Green Lean Six Sigma Sustainability Oriented Project Selection and Implementation Framework for Manufacturing Industry

Green Lean Six Sigma (GLS) project selection has been done based on the six sustainability-oriented criteria formed from seventeen sub-criteria (found from the literature and developed by authors).The weights of the criteria have been determined through the entropy method. The projects have been ranked based on the criteria through the advanced decision-making approach: Grey relation analysis (GRA). The results of the study were validated using best worst method (BWM) and sensitivity analysis. Purpose: The present study deals with the selection of the sustainability-oriented GLS project for the manufacturing industry in the complex decision-making environment. Moreover, the study also proposes a GLS implementation framework for improved organizational performance. It has been found that the productivity-related criterion is the most significant among other criteria with entropy weight of 0.2721. GRA has been used in this research work to rank the potential GLS projects in a manufacturing industry based on six sustainability criteria, to select a project that exhibits the maximum potential for sustainable improvement. The machine shop has been found as the most significant GLS project with grey relation grade of 0.4742. Originality: With increased globalized competition in recent times, new projects are being considered as the foundation stone for organizational success. The decision making becomes quite complex to select an effective project due to the intriguing nature of various criteria, subcriteria, and different aspects of sustainability. The present study is the first of its kind that provides ways for the selection of sustainability-oriented GLS projects.The present study facilitates practitioners and industrial managers to implement an inclusive GLS approach for improved sustainability dynamics through effective GLS project selection and implementation framework

Systematic review of Industry 5.0 from main aspects to the execution status

Purpose: The main aim of this study is to review different aspects of Industry 5.0 (I5.0) to foster this novel aspect of industrial sustainability. The study makes a comprehensive study to explore the implementation status of I5.0 in industries, key technologies, adoption level in different nations, barriers to I5.0 adoption together with mitigation actions. Methodology: To do a systematic study of the literature authors have used preferred reporting items for systematic reviews and meta-analysis (PRISMA) methodology to extract articles related to the field of the study. Findings: It has been found that academic literature on the I5.0 is continuously growing as the wheel of time is running. Most of the studies on I5.0 are conceptual-based, and manufacturing and medical industries are the flag bearer in the adoption of this novel aspect. Further, due to I5.0's infancy, many organizations face difficulty to adopt the same due to financial burden, resistive nature, a well-designed standard for cyber-physical systems, and an effective mechanism for human-robot collaboration. Further study also provides avenues for future research in terms of the identification of collaborative mechanisms between machines and wells, the establishment of different standards for comparison, development of I5.0-enabled models for different industrial domains. The study also provides concrete measures for mapping the I5.0 technologies with Sustainable development goals (SDGs). Originality: The study is of the first kind that reviews different facets of I5.0in conjunction with Kazien’s measures along with application areas and provides avenues for future research to improve an organization's environmental and social sustainability

COVID-19 pandemic and psychological wellbeing among health care workers and general population: A systematic-review and meta-analysis of the current evidence from India

IntroductionCoronavirus disease 2019 (COVID-19) was declared as pandemic and measures adopted for its control included quarantine of at-risk, isolation of infected along with other measures such as lockdown, restrictions on movement, and social interactions. Both the pandemic and these measures have the potential to cause mental health problems among individuals.ObjectiveThe present study aimed to investigate and estimate the prevalence of psychological well-being, particularly from an Indian perspective using systematic review and meta-analysis of existing literature.MethodsWe searched in the PubMed database, starting from the onset of the current pandemic and until 10th October 2020 to synthesize evidence on mental health outcomes from India. DerSimonian and Laird method of the random-effects meta-analysis was employed and heterogeneity between studies was assessed using the Chi-square based Cochran's Q statistic and I-squared (I2) statistics.ResultsThe pooled prevalence of stress in nine studies was 60.7% (95% CI: 42.3%–77.7%), depression in eight studies was 32.7% (95% CI: 24.6%–41.3%), anxiety in six studies was 34.1% (95% CI: 26.3%–42.3%) and sleep disturbances in six studies was 26.7% (95% CI: 13.9%–41.8%). As expected, high heterogeneity was observed in the above-mentioned outcomes. Sub-group analysis showed that Health Care Workers (HCWs) had a higher prevalence of stress, anxiety, depression & psychological distress in comparison to the general population.ConclusionA significant impact on psychological well-being during COVID-19 was observed in India as common adverse outcomes were stress (61%), psychological distress (43%), anxiety (34%), depression (33%), and sleep disturbances (27%). Thus the COVID-19 pandemic represents an unprecedented threat to mental health, which should become a priority for public health strategies

