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Blockchain and Internet of Things (IoT) technologies have recently gained much attention for Industry 4.0. With the emergence of disruptive technologies, it has become essential to redesign the business for innovations based on blockchain–IoT integrated architecture that helps organizations to improve agility in their operations. The paper aims to discuss this issue.

An industrial pump was Sensorized and IoTized to monitor its operations on real time and take predictive measures for managing these assets with more agility. The developed architecture was further extended for proposing the use of blockchain and how it can benefit the organization.

The known features of blockchain such as increasing the capacity of decentralization, trust-less transactions, security and allowing autonomous coordination of the devices along with the boons of IoT will help achieve the motto of improving agility in Industry 4.0.

This paper gives a new dimension to utilization of blockchain technology. blockchain along with IoT that gives a way forward for industries like manufacturing, oil and gas, engineering and construction, utilities, etc. to re-designing the business organization in a more agile way.

This paper aims to concentrate on classifying and analyzing the risks associated with the Industry 4.0 (I4.0) concept in manufacturing industries and developing strategies for managing risks.

In this research paper, risks categories and their sub-components associated with the I4.0 concept are identified by performing a systematic literature survey of peer-reviewed journal articles and taking inputs from industry experts and academicians. Then, the importance of the identified risks and causal relations among risks are analyzed by using decision-making trial and evaluation laboratory (DEMATEL) method. Finally, the strategies are developed to mitigate the identified risks.

From the literature survey, 6 risk categories and their 19 sub-components associated with the I4.0 concept are identified. The DEMATEL method resulted in economic risks and technical risks as the top two risk categories in the I4.0 concept. Ecological risks and legal and political risks are relatively low-ranked risk categories.

Causal relations and ranking among risk categories and their sub-components are obtained by analyzing responses received through questionnaires. There are other methods also available for risk analysis, which are beyond this study.

This research paper will help the industrialists to effectively manage the risks involved in adopting I4.0 concept in manufacturing industries by adopting strategies.

This research paper gives an idea about risks associated with the implementation of the I4.0 concept in manufacturing industries. Also, this paper uses the DEMATEL method for ranking the identified risk categories and their sub-components.

This article aims at - exploring and prioritizing the barriers to adoption of digitization in supply chains (SCs), categorizing them into sustainability triple bottom line (STBL) based upon their direct impact and suggesting digital technologies to address each barrier.

A five-phase methodology is used which consists of an exploration of 44 barriers to the adoption of digitization in SCs, analysis of 44 barriers for mean, standard deviation and Cronbach alpha based on questionnaire-based feedback of 25 experts, extraction of 10 most significant barriers through 05 experts, followed by categorization of the barriers into STBL referring to their direct impact on STBL, prioritization of ten barriers using Fuzzy Technique for Order Performance by Similarity to Ideal Solution and recommendation of digital technologies to address each barrier.

While all the barriers considered in this study significantly impede the adoption of digitization in SCs, lack of top management commitment (B1) is found to be most crucial while lack of culture toward use of information and communication technology required for digitization (B3) has minimum impact. Large investment in digital infrastructure (B6), difficulty in integration of cyber physical systems (CPSs) on varied platforms (B8) and lack of experts having knowledge of digital technologies (B2) are equally important barriers requiring more attention while adopting digitization in SCs.

This study is mainly based on feedback from 25 seasoned experts; a wider cross section of experts will give more insight.

The outcomes are very significant for organizations looking to adopt digitization in their SCs. Simultaneous consideration to all the barriers becomes impractical hence prioritization of same will be useful for the SC managers to benchmark their preparedness and decide strategies for the adoption of digitization with due consideration toward the impact of barriers on STBL. The digital technologies recommended will further aid in planning the digital strategies to address each barrier.

A unique approach to explore, analyze, prioritize and categorize the barriers to adoption of digitization in SCs is used to provide a deeper understanding of factors deterring the same. It implies that a supportive top management along with systematic allocation of finances plays a crucial role. The importance of availability of digital experts for integrating CPSs on a single platform is also highlighted. The digital technologies recommended will further assist the organizations toward adoption of digitization in SCs with due consideration to STBL.

