Evaluating the Performances of the Agoraphilic Navigation Algorithm under Dead-Lock Situations
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th IEEE International Symposium on Industrial Electronics, ISIE 2020 Vol. 2020-June, p. 536-542
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- Description: This paper presents a summary of the research which was conducted in developing a new free-space based (Agoraphilic) navigation algorithm. This new methodology is capable of maneuvering robots in static as well as dynamically cluttered unknown environments. The new algorithm uses only one force to drive the robot. This force is always an attractive force created by the freespace. This force is focused towards the goal by a force shaping module. Consequently, the robot is motivated to follow free-space directing towards the goal. As this method only based on the attractive forces, the robot always moves towards the goal as long as there is free-space . This method has eradicated many drawbacks of the traditional APF method. Several experimental tests were conducted using Turtlebot3 research platform. These tests were focused on testing the behavior of the new algorithm under dead-lock (local minima) situations for APF method. The test results proved that the proposed algorithm has successfully eliminated the local minima problem of APF method. © 2020 IEEE.
Agoraphilic navigation algorithm in dynamic environment with and without prediction of moving objects location
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 Vol. 2019-October, p. 5179-5185
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- Description: This paper presents a summary of research conducted in performance improvement of Agoraphilic Navigation Algorithm under Dynamic Environment (ANADE). The ANADE is an optimistic navigation algorithm which is capable of navigating robots in static as well as in unknown dynamic environments. ANADE has been successfully extended the capacity of original Agoraphilic algorithm for static environment. However, it could identify that ANADE takes costly decisions when it is used in complex dynamic environments. The proposed algorithm in this paper has been successfully enhanced the performance of ANADE in terms of safe travel, speed variation, path length and travel time. The proposed algorithm uses a prediction methodology to estimate future growing free space passages which can be used for safe navigation of the robot. With motion prediction of moving objects, new set of future driving forces were developed. These forces has been combined with present driving force for safe and efficient navigation. Furthermore, the performances of proposed algorithm (Agoraphilic algorithm with prediction) was compared and benched-marked with ANADE (Without predication) under similar environment conditions. From the investigation results, it was observed that the proposed algorithm extends the effective decision making ability in a complex navigation environment. Moreover, the proposed algorithm navigated the robot in a shorter and quicker path with smooth speed variations. © 2019 IEEE.
- Description: E1
Comparative study on object tracking algorithms for mobile robot navigation in GPS-denied environment
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2019
- Type: Text , Conference proceedings
- Relation: 2019 IEEE International Conference on Industrial Technology, ICIT 2019; Melbourne, Australia; 13th-15th February 2019 Vol. 2019-February, p. 19-26
- Full Text: false
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- Description: This paper presents a comparative study conducted on the performance of the commonly used object tracking and location prediction algorithms for mobile robot navigation in a dynamically cluttered and GPS-denied mining environment. The study was done to test the different algorithms for the same set criteria (such as accuracy and computational time) under the same conditions.The identified commonly used algorithms for object tracking and location prediction of moving objects used in this investigation are Kalman filter (KF), extended Kalman filter (EKF) and particle filter (PF). The study results of those algorithms are analyzed and discussed in this paper. A trade-off was apparent. However, in overall performance KF has shown its competitiveness.The result from the study has found that the KF based algorithm provides better performance in terms of accuracy in tracking dynamic objects under commonly used benchmarks. This finding can be used in development of an efficient robot navigation algorithm.
