GP abstract arpan

GP abstract arpan

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  Student Arpan Mahato Student email: [email protected] Studentsphone no: 9746499848 Faculty Mentor: Mr. N Muhilvanan Industry Mentor: Mr. Virendra Dalal DGM, Banswara garments IDENTIFICATION AND ELIMINATION OF WASTE ACTIVITIES IN THE SHOP FLOOR THROUGH LEAN TOOLS Background: Overall factory economy of any industry is subject to the cost and time related to production or quality management or wastage minimization. Savings made by eliminating non value added activities and time are important for management to keep the industry economically sound and safe. Thus there is a common objective for all the stakeholders in the organization to minimize wastage for the betterment of the company and the individuals as a whole. Objective: To identify waste activities in the sewing and finishing floor of trouser section and minimize them through the application of LEAN tools.  To implement KAIZEN  To introduce KANBAN  To implement 5S  To design a work aid Research Methodology: Keywords: (preferably 5) Lean: Waste: 5S: Root cause: PDCA: Time study: Kaizen: Kanban: Analysis: Inventory: Standard WIP of 10/op fixed in trouser finishing through implementation of new token system. Extra loader eliminated. Transportation: Walking time of loader reduced from 41.5 sec to 24.5 sec through proposed layout. Waiting: Waiting of top press operation reduced through removal of extra operator. Motion: Cutting of belt loops at belt loop attach eliminated through new work aid. Over processing: Rework of checker reduced through implementation of DEFECT cards. Overproduction: 540 sq mt of fabric saved per year through reduction in excess belt loops. Rs 5000 per month saved through reduction in excess thread ends. Defects: Rework rate minimized through SOPs at selected operations. Conclusion: The study brought out the direct costs involved in wastage in the production floor. Savings made up to Rs 2.4 lakhs/annum by eliminating these wastes. Meeting with industry mentor and discussion about the project GEMBA walk in the floor to identify the activities Classifying the wastes according to LEAN Data collection on wastes generated Problem solving through PDCA and Root cause analysis Data Analysis