Risk analysis of machine maintenance using Markov chains
Maintenance and risk management are important issues in any manufacturing company. In order to keep equipment running efficiently and reduce maintenance cost for better profit margin, manufacturing plants have always been seeking a effective way to replace Corrective Maintenances (CM) that occur aft...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2013
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/54605 |
| _version_ | 1811691564267732992 |
|---|---|
| author | Gulati, Yuvraj Singh. |
| author2 | Wang Dan Wei |
| author_facet | Wang Dan Wei Gulati, Yuvraj Singh. |
| author_sort | Gulati, Yuvraj Singh. |
| collection | NTU |
| description | Maintenance and risk management are important issues in any manufacturing company. In order to keep equipment running efficiently and reduce maintenance cost for better profit margin, manufacturing plants have always been seeking a effective way to replace Corrective Maintenances (CM) that occur after unscheduled downtimes with more cost-effective Predictive Maintenance (PdM).
Most often, sensors are used at crucial parts of a machine to gather data. Therefore, the effectiveness of predictive maintenance is enhanced by using historical measured event data that exists in most manufacturing equipment log database.
This report, utilizing a log database from a semiconductor company plant as a study example, investigates a Recipe Based Approach (PBA) for failure risk analysis. For this approach, three different analyzing methods are used to perform a risk analysis of the system; these are – Statistical Regression Analysis, Back-Propagation Neural Network Analysis and Markov Chain analysis.
The significance of this project is to create a platform to perform risk profiling of a system. Another feature of the program is its ease of use to update and understand data. The main program is designed using Visual Basic for Applications and neural network algorithm is implemented using MatLabScripts. |
| first_indexed | 2024-10-01T06:21:54Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/54605 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:21:54Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/546052023-07-07T15:58:06Z Risk analysis of machine maintenance using Markov chains Gulati, Yuvraj Singh. Wang Dan Wei School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Maintenance and risk management are important issues in any manufacturing company. In order to keep equipment running efficiently and reduce maintenance cost for better profit margin, manufacturing plants have always been seeking a effective way to replace Corrective Maintenances (CM) that occur after unscheduled downtimes with more cost-effective Predictive Maintenance (PdM). Most often, sensors are used at crucial parts of a machine to gather data. Therefore, the effectiveness of predictive maintenance is enhanced by using historical measured event data that exists in most manufacturing equipment log database. This report, utilizing a log database from a semiconductor company plant as a study example, investigates a Recipe Based Approach (PBA) for failure risk analysis. For this approach, three different analyzing methods are used to perform a risk analysis of the system; these are – Statistical Regression Analysis, Back-Propagation Neural Network Analysis and Markov Chain analysis. The significance of this project is to create a platform to perform risk profiling of a system. Another feature of the program is its ease of use to update and understand data. The main program is designed using Visual Basic for Applications and neural network algorithm is implemented using MatLabScripts. Bachelor of Engineering 2013-06-28T04:28:05Z 2013-06-28T04:28:05Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/54605 en Nanyang Technological University 52 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Gulati, Yuvraj Singh. Risk analysis of machine maintenance using Markov chains |
| title | Risk analysis of machine maintenance using Markov chains |
| title_full | Risk analysis of machine maintenance using Markov chains |
| title_fullStr | Risk analysis of machine maintenance using Markov chains |
| title_full_unstemmed | Risk analysis of machine maintenance using Markov chains |
| title_short | Risk analysis of machine maintenance using Markov chains |
| title_sort | risk analysis of machine maintenance using markov chains |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | http://hdl.handle.net/10356/54605 |
| work_keys_str_mv | AT gulatiyuvrajsingh riskanalysisofmachinemaintenanceusingmarkovchains |