- Description: Proceedings of the IEEE International Conference on Industrial Technology
Tire size identification using extreme learning machine algorithm
- Authors: Kahandawa, Gayan , Choudhury, Tanveer , Ibrahim, Yousef
- Date: 2018
- Type: Text , Conference proceedings
- Relation: 27th IEEE International Symposium on Industrial Electronics, ISIE 2018; Cairns, Australia; 13th-15th June 2018 Vol. 2018-June, p. 571-576
- Full Text: false
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- Description: Precise tire size identification is needed to increase the efficiency and the reliability of tire inflators and to minimize the inflation cycle time. On the other hand the correct inflation pressure improve the road safety and tire life as well. A single hidden layer feed forward neural network (SLFN) is used in this study to precisely identify a tire size to enhance the tire inflation cycle. The training times of traditional back propagation algorithms, mostly used to model such tire identification processes, are far slower than desired for implementation of an on-line control system. Use of slow gradient based learning methods and iterative tuning of all network parameters during the learning process are the two major causes for such slower learning speed. An extreme learning machine (ELM) algorithm, which randomly selects the input weights and biases and analytically determines the output weights, is used in this work to train the SLFNs. It is found that networks trained with ELM have relatively good generalization performance, much shorter training times and stable performance with regard to the changes in number of hidden layer neurons. The result represents robustness of the trained networks and enhance reliability of the mode. Together with short training time, the algorithm has valuable application in tire identification process.
- Description: IEEE International Symposium on Industrial Electronics
Industry-led mechatronics degree development in regional Australia
- Authors: Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer , Mazid, Abdul Md
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 2017 IEEE International Conference on Mechatronics, ICM 2017; Gippsland, Australia; 13th-15th February 2017 p. 419-424
- Full Text: false
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- Description: This paper presents a technique that was used in the recent development of a new Mechatronics degree in Australia. This technique addressed the local industry needs and the available resources for a well-balanced Mechatronics degree program. The degree development was based on project-based learning and industry engagement. The development of the new Mechatronics degree was made possible via a State Government grant of AU$2.4 Million which was matched by industry contribution of AU$10 Million in cash and in-kind. Since industry was a major stake holder in this degree, a specific industry survey was conducted to check the desired graduates attributes, from industry point of view. The results of this survey is also included in this papers. In addition, the program also addressed the regional industry's challenge of retaining qualified engineers via a clear pathway program for students knowledge and skills development. This paper presents industry's anticipated outputs of the academic Mechatronics program. In addition the paper also discusses the mechanisms adopted for the development of this new degree. The developed fully integrated Mechatronics program was founded on the realisation that if a person undertook a mechanical degree followed by an electronics degree followed by a computer science degree, that person is, still, NOT a Mechatronics engineer. © 2017 IEEE.
- Description: Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017
New state observer gain tuning methodology based on the stable margin theory
- Authors: Ogawa, Kenji , Ohnishi, Kouhei , Ibrahim, Yousef
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 2017 IEEE International Conference on Industrial Technology, ICIT 2017; Toronto, Canada; 23rd-25th March 2017 p. 677-682
- Full Text: false
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- Description: This paper proposes a new observer gain tuning methodology to achieve a robust position control. The state observer is often used to estimate the state of the system. Generally, the observer gain is tuned by an evaluation function and the operator needs to arbitrarily select a weight function to obtain an optimal observer gain. This paper introduces a methodology for observer gain tuning using the stability margin theory. In addition, the state observer is combined with the Disturbance Observer (DOB) to achieve a robust position control. The validity of the proposed methodology was tested and confirmed by simulations and experimental study. © 2017 IEEE.
- Description: Proceedings of the IEEE International Conference on Industrial Technology
Novel tire inflating system using extreme learning machine algorithm for efficient tire identification
- Authors: Choudhury, Tanveer , Kahandawa, Gayan , Ibrahim, Yousef , Dzitac, Pavel , Mazid, Abdul Md , Man, Zhihong
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 2017 IEEE International Conference on Mechatronics, ICM 2017; Gippsland, Victoria; 13th-15th February 2017 p. 404-409
- Full Text: false
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- Description: Tire inflators are widely used all around the word and the efficient and accurate operation is essential. The main difficulty in improving the inflation cycle of a tire inflator is the identification of the tire connected for inflation. A robust single hidden layer feed forward neural network (SLFN) is, thus, used in this study to model and predict the correct tire size. The tire size is directly related to the tire inflation cycle. Once the tire size is identified, the inflation process can be optimized to improve performance, speed and accuracy of the inflation system. Properly inflated tire and tire condition is critical to vehicle safety, stability and controllability. The training times of traditional back propagation algorithms, mostly used to model such tire identification processes, are far slower than desired for implementation of an on-line control system. Use of slow gradient based learning methods and iterative tuning of all network parameters during the learning process are the two major causes for such slower learning speed. An extreme learning machine (ELM) algorithm, which randomly selects the input weights and biases and analytically determines the output weights, is used in this work to train the SLFNs. It is found that networks trained with ELM have relatively good generalization performance, much shorter training times and stable performance with regard to the changes in number of hidden layer neurons. The result represents robustness of the trained networks and enhance reliability of the mode. Together with short training time, the algorithm has valuable application in tire identification process. © 2017 IEEE.