Integrating Green Lean Six Sigma and Industry 4.0: A Conceptual Framework

This research aims to propose a framework to integrate Green Lean Six Sigma (GLSS) and Industry 4.0 to improve organizational sustainability. The integration of GLSS and Industry 4.0 is proposed based on theoretical facets of the individual approaches. A generic, conceptual framework of an integrated GLSS-Industry 4.0 approach is then proposed using the application of different tools and techniques of GLSS and Industry 4.0 at different stages of the realization of a project. Both approaches have common facets related to enablers and barriers, and the integrated application of tools and techniques of each approach supplements the common focus of both related to sustainability enhancement. The proposed, conceptual framework provides systematic guidelines from the project selection stage to the sustainment of the solution, with the enumerated application of different techniques and tools at each step of the framework. This research is the first of its kind to propose the integration of GLSS and Industry 4.0 under the umbrella of a unified approach, including a conceptual framework of this integrated GLSS-Industry 4.0 approac

Green Lean Six Sigma for sustainability improvement: a systematic review and future research agenda

Design/ Methodology/ Approach: To do a systematic analysis of the literature, a systematic literature review methodology has been used in this research work. 140 articles from the reputed databases were identified to explore hidden aspects of GLSS. Exploration of articles in different continents, year-wise, approach-wise, and journal-wise, were also done to find the execution status of GLSS. Purpose: The main purpose of this article is to explore different aspects of the Green Lean Six Sigma approach, application status, and potential benefits from a comprehensive review of the literature and provides an avenue for future research work. The study also provides a conceptual framework for GLSS. Findings: The study depicts that GLSS implementation is increasing year by year, and it leads to considerable improvement in all dimensions of sustainability. Enablers, barriers, tools, and potential benefits that foster the execution of GLSS in industrial organizations are also identified based on a systematic review of the literature. Originality: The study's uniqueness lies in that study is the first of its kind that depicts the execution status of GLSS, and its different facets, explores different available frameworks and provides avenues for potential research in this area for potential researchers and practitioners

Integrated Green Lean Six Sigma-Industry 4.0 approach to combat COVID-19: from literature review to framework development

Purpose: The Coronavirus (COVID-19) pandemic has led to a surge in demand for healthcare facilities, medicines, vaccines, and other healthcare items. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of healthcare units and also leads to improving the quality of inpatient care with better safety, hygiene, and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas, and potential benefits for the adoption of an integrated GLSS-I4.0 approach within healthcare facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS- I4.0 has been proposed for better COVID management. Methodology: To conduct literature, authors used Preferred reporting items for systematic reviews and meta-analysis (PRISMA) and covers relevant articles from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS- I 4.0 approach and through insights of experts (academicians, and healthcare personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention, and cure. Findings: The systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID healthcare management. In this study, the proposed framework reveals that IOT (Internet of Things), Big Data, and Artificial Intelligence (AI) are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management right from diagnosis, manufacture of items, inpatient and outpatient care of the affected person. Implications: This study provides a significant knowledge database to the practitioners by understanding different tools and techniques of integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge-based in medical areas and provides different novel prospects to combat other medical urgencies

Exploration and Mitigation of Green Lean Six Sigma Barriers: A Higher Education Institutions perspective

