Enabling condition-based maintenance in precious metals processing
- Authors: Ngoma, W. J.
- Date: 2019
- Subjects: Ion pumps - Maintenance and repair , Pumping machinery - Maintenance and repair , Ventilation - Equipment and supplies , Sustainable construction
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/417785 , uj:35396
- Description: Abstract: This dissertation focussed on improving maintenance practice for vacuum pump and ventilation fan systems. The availability and safe operation of assets and plant is a vital consideration in refineries. The optimisation of maintenance is required to improve the plant availability and performance and to reduce operating costs. This dissertation was inspired by the maintenance challenges facing a company that is involved in the refining of special metals. For such a precious metal refinery plant, fume extraction and filtration systems are important to personal safety and processing. Chemicals used in the plants are toxic and hence it is essential that the engineering systems such as extraction fans are always in good condition. Vacuums systems are used as filtration process to separate solids from waste. Product extraction requires precision systems. Proper and suitable maintenance should be deployed on these critical systems, to avoid plant delays and to provide the necessary plant operating environment. Running equipment/systems to failure affects plant performances. A key focus for the company has been installing early detection sensors to monitor and predict abnormal equipment behaviours. The aim of this dissertation was to build on from such investments and examine how maintenance could be improved and better informed by the condition monitoring systems. The research examined existing literature on condition-based maintenance, maintenance and practice at the company under study. Pareto analysis was used to define the critical assets and problems that dominated the escalating maintenance costs. This allowed focus on the big hit strategies (big gains). The research was conducted in three sections around the entire plant at Precious refinery plant, these sections are as follows, Main extraction fan system, Material handling extraction fan system and Other precious vacuum system. Process data was collected on existing sensors, analysed and used to infer condition of critical assets. New statistical tools such as process capability index were introduced to enable tracking the condition of the equipment. Process capability index values for processes in control and out of control were defined and these can be used for tracking system deterioration and enabling predictive maintenance. The focus was on investigation of failures on vacuum pumps and ventilation fans. The research demonstrated the potential for existing sensors and data to be used in predictive maintenance to alert maintenance teams to attend to vacuum pumps and fans pre-failure and hence improve plant availability, operations and reduce cost. , M.Ing. (Engineering Management)
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- Authors: Ngoma, W. J.
- Date: 2019
- Subjects: Ion pumps - Maintenance and repair , Pumping machinery - Maintenance and repair , Ventilation - Equipment and supplies , Sustainable construction
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/417785 , uj:35396
- Description: Abstract: This dissertation focussed on improving maintenance practice for vacuum pump and ventilation fan systems. The availability and safe operation of assets and plant is a vital consideration in refineries. The optimisation of maintenance is required to improve the plant availability and performance and to reduce operating costs. This dissertation was inspired by the maintenance challenges facing a company that is involved in the refining of special metals. For such a precious metal refinery plant, fume extraction and filtration systems are important to personal safety and processing. Chemicals used in the plants are toxic and hence it is essential that the engineering systems such as extraction fans are always in good condition. Vacuums systems are used as filtration process to separate solids from waste. Product extraction requires precision systems. Proper and suitable maintenance should be deployed on these critical systems, to avoid plant delays and to provide the necessary plant operating environment. Running equipment/systems to failure affects plant performances. A key focus for the company has been installing early detection sensors to monitor and predict abnormal equipment behaviours. The aim of this dissertation was to build on from such investments and examine how maintenance could be improved and better informed by the condition monitoring systems. The research examined existing literature on condition-based maintenance, maintenance and practice at the company under study. Pareto analysis was used to define the critical assets and problems that dominated the escalating maintenance costs. This allowed focus on the big hit strategies (big gains). The research was conducted in three sections around the entire plant at Precious refinery plant, these sections are as follows, Main extraction fan system, Material handling extraction fan system and Other precious vacuum system. Process data was collected on existing sensors, analysed and used to infer condition of critical assets. New statistical tools such as process capability index were introduced to enable tracking the condition of the equipment. Process capability index values for processes in control and out of control were defined and these can be used for tracking system deterioration and enabling predictive maintenance. The focus was on investigation of failures on vacuum pumps and ventilation fans. The research demonstrated the potential for existing sensors and data to be used in predictive maintenance to alert maintenance teams to attend to vacuum pumps and fans pre-failure and hence improve plant availability, operations and reduce cost. , M.Ing. (Engineering Management)
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Predictive maintenance as a means to increase the availability of a positive displacement pump