- Description: Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017
OEE improvement of thermoforming machines through application of TPM at Tibaldi Australasia
- Authors: Chundhoo, Vickram , Chattopadhyay, Gopinath , Gunawan, Indra , Ibrahim, Yousef
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017; Singapore, Singapore; 10th-13th December 2017 p. 929-933
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- Description: Overall Equipment Effectiveness (OEE) evaluates quantitatively how effectively a manufacturing operation is utilised. Total Productive Maintenance (TPM) was considered by Tibaldi, a leading food manufacturer in Australia for achieving OEE. This research project has identified performance gaps, developed plan and implemented it in Thermoforming area of the business. The developed methodology helped Tibaldi in improving productivity and quality through TPM involving machines, equipment, processes, and employees. This paper demonstrates how this can be achieved by reducing lead time and establishing lean environment. Productivity improvement through the devised methodology led to further enhancement of competitiveness of the organisation for domestic and international markets of processed food manufactured by Tibaldi Australia. Lessons learned from application of TPM in Thermoforming, a key asset area, is rolled out to other sections of the plat and results from this pilot study are presented in this paper.
On the development of a portable, cost effective and compact master/slave system for robot-assistec Minimally Invasive Surgery
- Authors: Saafi, Houssem , Laribi, Med Amine , Zeghloul, Said , Ibrahim, Yousef
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 2017 IEEE International Conference on Mechatronics, ICM 2017; Gippsland, Australia;13th-15th February 2017 p. 290-296
- Full Text: false
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- Description: Tele-operation systems offer more security and comfort to the surgeon in Minimally Invasive Surgery (MIS). This paper presents a new tele-operation system for MIS. This system was designed to be efficient, portable, compact and affordable. The developments of master and slave robots of the teleoperation system are presented. Some issues encountered in the development of these robots are studied here. The main issues are as follows: the presence of the singularities in the workspace of the master robot, the complexity of the master forward kinematic model due to its parallel structure and the difference between the kinematics of the master and the slave robots. Those issues are solved using different techniques which are presented in this paper. Finally, experimental validations of the developed teleoperation system were carried out successfully. © 2017 IEEE.
- Description: Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017
Evaluation of control system reliability using combined dynamic fault trees and Markov models
- Authors: Kolek, Levente , Ibrahim, Yousef , Gunawan, Indra , Laribi, Med Amine , Zegloul, Said
- Date: 2015
- Type: Text , Conference proceedings
- Full Text: false
- Description: In this paper, dynamic simulation methods for reliability evaluation of common industry-based control system architectures are investigated. Control system design often employs complex reliability structures in the forms of several levels of software and hardware redundancies, hot and cold standby systems. This is required in order to achieve certain plant availability and safety functions. Control system maintenance requires expert knowledge due to the complexity of troubleshooting steps involved with a hardware or software failures of a large system. Hence, it is crucial to understand the effect of recovery time on reliability and on overall availability in a critical control system. Dynamic Fault Tree Analysis (DFTA), Markov Chains and Reliability Block Diagrams (RBD) are presented and a block library is introduced for addressing the aforementioned modelling problems. In order to be able to evaluate dynamic fault trees and Markov Chains, Monte Carlo simulation has been used. An industry-based case study is presented, where critical failures of a redundant Programmable Logic Controller (PLC) system are identified by a Failure Mode and Effect Analysis (FMEA). The bottom up process of modelling control system reliability is discussed. © 2015 IEEE.
