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Consistently rising issues through food supply chain like food safety, security along with point of origin, traceability is becoming the most demanding characteristic. Numerous incidents like food adulteration, misinterpreting food characteristics and recently Covid-19 disease spread incidents in the FSC have shaken the consumer's trust and supported the need of creating traceability in the FSC. Food recalls creates huge losses. However financial losses can be catered but regaining consumer trust and recovering a bad reputation associated with product is often considered as a challenging task by the responsible authorities. A sound traceability system tends to minimize unsafe and low quality goods during production, processing and distribution phases. For implementing tracking and tracing, one should understand what drives, inhibits, and enables the tracking and tracing feature through the food supply chain. In continuation, the research is an effort to create a robust set of the drivers and prioritise them to create traceability in food supply chain. Sixteen drivers have been identified by means of literature review supported by expert's opinion. For getting priority among drivers, authors have implemented fuzzy AHP to determine the robust set of drivers along with their priorities. The results can directly contribute to the effective decision making while creating traceability in FSC. [ABSTRACT FROM AUTHOR]

With the development in industrialization, sustainability has emerged as a major issue in the global market. Ignorance of sustainability issues in any organization leads to huge financial losses and market reputation. With the development of new technologies developed economies have achieved sustainability in their industry sectors due to strong infrastructure. However, the adoption levels of sustainability practices in emerging economies are still limited. The current manufacturing trend in Industry 4.0 offers new key technologies e.g. cyber-physical systems, IoT (Internet of Things), additive manufacturing and big data analytics which are under the umbrella of Industry 4.0 known as key technologies for 4th industrial revolution. These new technologies are contributing to sustainability in a direct or indirect way. Identification of different enablers is necessary as it facilitates the adoption of sustainability practices in Industry 4.0. The present study aimed at the development of sustainability practices framework for Industry 4.0 for MSMEs (Micro Small Medium enterprises) sector. Initially, enablers to sustainability in Industry 4.0 were identified from the available literature on Sustainability and Industry 4.0. Further, a case study is done in one of MSMEs of India which is working on the adoption of Industry 4.0 practices. A hybrid MCDM (multi-criteria decision making) approach based on F-AHP (Fuzzy-Analytical hierarchy process) and DEMATEL (Decision making trial and evaluation laboratory) is utilized for the framework development. The results revealed that supply chain and environment related enablers are the main cause of barriers to sustainability in Industry 4.0. It is expected that the findings of this study will be beneficial for the researchers, policymakers and managers to improve the sustainability with the use of Industry 4.0 technologies within the emerging economies in MSMEs. [ABSTRACT FROM AUTHOR]

At present environmental pollution is the major problem that is drastically affecting human health and worsening the climatic conditions worldwide. Manufacturing industries are now working towards cleaner production to reduce the pollution level and other hazardous emissions emitted from manufacturing industries during manufacturing processes. In the present study Life cycle assessment tool is used to compute the total environmental impact of the sand casting process during its manufacturing phase and also different available scenarios have been compared to find the best one. Aluminum alloy-LM04 is used in the present study having good casting characteristics and a wide range of applications in different engineering sectors. The case study is carried out in the Indian additive manufacturing industry located in the Southern region of India. This study considers gate to gate analysis which considers the manufacturing phase of the aluminum product. The result calculated includes raw material, solid waste, energy consumption, and air emission during the manufacturing phase. Also, different environmental impact factors are calculated in the study. GABI software version 9 is used in this study for the analysis purpose. It is found that changes in electricity source in additive manufacturing industries result in about a 40 % reduction in emissions. Also, out of four studied electricity sources hydropower source is found be the best fit for manufacturing industries. About 91 % of solid waste can be reduced by the reuse of sand. Combining all the available scenario result 67 % reduction in emissions. [ABSTRACT FROM AUTHOR]