- Authors: Museka, Zvikomborero Austen
- Date: 2015-06-29
- Subjects: Engineering - Management , Pumping machinery - Maintenance and repair , Positive displacement pumps
- Type: Thesis
- Identifier: uj:13645 , http://hdl.handle.net/10210/13829
- Description: M.Ing. (Engineering Management) , Please refer to full text to view abstract
- Full Text:
- Authors: Museka, Zvikomborero Austen
- Date: 2015-06-29
- Subjects: Engineering - Management , Pumping machinery - Maintenance and repair , Positive displacement pumps
- Type: Thesis
- Identifier: uj:13645 , http://hdl.handle.net/10210/13829
- Description: M.Ing. (Engineering Management) , Please refer to full text to view abstract
- Full Text:
Predictive maintenance as a means to increase the availability of positive displacement pumps at Ekurhuleni Base Metals
- Authors: Kau, Motlalepula Lawrence
- Date: 2016
- Subjects: Industrial equipment - Maintenance and repair , Pumping machinery - Maintenance and repair , Plant maintenance - Management , Total productive maintenance
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/233738 , uj:23870
- Description: M.Phil. (Engineering Management) , Abstract: Condition monitoring is a maintenance technique used to monitor parameters like vibration, overheating, overcurrent of the system or machinery at an early stage of failure; to forecast on the need for maintenance before a catastrophic failure; or to estimate system conditions. It can be achieved through visual inspection or the use of a sophisticated intelligent diagnosis system. Predictive maintenance helps the organisation to predict failure before a catastrophic failure. It is a technique to help the user plan the job that needs to be done on the equipment to prevent an unexpected failure. This technique is central to our research question. This study investigated whether predictive maintenance is the best maintenance strategy to minimise maintenance costs. In predictive maintenance, decisions are made based on the data collected through condition monitoring. Condition monitoring has three steps: data acquisition, data processing and maintenance decision-making. Condition monitoring helps to prevent equipment failure. It also helps to avoid unplanned breakdowns and to optimise maintenance resources by planning maintenance or shutdown as required based on the data collected. Peristaltic pumps, such as LPPT 65 (DN65), are commonly used for pumping slurry. Ekurhuleni Base Metals uses it to pump slurry. Due to several failures, the pumps are not operating at their peak efficiency point. Before the implementation of predictive maintenance, the pumps did not receive regular maintenance. In the past, the organisation did reactive maintenance, and maintenance costs were escalating. Root Cause Failure Analysis (RCFA) helps to understand the root cause of equipment failure, and is commonly used to reduce costs, mean time to failure (MTTF) and mean down time (MDT). If implemented successfully, the organisation benefits significantly in terms of cost savings and/or total elimination of failure. Organisations benefit considerably from implementing Reliability Centred Maintenance (RCM). It aims to identify routine maintenance that preserves the system in such a way that costs are acceptable. If preventive maintenance costs are higher than those of operational losses and repair, maintenance will not be beneficial, unless it relates to regulatory, safety or environmental requirements...
- Full Text:
- Authors: Kau, Motlalepula Lawrence
- Date: 2016
- Subjects: Industrial equipment - Maintenance and repair , Pumping machinery - Maintenance and repair , Plant maintenance - Management , Total productive maintenance
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/233738 , uj:23870
- Description: M.Phil. (Engineering Management) , Abstract: Condition monitoring is a maintenance technique used to monitor parameters like vibration, overheating, overcurrent of the system or machinery at an early stage of failure; to forecast on the need for maintenance before a catastrophic failure; or to estimate system conditions. It can be achieved through visual inspection or the use of a sophisticated intelligent diagnosis system. Predictive maintenance helps the organisation to predict failure before a catastrophic failure. It is a technique to help the user plan the job that needs to be done on the equipment to prevent an unexpected failure. This technique is central to our research question. This study investigated whether predictive maintenance is the best maintenance strategy to minimise maintenance costs. In predictive maintenance, decisions are made based on the data collected through condition monitoring. Condition monitoring has three steps: data acquisition, data processing and maintenance decision-making. Condition monitoring helps to prevent equipment failure. It also helps to avoid unplanned breakdowns and to optimise maintenance resources by planning maintenance or shutdown as required based on the data collected. Peristaltic pumps, such as LPPT 65 (DN65), are commonly used for pumping slurry. Ekurhuleni Base Metals uses it to pump slurry. Due to several failures, the pumps are not operating at their peak efficiency point. Before the implementation of predictive maintenance, the pumps did not receive regular maintenance. In the past, the organisation did reactive maintenance, and maintenance costs were escalating. Root Cause Failure Analysis (RCFA) helps to understand the root cause of equipment failure, and is commonly used to reduce costs, mean time to failure (MTTF) and mean down time (MDT). If implemented successfully, the organisation benefits significantly in terms of cost savings and/or total elimination of failure. Organisations benefit considerably from implementing Reliability Centred Maintenance (RCM). It aims to identify routine maintenance that preserves the system in such a way that costs are acceptable. If preventive maintenance costs are higher than those of operational losses and repair, maintenance will not be beneficial, unless it relates to regulatory, safety or environmental requirements...
