ◽  
Cold Forging ◽  
Future Research ◽  
Energy Consumptions

Background: Cold forging operation is done on small as well as large scale in manufacturing industries. These industries are facing problems such as higher rejection rate of the final product, low productivity, the high number of accidents during production, etc. Objective: The purpose of this research work is to develop a Voice-Assisted Forging System (VAFS) with a lower rejection rate, higher productivity, and lower number of accidents during production. Methods: Based on recently published journals and patents, traditional and automatic forging operations, Industry 4.0, and voice assisted systems are reviewed and VAFS is designed and developed. Then, trial is taken on VAFS to investigate its performance. Finally, limitations and future research of the VAFS is proposed. Results : It is found that after implementation of the VAFS the average rejection count is reduced by 90.3 percentage, production rate is increased by 71.2 percentage, and process accuracy is increased from 92.75 percentage to 99.30 percentage. Also, number of accidents are reduced to zero. In comparison with the manual forging operation, the VAFS occupies less space, and it is easy to operate. Conclusion: This system will help the workers as well as the owner of industries to create a better man and machine relationship and to have a human-friendly working environment. VAFS reduces exhaustion and hassle of employees, components rejection, and energy consumptions in the production line.

scholarly journals Cyber-physical manufacturing systems: An architecture for sensor integration, production line simulation and cloud services

ACTA IMEKO ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 39
Author(s):  
Mariorosario Prist ◽  
Andrea Monteriù ◽  
Emanuele Pallotta ◽  
Paolo Cicconi ◽  
Alessandro Freddi ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Production Line ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Research Work ◽  
Cloud Services ◽  
Production Lines ◽  
Modular Software

The pillars of Industry 4.0 require the integration of a modern smart factory, data storage in the Cloud, access to the Cloud for data analytics, and information sharing at the software level for simulation and hardware-in-the-loop (HIL) capabilities. The resulting cyber-physical system (CPS) is often termed the cyber-physical manufacturing system, and it has become crucial to cope with this increased system complexity and to attain the desired performances. However, since a great number of old production systems are based on monolithic architectures with limited external communication ports and reduced local computational capabilities, it is difficult to ensure such production lines are compliant with the Industry 4.0 pillars. A wireless sensor network is one solution for the smart connection of a production line to a CPS elaborating data through cloud computing. The scope of this research work lies in developing a modular software architecture based on the open service gateway initiative framework, which is able to seamlessly integrate both hardware and software wireless sensors, send data into the Cloud for further data analysis and enable both HIL and cloud computing capabilities. The CPS architecture was initially tested using HIL tools before it was deployed within a real manufacturing line for data collection and analysis over a period of two months.

Development of innovation ecosystem framework for successful adoption of industry 4.0 enabling technologies in Indian manufacturing industries

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bhaveshkumar Nandanram Pasi ◽  
Subhash K. Mahajan ◽  
Santosh B. Rane
Keyword(s):  
Industry 4.0 ◽  
Research Work ◽  
Literature Survey ◽  
Manufacturing Industries ◽  
Research Approach ◽  
Innovation Ecosystem ◽  
Content Type ◽  
Enabling Technologies ◽  
Essential Components ◽  
The Government

Purpose The purpose of this paper is to develop an industry 4.0 (I4.0) innovation ecosystem framework by exploring the essential components of the same to ensure the collaborative efforts of different stakeholders. Design/methodology/approach In this research work, important perspectives and their sub-components for the I4.0 innovation ecosystem framework are identified by performing a systematic literature survey of peer-reviewed journal articles. Then, I4.0 challenges among higher education (HE) institutions students and industries in India are explored by adopting the questionnaire-based research approach. Finally, the importance of the identified perspectives and their sub-components and causal relations among components are analyzed by using the decision-making trial and evaluation laboratory method. Findings From the literature survey, three perspectives and their 45 sub-components are identified for the I4.0 innovation ecosystem framework. The outcomes show that the industry has a direct impact on HE institutions and the government. While HE institutions are most influenced by the industry and government. Research limitations/implications I4.0 innovation ecosystem framework is developed by analyzing responses received through questionnaires. There are other methods also available for ecosystem framework development, which are beyond this study. Practical implications This research work will facilitate policy formulation by the government. It will also help the managers to develop strategies for the adoption of I4.0 enabling technologies in their business. Originality/value This research study gives an idea about the innovation ecosystem framework for the successful adoption of I4.0 enabling technologies in Indian Manufacturing Industries.

ANN-Based Relaying Algorithm for Protection of SVC- Compensated AC Transmission Line and Criticality Analysis of a Digital Relay

2020 ◽  
Vol 13 (3) ◽  
pp. 381-393
Author(s):  
Farhana Fayaz ◽  
Gobind Lal Pahuja
Keyword(s):  
Transmission Line ◽  
Failure Modes ◽  
Reactive Power ◽  
Circuit Breaker ◽  
Research Work ◽  
Back Propagation ◽  
Static Var Compensator ◽  
Data Set ◽  
Ac Transmission ◽  
Criticality Analysis