Project risk management (PRM) and human resource management (HRM) are the two critical success factors (CSFs) for international project management. This paper aims to correlate these two CSFs, identify the human resource (HR) barriers, develop a hybrid model for risk management and develop strategies to overcome the HR barriers to effective risk management in international projects.

In total, 20 key HR barriers have been identified through a literature survey and verified by project professionals. These HR barriers are ranked according to their ability to trigger other barriers by analysing their interactions using the decision-making trial and evaluation laboratory (DEMATEL) method. Based on Ulrich’s revised model for HR functions, a hybrid framework for international PRM has been proposed.

DEMATEL analysis categorized nine barriers as cause barriers and 11 as affected barriers. The “PROJECTS” model proposed for HR strategy development suggests eight strategies to overcome these nine cause barriers. The hybrid PRM framework developed includes the effect of the HR dimension.

This paper presents the generalized prioritization of HR barriers to international PRM. For a specific international project, the HR barriers and their prioritization may change slightly. The hybrid framework for PRM and the strategy development model suggested are yet to be validated.

Correlating two CSFs in international project management, i.e. HRM and PRM and ranking the HR barriers using the DEMATEL method is the uniqueness of this research paper. The hybrid framework developed for PRM based on HR functions in Ulrich’s revised model and the proposed new HR strategy development model “PROJECTS” are unique contributions of this paper.

The purpose of this paper is to review the risk categories which are predominant in international projects and to rank them according to their effect on project success.

A literature survey of peer-reviewed journal articles, survey reports and books on project management is used as the research methodology. One among the various multi-criteria decision making methods named as Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) has been used to rank the risk categories according to their importance. The data for TOPSIS were collected through questionnaire as the research instrument.

The findings derived from evaluation of the publications led to the identification of eight different types of risk categories associated with international projects. The TOPSIS method resulted into political risks, technical risks and design-related risks as the top three risk categories in international projects. Contractual and legal risks and fraudulent practices-related risks are relatively low-ranked risk category.

The findings will be useful in successful implementation of international projects as the knowledge of risk categories and their ranking will help project manager to plan the risk response strategies. A larger sample size for decision makers and more variety of projects can give more exhaustive risk categories and their ranking.

This paper explores eight different risk categories in international projects. It represents the ranking of risk categories according to their importance in project success. This will be helpful to project managers for developing a general framework for planning the appropriate risk response strategies.

Governments of many countries around the world are encouraging their industries to undertake and successfully complete projects in foreign countries. However, many industries experience failure in projects as they fail to implement the risk management (RM) effectively in international projects. This research work provides the risk categories in international projects and their ranking which can assist in developing strategies to respond the risk appropriately.

This paper uses the TOPSIS method for ranking major types of risk categories in international projects. It might represent new opportunities for rigorous and relevant research that would contribute to an in-depth knowledge of RM methodologies.

The purpose of this paper is to develop a green supplier development (GSD) process model and validate the model with a case study in Indian automobile industry.

A literature survey of peer-reviewed journal articles, survey reports and paradigmatic books with managerial impact is done for the research. The process of GSD is modeled using stage-gate approach and KPIV and KPOV of the process are determined. The process model is implemented in an Indian automobile components manufacturing industry for validation.

The industry implemented the model with ten suppliers and was able to successfully convert seven of them into Green suppliers. Remaining three suppliers were asked to repeat the process again or terminate the contracts. Model implementation took around three years starting from planning of resources and finances to actual development of suppliers.

The model implementation was done with a small automobile industry and hence the validation and implications may be generalized by taking the case study further in different industries. It would be beneficial to test the model with case studies of large-scale industries.

The process model for implementing GSD activities will help managers in taking complex investment decisions. The stages and process inputs and outputs are clearly defined which helps the managers to successfully develop the suppliers.

This paper puts forward the process model that should be implemented for the successful development of green suppliers. It might represent new opportunities for rigorous and relevant research in the area of green supply chain.

Successful device development brings substantial revenues to medical device manufacturing industries. This paper aims to evaluate factors contributing to the success of medical device development (MDD) using grey DEMATEL (decision-making trial and evaluation laboratory) methodology through an empirical case study.

