Additive Manufacturing (AM) is an automated process of fabricating three-dimensional (3D) physical objects from a 3D-CAD data by adding layers of materials one upon another through a print head or nozzle without using any tooling components or machining environments. Due to freedom in design, any complex shape can be produced using this process. Fused Deposition Modeling (FDM) is one such AM technology that is commonly used for its simplicity, environment friendliness and low requirement for process monitoring. However, this technology is limited only to small-scale production due to high cost and high build time. The present work focuses on the development of a framework for parametric optimization of the FDM process using multi-objective optimization based on ratio analysis (MOORA). A CAD model of the cam follower mechanism has been prepared in the Solidworks platform and used in this experiment for optimization of build time and cost which have been considered as response variables of the experiment. The experiment has been conducted following the full factorial design of experiment (DoE) method.

Small and Medium Enterprises (SMEs) play a crucial role in the Indian economy. To remain competitive in the global market, application of Lean Manufacturing Techniques (LMT) helps SMEs to improve their processes in alignment with customer needs. The purpose of this study is to reduce overall lead time by identification and eliminating non-value added activities (NVA) from the manufacturing system. In this paper, the current manufacturing processes have been thoroughly studied using the principle of work study. Several lean approaches such as- TAKT time computation, Value stream Mapping (VSM), layout optimization, Kanban, Andon etc. have been used to make improvement in line efficiency and hence productivity. The study shows that use of line balancing technique, matches the cycle time with calculated TAKT time. And the efficiency of the line has increased approx 10% and hence balance delay got reduced. Again VSM helps to reduce the lead time of foundry shops by 51 minutes. It is one of the few studies that deal with productivity improvement in Indian SME.

The COVID-19 outbreak has illustrated the wide range of issues that supply networks confront when they are subjected to major interruptions. The supply networks for vaccines are no exception. To get out of this pandemic, it's critical to identify and address problems with the COVID-19 vaccine supply chain (VSC). This work identifies 13 challenges and prioritizes those. The findings provide stakeholders and government policymakers with realistic advice for developing a better VSC. This paper proposes a methodology based on fuzzy analytical hierarchy process (Fuzzy-AHP) with the use of triangular fuzzy numbers for prioritizing VSC barriers. It has been found that the impact of poor health worker training facilities becomes maximum with the highest weightage. Moreover, the managerial implication of the results is also provided, which will be useful for VSC sectors to take suitable decisions to overcome these obstacles.

The mobility sector including all kinds of transportation systems are facing global challenges in re-spect of green environmental issues. There has been a paradigm shift in the concept of design and manufacturing of automotive vehicles keeping in mind the scarcity of fossil fuel and the impact of emission on environment due to burning of it. The addition of hybrid and electric vehicles in pas-senger car segment has got significant momentum to address the global challenges. This research investigates the performance of a group of hybrid vehicles from customers’ perspective. Among the different brands that are available in the hybrid vehicle market, smart customers have given pri-ority to vehicle cost, mileage, tail pipe emission, comfortness and high tank size volume for long drive. Considering these attributes, selection strategy for hybrid vehicles has been developed using entropy based multi-attributive border approximation area comparison (MABAC) method. This research highlights the best hybrid vehicle which reduces air pollution in cities with other significant environmental benefits, reduces dependence on foreign energy imports and minimizes the annual fuel cost.

There are many opportunities and challenges in the area of Indian technical education due to liberalization and globalization of economy. One of these challenges is how to assess the performance of technical institutions based on multiple criteria. The purpose of this paper is to describe and illustrate an application of a structured approach to determine relative performance and ranking of seven Indian Institutes of Technology (IITs) under multi-criteria environment. To evaluate the alternatives in respect to stakeholders’ preference we suggest a new methodology consisting of fuzzy AHP, DEA and TOPSIS. Fuzzy AHP technique is used to determine the weights of criteria and some linguistic terms are applied to assess performance under each criterion, then in order to determine the value of linguistic terms we use the data envelopment analysis (DEA) method. Finally TOPSIS method is used to aggregate performance scores under different criteria into an overall performance score for each institution and ranking the institution according to their overall performance score. The proposed fuzzy AHP–DEA–TOPSIS methodology is applicable to any multiple criteria decision making (MCDM) problem due to its generic nature.