Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/21890
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dc.contributor.advisorMurthy, Rajluxmi V
dc.contributor.authorPegu, Hansraj
dc.contributor.authorHoro, Saomya Srishti
dc.date.accessioned2023-05-15T12:30:04Z-
dc.date.available2023-05-15T12:30:04Z-
dc.date.issued2022
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/21890-
dc.description.abstractGiven the vastly complex nature of supply chain networks, firms need to leverage a multitude of optimization methods and data analytics tools to make their decisions, such a firm is TVS Supply Chain Solutions (TVSSCS). As they aim to bid for more opportunities in the future, it becomes critical to dive into the core of their operations- the workforce, who carry out tasks at an individual level which all add up and inevitably form the supply chain. One needs the ability to properly allocate resources at each step of the supply chain to rise above the competition. Our project is focused on manpower allocation in the warehouse, more specifically in the putaway and picking processes. Based on the standards set, and the layout of the warehouse, for a given demand of items we need to estimate the optimum number of workers. Using a Time and Motion Study (TMS) of all different tasks performed by the workers, and taking into account the shifts of workers, we calculate the optimum number of workers for different scenarios of putaway and picking processes for a given demand. Additionally, using a sample of simulated data we developed a model which recommends the optimal location to store the items, automating the allocation of storage location, and enabling better mobility of the products down the warehouse. Finally, to supplement the TMS and improve the productivity of the workforce, we have recommended three video analytics solutions that will further open scopes for improvement in the warehouse processes.
dc.publisherIndian Institute of Management Bangalore
dc.relation.ispartofseriesPGP_CCS_P22_026
dc.subjectSupply chain
dc.subjectWarehouse automation
dc.subjectVideo analytics
dc.subjectAutomobile industry
dc.subjectTVS supply chain
dc.titleWarehouse automation selection and video analytics with TVS supply chain solutions
dc.typeCCS Project Report-PGP
dc.pages19p.
Appears in Collections:2022
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