Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/520476
Title: Investigation on impact of lean concept in manufacturing industries using deep learning techniques
Researcher: Vijayakumar S R
Guide(s): Suresh P
Keywords: Deep Belief Neural Network
Deep Learning Techniques
Engineering
Engineering and Technology
Engineering Mechanical
Value Stream Mapping (Vsm)
University: Anna University
Completed Date: 2023
Abstract: As industrialization is greatly associated with greater average income and also improved living standards of people, this paved way for emergence of numerous manufacturing industries all over the globe. Due to increase in number of industries, they must come out with new variant of product to withstand in this competitive world as well as to attract the customers. To meet out these above mentioned requirement concept of lean was introduced. Lean manufacturing s roots lie in Japanese manufacturing with the Toyota Production System. Lean principles pioneered by Toyota include and#8213;Just-in-Timeand#8214; manufacturing, where inventory is kept at low as-neededand#8214; levels; automation supervised by human workers to maintain quality control; minimization of downtime and transportation, and others. Implementing lean manufacturing practices in part means identifying and eliminating the wasteful practices and procedures that are specific to your business, and replacing them with more optimized lean strategies. Various lean tools are in practice for improving production in manufacturing sector. From that Value Stream Mapping (VSM) based lean principle is considered in this current research. VSM is a tool that is utilized to analyze the activity undertaken in the production process of an organization. VSM referred to Toyota as quotMaterial and Information Flow Mapping,quot and it is a technique that assists experts in distinguishing systemic resources of waste in a procedure. In this manner, the technique is eliminating these sources on an auxiliary premise. The resources waste includes time, cost, excess labour and production. These wastes must be identified and eliminated in order to reach improved profit. In this current research the resources considered for analysis cycle time. Optimizing cycle time can help in calculating the excess time spent on non- value added process and further eliminate it to maximise profit. Manufacturing cycle time is a key performance indicator for manufacturing businesses. It refers to the amount of time spent work
Pagination: xxiii, 219
URI: http://hdl.handle.net/10603/520476
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File112.17 kBAdobe PDFView/Open
02_prelim_pages.pdf3.4 MBAdobe PDFView/Open
03_content.pdf335.51 kBAdobe PDFView/Open
04_abstract.pdf125.86 kBAdobe PDFView/Open
05_chapter 1.pdf706.47 kBAdobe PDFView/Open
06_chapter 2.pdf279.75 kBAdobe PDFView/Open
07_chapter 3.pdf676.81 kBAdobe PDFView/Open
08_chapter 4.pdf673.48 kBAdobe PDFView/Open
09_chapter 5.pdf697.36 kBAdobe PDFView/Open
10_chapter 6.pdf349.64 kBAdobe PDFView/Open
11_annexures.pdf108.27 kBAdobe PDFView/Open
80_recommendation.pdf86.63 kBAdobe PDFView/Open
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