Purpose-The study aims to identify Green Lean Six Sigma (GLSS) barriers in the context of Higher Education Institutions (HEIs) and prioritize them for executing the GLSS approach. Design/methodology/approach-A systematic literature review (SLR) was used to identify a total of fourteen barriers, which were then verified for greater relevance by the professional judgments of industrial personnel. Moreover, many removal measures strategies are also recommended in this study. Furthermore, this work also utilizes Gray Relational Analysis (GRA) to prioritize the identified GLSS barriers. Findings-The study reveals that Training and education, continuous assessment of SDG, organizational culture, resources and skills to facilitate implementation, and assessment of satisfaction and welfare of the employee are the most significant barriers to implementing this approach. Research limitations/implications-The present study provides an impetus for practitioners and managers to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers. In this case, the outcomes of this research, and in particular the GRA technique presented by this work, can be used by managers and professionals to rank the GLSS barriers and take appropriate action to eliminate them. Practical implications-The ranking of GLSS barriers gives top officials of higher education institutes a very clear view to effectively and efficiently implementing GLSS initiatives. The outcomes also show training and education, sustainable development goals, and organizational culture as critical barriers. The findings of this study provide an impetus for managers, policymakers, and consultants to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers. Societal implications-The GLSS barriers in HEIs may significantly affect the society. HEIs can lessen their environmental effect by using GLSS practices, which can support sustainability initiatives and foster social responsibility. Taking steps to reduce environmental effect can benefit society as a whole. GLSS techniques in HEIs can also result in increased operational effectiveness and cost savings, which can free up resources to be employed in other areas, like boosting student services and improving educational programs. However, failing to implement GLSS procedures in HEIs could have societal repercussions as well. As a result, it's critical for HEIs to identify and remove GLSS barriers in order to advance sustainability, social responsibility, and operational effectiveness. Originality/value-GLSS is a comprehensive methodology that facilitates the optimum utilization of resources, reduces waste, and provides the pathway for sustainable development so, the novelty of this study stands in the inclusion of its barriers and HEIs to prioritize them for effective implementation

Uji Daya Hasil Pendahuluan Kandidat Jagung Hibrida Madura

Uji daya hasil pendahuluan dilakukan untuk mengetahui potensi hasil calon varietas dibandingkan dengan varietas lainnya.  Tujuan penelitian ini adalah untuk mengevaluasi karakter tiga kandidat jagung hibrida Madura dibandingkan dengan 46 genotip lain yang diuji.  Penelitian ini dilaksanakan di Kecamatan Blega Kabupaten Bangkalan Madura pada bulan Agustus sampai November 2017.  Bahan tanaman yang digunakan dalam penelitian ini adalah tiga kandidat jagung hibrida Madura (G1 (MDR-3), G2 (MDR-4), G3 (MDR-5) dan 46 genotip jagung (entri) sebagai pembanding.  Penelitan ini menggunakan Rancangan Latis Sederhana (7x7x2).  Data dianalisis dengan uji-F, apabila terdapat pengaruh yang nyata dalam perlakuan maka dilakukan uji lanjut menggunakan uji Duncan’s  dengan taraf (α) 5%.  Hasil penelitian menunjukkan bahwa beberapa karakter tanaman dari 49 genotip yang diuji memiliki perbedaan yang nyata kecuali karakter bobot 100 biji.   Kandidat jagung hibrida Madura (G1, G2 dan G3) sangat sesuai dikembangkan di Madura karena mempunyai umur pendek (84 hari sampai 85 hari) dan produktivitas tinggi (6,7 ton per hektar sampai 8,2 ton per hektar)

Weighted Hashing-Based Capture Text Similarity Estimation with the Cross-Media Semantic Level

Web Mining is an emerging trend for the drastic advancement of the different data mining techniques. The web mining process comprises the sequence of operations that are comprises of the different languages those need to be processed effectively. The estimation of the similarity between the ontologies words and the sequences are computed. This paper proposed a Weighted Hashing Similarity Estimation (WHSE). The proposed WHSE model comprises of the weightedvalues for the estimated semantics. The computed semantics are updated in the hashing table for the estimation of the features in the variables. The proposed WHSE computes the similarity score for the extracted sematic word features in the ontology and computes the key words. The proposed WHSE model performance is comparatively examined with the existing technique. The measured recall, precision and accuracy value expressed that proposed WHSE achievesthe 0.98 accuracy value for the semantic ontology. The comparative analysis expressed that proposed WHSE achieves the ~3% -7% improvement than the existing technique for the semantic leve