50 research outputs found

    Managing supply chains for sustainable operations in the era of industry 4.0 and circular economy: Analysis of barriers

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    Organizations are struggling to leverage emerging opportunities for maintaining sustainability in the global markets due to many barriers in the era of Industry 4.0 and circular economy. The main aim of this study is to analyze these barriers to improve the sustainability of a supply chain. Our study identifies the major criteria for sustainable operations and barriers that need to be overcome to achieve the objectives of sustainability through literature review and experts’ opinions. An integrated approach comprising Analytic Hierarchy Process (AHP) and Elimination and Choice Expressing Reality (ELECTRE) is used to analyze these barriers and ensure the sustainable supply chain operations. Resource circularity, increasing profits from green products, and designing processes for resource and energy efficiency have been found to be as major sustainability criteria. There are many barriers to the implementation of Industry 4.0. These barriers include but are not limited to, a lack of a skilled workforce that understands Industry 4.0, ineffective legislation and controls, ineffective performance framework, and short-term corporate goals. The study finds that ineffective strategies for the integration of industry 4.0 with sustainability measures, combined with a lack of funds for industry 4.0 initiatives, are just two of the major barriers. The findings of the study will help organizations to develop an effective and integrated strategic approach that will foster sustainable operations through the utilization of improved knowledge of Industry 4.0 and the circular economy

    Cancer Biomarker Discovery: The Entropic Hallmark

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    Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

    Guest editorial

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    Selection of warehouse location for a global supply chain: A case study

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    This study is based on an India case, where an auto components manufacturing organisation is planning to expand its business in Iran. Recently, the Government of Iran has announced incentives for industrial activities in Special Economic Zones (SEZs) and Free Trade Zones (FTZs). The purpose of this study is to illustrate the selection of most optimal location for a warehouse in various SEZs and FTZs in Iran on the basis of different criteria for warehouse location selection. Fuzzy AHP methodology has been used to choose the best out of four options available for effectiveness of supply chain. Keywords: Global supply chain, Warehouse location selection, Multi criteria decision making, Fuzzy AHP, Sensitivity analysi

    Developing IT-enabled performance monitoring system for green logistics: A case study

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    Purpose – Logistics companies are compelled to improve their efficiency and the environmental performance by introducing the green concept in their operations. The main purpose of the paper is to have continuous monitoring and tracking of logistics operations to enhance the green performance.Design/methodology/approach – This research uses a case study approach. It illustrates a monitoring system to digitize the logistics activities by sending real-time GPS data to the server and capture the surrounding pictures with the help of the Internet of things (IoTs) based camera. Data generated through digitization is mathematically analyzed for ensuring a green logistic system. The alerts due to the halts, help in keeping a check on fuel consumption, carbon emissions, and security of logistics. Performance indicators such as carbon emissions and the value of travel time saving (VTTS) are selected for the study.Findings -The findings of the study show that the actual travel time and distances are higher than the estimated travel time and distances. It also reveals that actual travel routes with diversions involve a considerably higher amount of carbon emissions during all sample travels. The results indicate a considerable saving in terms of carbon emissions, time and cost savings by effective practices of Green Logistics in Monitoring system (MSGL). These findings can help the top management of logistics companies in formulating effective strategies for technology applications in logistic operations to ensure green performance.Research limitations/implications –The study has been carried out under certain set of conditions, which may vary depending upon the organizations. Also certain more environmental dimensions for performance monitoring can be used as a future scope of study. Further studies also need to be carried out to widen the scope of the MSGL model at a global level rather than only at local level.Originality/value – Any organization which deploys transportation as part of their activity can use this MSGL model and then do the mathematical analysis to reduce the CO2 emissions, reduce the time and extra cost. The value of this study lies in the fact that Govt is trying different methods and models to reduce pollution. This MSGL should be made compulsory by the govt. as a part of their policies for environment of the country
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