- Full Text:
The advantages of predictive maintenance as a means to improve the availability of centrifugal slurry pump at Ergo City Deep Plant
- Authors: Martinus, Aroon
- Date: 2018
- Subjects: Mining machinery - Maintenance and repair , Pumping machinery - Maintenance and repair , Plant maintenance - Management
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/284823 , uj:30776
- Description: M.Phil. (Engineering Management) , Abstract: Condition monitoring is the process of monitoring a parameter of condition (vibration, temperature etc.) in machinery in order to identify a significant change which is indicative of developing fault. It is a major component of Predictive Maintenance. The use of condition monitoring allows maintenance to be scheduled, or other actions to be taken to prevent failure and it consequences. Predictive Maintenance helps the organization to predict equipment failure before a catastrophic failure can occur. The purpose for implementing Predictive Maintenance in industry is to increase productivity, decrease maintenance costs and downtime, and also to increase safety. In this study, Predictive Maintenance was implemented as a means to improve the availability of a centrifugal slurry pump, and conclusions were made on whether it is a better method than reactive maintenance to minimize equipment downtime and maintenance operation costs. Centrifugal slurry pumps are used in many applications such as in the mining, chemical and in the industrial plants. Ergo City Deep Plant uses centrifugal slurry pumps to pump slurry from its City Deep pumping station to Elsburg pumping station over a distance of about 50 km. Due to unplanned breakdowns, the pumps are not operating at peak efficiency point, and as a result the plant does not meet its monthly production target. Before the implementation of Predictive Maintenance, no planned maintenance strategy was done on the pumps. Ergo City Deep Plant used reactive (breakdown) maintenance, which had escalated the maintenance operating costs year on year. Reactive Maintenance methods result in huge unplanned costs as well as overheads if the budget for maintenance is exceeded in order to restore the pump into working order. Hench in this study, Predictive Maintenance by using Condition Monitoring techniques was used to improve the availability of a centrifugal slurry pump. From the field data the pump availability increased by Predictive Maintenance. The research field data resulted in decrease in downtime and equipment failures, and also reduced maintenance costs. It was concluded that Predictive Maintenance is a better maintenance method than reactive maintenance.
- Full Text:
- Authors: Martinus, Aroon
- Date: 2018
- Subjects: Mining machinery - Maintenance and repair , Pumping machinery - Maintenance and repair , Plant maintenance - Management
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/284823 , uj:30776
- Description: M.Phil. (Engineering Management) , Abstract: Condition monitoring is the process of monitoring a parameter of condition (vibration, temperature etc.) in machinery in order to identify a significant change which is indicative of developing fault. It is a major component of Predictive Maintenance. The use of condition monitoring allows maintenance to be scheduled, or other actions to be taken to prevent failure and it consequences. Predictive Maintenance helps the organization to predict equipment failure before a catastrophic failure can occur. The purpose for implementing Predictive Maintenance in industry is to increase productivity, decrease maintenance costs and downtime, and also to increase safety. In this study, Predictive Maintenance was implemented as a means to improve the availability of a centrifugal slurry pump, and conclusions were made on whether it is a better method than reactive maintenance to minimize equipment downtime and maintenance operation costs. Centrifugal slurry pumps are used in many applications such as in the mining, chemical and in the industrial plants. Ergo City Deep Plant uses centrifugal slurry pumps to pump slurry from its City Deep pumping station to Elsburg pumping station over a distance of about 50 km. Due to unplanned breakdowns, the pumps are not operating at peak efficiency point, and as a result the plant does not meet its monthly production target. Before the implementation of Predictive Maintenance, no planned maintenance strategy was done on the pumps. Ergo City Deep Plant used reactive (breakdown) maintenance, which had escalated the maintenance operating costs year on year. Reactive Maintenance methods result in huge unplanned costs as well as overheads if the budget for maintenance is exceeded in order to restore the pump into working order. Hench in this study, Predictive Maintenance by using Condition Monitoring techniques was used to improve the availability of a centrifugal slurry pump. From the field data the pump availability increased by Predictive Maintenance. The research field data resulted in decrease in downtime and equipment failures, and also reduced maintenance costs. It was concluded that Predictive Maintenance is a better maintenance method than reactive maintenance.
- Full Text:
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