The factors are identified through literature review and industry experts’ opinions. Grey-based DEMATEL methodology is used to establish the cause-effect relationship among the factors and develop a structured model. Most significant factors contributing to the success of MDD are identified. An empirical case study of an MDD and manufacturing organisation is presented to demonstrate the use of the grey DEMATEL method. Sensitivity analysis is carried out to check robustness of results.

The results of applying the grey DEMATEL methodology to evaluate success factors of MDD show that availability of experts and their experience (SF4) is the most prominent cause factor, and active involvement of stakeholders during all stages of MDD (SF3) and complete elicitation of end-user requirements (SF1) are the most prominent effect factors for successful MDD. A sensitivity analysis confirms the reliability of the initial solution.

The findings will greatly help medical device manufacturers to understand the success factors and develop strategies to conduct successful MDD processes.

In the past, few success factors to MDD have been identified by some researchers, but complex inter-relationships among factors are not analysed. Finding direct and indirect effects of these factors on the success of MDD can be a good future research proposition.

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.

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.

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.

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.

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.

This research study gives an idea about the innovation ecosystem framework for the successful adoption of I4.0 enabling technologies in Indian Manufacturing Industries.

The purpose of this technical paper is to explore the application of analytics and Six Sigma in the manufacturing processes for iron foundries. This study aims to establish a causal relationship between chemical composition and the quality of the iron casting to achieve the global benchmark quality level.

The case study-based exploratory research design is used in this study. The problem discovery is done through the literature survey and Delphi method-based expert opinions. The prediction model is built and deployed in 11 cases to validate the research hypothesis. The analytics helps in achieving the statistically significant business goals. The design includes Six Sigma DMAIC (Define – Measure – Analyze – Improve and Control) approach, benchmarking, historical data analysis, literature survey and experiments for the data collection. The data analysis is done through stratification and process capability analysis. The logistic regression-based analytics helps in prediction model building and simulations.

The application of prediction model helped in quick root cause analysis and reduction of rejection by over 99 per cent saving over INR6.6m per year. This has also enhanced the reliability of the production line and supply chain with on-time delivery of 99.78 per cent, which earlier was 80 per cent. The analytics with Six Sigma DMAIC approach can quickly and easily be applied in manufacturing domain as well.

The limitation of the present analytics model is that it provides the point estimates. The model can further be enhanced incorporating range estimates through Monte Carlo simulation.

The increasing use of prediction model in the near future is likely to enhance predictability and efficiencies of the various manufacturing process with sensors and Internet of Things.

The researchers have used design of experiments, artificial neural network and the technical simulations to optimise either chemical composition or mould properties or melt shop parameters. However, this work is based on comprehensive historical data-based analytics. It considers multiple human and temporal factors, sand and mould properties and melt shop parameters along with their relative weight, which is unique. The prediction model is useful to the practitioners for parameter simulation and quality enhancements. The researchers can use similar analytics models with structured Six Sigma DMAIC approach in other manufacturing processes for the simulation and optimisations.

The purpose of this paper is to present an analysis of research on lean focusing on barriers in its implementation through a systematic literature survey.

A literature survey of peer-reviewed journal articles, survey reports, master theses, doctoral theses and paradigmatic books with managerial impact is used as the research methodology.

The findings derived from the evaluation of the publications analyzed have led to the identification of 24 lean barriers. The success of lean implementation will not be entirely based on application of appropriate tools and techniques alone but also on the top managements' involvement and leadership, workers' attitude, resources and the organizational culture.

This literature survey is primarily focused on lean implementation in the manufacturing sector.

This paper explores barriers for successful lean implementation and provides a concise description of the barriers that will be helpful for further studies in the domain of lean manufacturing.

Government of many countries around the world is encouraging and helping small- and medium-scale industries to understand and implement lean systems by preparing accessible database of lean consultants, providing financial assistance for training by professionals and establishing professional associations. However, many industries experienced failure in lean implementation. This research work provides a launching pad to develop a strategy to tackle barriers for successful lean implementation.

This paper puts forward the key barriers that should be tackled for successful lean implementation. It might represent new opportunities for rigorous and relevant research that would contribute to more translucent knowledge of lean being gained.