Background:The Static VAR Compensator (SVC) has the capability of improving reliability, operation and control of the transmission system thereby improving the dynamic performance of power system. SVC is a widely used shunt FACTS device, which is an important tool for the reactive power compensation in high voltage AC transmission systems. The transmission lines compensated with the SVC may experience faults and hence need a protection system against the damage caused by these faults as well as provide the uninterrupted supply of power.Methods:The research work reported in the paper is a successful attempt to reduce the time to detect faults on a SVC-compensated transmission line to less than quarter of a cycle. The relay algorithm involves two ANNs, one for detection and the other for classification of faults, including the identification of the faulted phase/phases. RMS (Root Mean Square) values of line voltages and ratios of sequence components of line currents are used as inputs to the ANNs. Extensive training and testing of the two ANNs have been carried out using the data generated by simulating an SVC-compensated transmission line in PSCAD at a signal sampling frequency of 1 kHz. Back-propagation method has been used for the training and testing. Also the criticality analysis of the existing relay and the modified relay has been done using three fault tree importance measures i.e., Fussell-Vesely (FV) Importance, Risk Achievement Worth (RAW) and Risk Reduction Worth (RRW).Results:It is found that the relay detects any type of fault occurring anywhere on the line with 100% accuracy within a short time of 4 ms. It also classifies the type of the fault and indicates the faulted phase or phases, as the case may be, with 100% accuracy within 15 ms, that is well before a circuit breaker can clear the fault. As demonstrated, fault detection and classification by the use of ANNs is reliable and accurate when a large data set is available for training. The results from the criticality analysis show that the criticality ranking varies in both the designs (existing relay and the existing modified relay) and the ranking of the improved measurement system in the modified relay changes from 2 to 4.Conclusion:A relaying algorithm is proposed for the protection of transmission line compensated with Static Var Compensator (SVC) and criticality ranking of different failure modes of a digital relay is carried out. The proposed scheme has significant advantages over more traditional relaying algorithms. It is suitable for high resistance faults and is not affected by the inception angle nor by the location of fault.

scholarly journals Outlier Detection Transilience-Probabilistic Model for Wind Tunnels Based on Sensor Data

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2532
Author(s):  
Encarna Quesada ◽  
Juan J. Cuadrado-Gallego ◽  
Miguel Ángel Patricio ◽  
Luis Usero
Keyword(s):  
Anomaly Detection ◽  
Outlier Detection ◽  
Research Work ◽  
Industrial Sector ◽  
Sensor Data ◽  
Correct Selection ◽  
Wind Tunnels ◽  
Data Set ◽  
First Case ◽  
Anomaly Analysis

Anomaly Detection research is focused on the development and application of methods that allow for the identification of data that are different enough—compared with the rest of the data set that is being analyzed—and considered anomalies (or, as they are more commonly called, outliers). These values mainly originate from two sources: they may be errors introduced during the collection or handling of the data, or they can be correct, but very different from the rest of the values. It is essential to correctly identify each type as, in the first case, they must be removed from the data set but, in the second case, they must be carefully analyzed and taken into account. The correct selection and use of the model to be applied to a specific problem is fundamental for the success of the anomaly detection study and, in many cases, the use of only one model cannot provide sufficient results, which can be only reached by using a mixture model resulting from the integration of existing and/or ad hoc-developed models. This is the kind of model that is developed and applied to solve the problem presented in this paper. This study deals with the definition and application of an anomaly detection model that combines statistical models and a new method defined by the authors, the Local Transilience Outlier Identification Method, in order to improve the identification of outliers in the sensor-obtained values of variables that affect the operations of wind tunnels. The correct detection of outliers for the variables involved in wind tunnel operations is very important for the industrial ventilation systems industry, especially for vertical wind tunnels, which are used as training facilities for indoor skydiving, as the incorrect performance of such devices may put human lives at risk. In consequence, the use of the presented model for outlier detection may have a high impact in this industrial sector. In this research work, a proof-of-concept is carried out using data from a real installation, in order to test the proposed anomaly analysis method and its application to control the correct performance of wind tunnels.

scholarly journals Open Source Control Device for Industry 4.0 Based on RAMI 4.0

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 869
Author(s):  
Pablo F. S. Melo ◽  
Eduardo P. Godoy ◽  
Paolo Ferrari ◽  
Emiliano Sisinni
Keyword(s):  
Open Source ◽  
Industry 4.0 ◽  
Product Life Cycle ◽  
Manufacturing Systems ◽  
Industrial Revolution ◽  
Control Device ◽  
Source Control ◽  
Reference Architecture ◽  
Architecture Model ◽  
Complex Relationships

The technical innovation of the fourth industrial revolution (Industry 4.0—I4.0) is based on the following respective conditions: horizontal and vertical integration of manufacturing systems, decentralization of computing resources and continuous digital engineering throughout the product life cycle. The reference architecture model for Industry 4.0 (RAMI 4.0) is a common model for systematizing, structuring and mapping the complex relationships and functionalities required in I4.0 applications. Despite its adoption in I4.0 projects, RAMI 4.0 is an abstract model, not an implementation guide, which hinders its current adoption and full deployment. As a result, many papers have recently studied the interactions required among the elements distributed along the three axes of RAMI 4.0 to develop a solution compatible with the model. This paper investigates RAMI 4.0 and describes our proposal for the development of an open-source control device for I4.0 applications. The control device is one of the elements in the hierarchy-level axis of RAMI 4.0. Its main contribution is the integration of open-source solutions of hardware, software, communication and programming, covering the relationships among three layers of RAMI 4.0 (assets, integration and communication). The implementation of a proof of concept of the control device is discussed. Experiments in an I4.0 scenario were used to validate the operation of the control device and demonstrated its effectiveness and robustness without interruption, failure or communication problems during the experiments.

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