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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 |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 112.17 kB | Adobe PDF | View/Open |
02_prelim_pages.pdf | 3.4 MB | Adobe PDF | View/Open | |
03_content.pdf | 335.51 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 125.86 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 706.47 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 279.75 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 676.81 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 673.48 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 697.36 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 349.64 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 108.27 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 86.63 kB | Adobe PDF | View/Open |
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