Mohit Malinda

Bio: Mohit Malinda is an academic researcher from VIT University. The author has contributed to research in topics: Repurposing. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.

Barriers in repurposing an existing manufacturing plant: a total interpretive structural modeling (TISM) approach

Abstract: Repurposing of an existing manufacturing plant is an emerging field due to the increase in emergencies of the covid-19 pandemic with the need of rapid responses which has a wide range of potential applications in sustainment of the manufacturing plant in these unfavourable times and helping of the economy. It makes the manufacturing plant adaptable to changes, makes it productive by manufacturing products that are currently in demand, prevents the dissolution of the plant and thus harvests the maximum potential of the manufacturing plant in the need of an emergency. However, not many industries and plants are suited to make the appropriate changes and lack knowledge on how to proceed to do so. The paper identifies the barriers that are faced in the transition for repurposing a general manufacturing plant to a more suited plant for current emergencies that need rapid response. These barriers hinder the repurposing of the manufacturing plant and impact the business decisions to establish a manufacturing plant suited for emergency situations. Surveys and information from various experts in this field are used to identify these barriers and document their interdependencies and influence on one another. The data is graphed and analysed utilizing TISM (Total Interpretive Structural Modelling) and MICMAC (Cross-Impact Matrix Multiplication Applied to Classification) methodology to further examine by classifying and ranking the relationships. Analysing the relationships between barriers leads to effective decisions towards the successful adoption of repurposing of manufacturing plant. A contextual relationship based structural table called interpretive table and structural model is made to pinpoint influential barriers. Thus, the research explains and explores significant barriers to the adoption of repurposing in manufacturing plant and not only provides a strong methodological and contextual contribution with the help of TISM and MICMAC but also gives research a sense of links of the barriers across various levels. On a practical level, the study is immensely useful to help manufacturing plants overcome repercussions due to disruptions by modifying existing practice and business model to a new model which synchronizes with the new normal to increase the efficiency and survivability of the plant. The result of the research points out that strategical, cultural, technological, and innovation barriers are the most influential barrier in repurposing of manufacturing plant.

Enablers for resilience and pandemic preparedness in food supply chain

Abstract: Abstract The recent COVID-19 pandemic has caused enormous disruptions to supply chain (SCs). Border restrictions forced countless businesses to close either permanently or temporarily. However, the food industry is an essential sector that needs to be operational during a pandemic. Although the food industry has proactively worked towards fulfilling human needs, the food supply chain (FSC) faced numerous challenges, forcing SC managers to rethink their business strategy to cater to consumer demands effectively. In a pandemic situation, manufacturing operations need to repurpose and adapt to produce different high-demand products. Resilience initiatives help fight disruption phases in an uncertain environment by building capacity to resist and recover to a better position. This study identifies 14 key enablers to develop a resilient FSC and reveals the most significant enablers in India. We used a hybrid Delphi-interpretive structural modeling (ISM) and Fuzzy decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) methodology to achieve these goals. The Delphi technique identified essential enablers, while the ISM analyzed the interrelationship among enablers and level of importance in a hierarchical structural model. Finally, the Fuzzy-DEMATEL categorized the enablers into the cause-effect group. This study helps SC decision-makers recognize the enablers and the contextual and causal relationships to improve resilience initiatives. It also helps them repurpose their manufacturing operations and shift to other highly required and high-demand production.

Analyzing the enablers to overcome the challenges in the adoption of electric vehicles in Delhi NCR

Abstract: The major contributor to air pollution in the cities like Delhi is emissions from vehicles running on fossil fuels. Delhi has been listed as one of the highest air polluted cities. World Health Organization has also produced a similar report. The Indian economy is highly dependent on the import of fossil fuels. One of the best ways to address these issues may be the adoption of all types of Electric Vehicles (EVs). The benefits of electric mobility are numerous. Some of these advantages include better air quality, less reliance on fuel imports, lower greenhouse gas (GHG) emissions, the enhanced plant load factor for the electrical grid, and the possibility to be a leader in a booming worldwide market. The government of India and the state governments have taken several initiatives to promote the use of EVs but the adoption of EVs is still very low. Thus, this study aims to identify the key enablers that the state government should build to encourage the adoption of EVs in Delhi. In this context, a focus group discussion composed of industry experts, practitioners, and policymakers has been used to get the opinion regarding the challenges in the adoption of EVs and enablers to overcome these challenges. Some major challenges in the adoption of EVs have been explored through the literature review and focus group discussion (FGD). To overcome these challenges, thirteen enablers for adopting EVs were identified through a literature review and FGD. Then, using the Total Interpretive Structural Modelling methodology (TISM), the mutual relationships amongst these identified enablers were evaluated and enablers with high driving power were determined. This study may help the governments and policymakers for the effective adoption of EVs in Delhi and other Metro cities.