New artificial intelligence based tire size identification for fast and safe inflating cycle
- Authors: Kahandawa, Gayan , Choudhury, Tanveer , Ibrahim, Yousef , Dzitac, Pavel , Mazid, Abdul Md
- Date: 2015
- Type: Text , Conference proceedings
- Full Text: false
- Description: Motor vehicle accidents are one of the main killers on the road. Modern vehicles have several safety features to improve the stability and controllability. The tire condition is critical to the proper function of the designed safety features. Under or over inflated tires adversely affects the stability of vehicles. It is generally the vehicle's user responsibility to ensure the tire inflation pressure is set and maintained to the required value using a tire inflator. In the tire inflator operation, the vehicle's user sets the desired value and the machine has to complete the task. During the inflation process, the pressure sensor does not read instantaneous static pressure to ensure the target value is reached. Hence, the inflator is designed to stop repetitively for pressure reading and avoid over inflation. This makes the inflation process slow, especially for large tires. This paper presents a novel approach using artificial neural network based technique to identify the tire size. Once the tire size is correctly identified, an optimized inflation cycle can be computed to improve performance, speed and accuracy of the inflation process. The developed neural network model was successfully simulated and tested for predicting tire size from the given sets of input parameters. The test results are analyzed and discussed in this paper. © 2015 IEEE.
Optimal sensing requirement for slippage prevention in robotic grasping
- Authors: Dzitac, Pavel , Mazid, Abdul Md , Ibrahim, Yousef , Appuhamillage, Gayan , Choudhury, Tanveer
- Date: 2015
- Type: Text , Conference proceedings
- Full Text: false
- Description: This paper presents a new theoretical development and modelling related to the requirement of the minimum number of sensors necessary for slippage prevention in robotic grasping. A fundamental experimental investigation has been conducted to support the newly developed postulate. A series of basic experiments proved that it is possible to evaluate the contributions of various sensors to slippage prevention and control in robotic grasping. The use of three discrete physical sensors, one for each of the three sensing functions (normal, tangential and slippage), has been proven to be the most reliable combination for slippage prevention in robotic grasping. It was also proven that the best performance from a two-sensor combination can be achieved when normal grasp force and tangential force are both monitored in the grasping process. © 2015 IEEE.
An optimization model for multi-state weighted kout-of-n system reliability value
- Authors: Korshidi, Hadi , Gunawan, Indra , Ibrahim, Yousef
- Date: 2013
- Type: Text , Conference proceedings
- Relation: IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society, Vienna, Austria Nov. 2013, p.4357-4361
- Full Text: false
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- Description: A reliability optimization model is proposed in this paper for multi-state weighted k-out-of-n systems. In this model, income generated by components through each functioning period is used as a reliability index. Therefore, time value of money is used in the presented optimization model to estimate both system's reliability and cost. The system reliability is evaluated by Universal Generating Function (UGF). The model's objective function is to maximize the net present value (NPV) of the system. Therefore, it would maximize the system reliability and minimize the system cost simultaneously. A numerical example is presented in this paper to illustrate the model by finding the optimal design of the system, and the best time for maintenance plan. Also, a discussion is provided based on the result.
Cyclic scheduling in small-scale robotic cells served by a multi-function robot
- Authors: Foumani, Mehdi , Ibrahim, Yousef , Gunawan, Indra
- Date: 2013
- Type: Text , Conference proceedings
- Relation: IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society, Nov. 2013, Vienna, Austria pp.4362-4367
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- Description: The industrial robot is one of the popular devices used in fully automatic production lines as material handling tool. A consequential problem is finding a cyclic robot movement which gives the maximum cell output in mass production environments. The Robotic Cell Scheduling Problem (RCSP) is predominantly separated into two different problems: Single-Function Robotic Cell (SFRC) and Multi-Function Robotic Cell (MFRC) scheduling problem. These problems are layout-oriented and operation-oriented, respectively. Literature concerning with former case considered a robotic system served by a transporting robot performing a single task. This kind of transporting robot is usually called Single-Function Robot (SFR). For the latter case, the robotic system served by a Multi-Function Robot (MFR) which simultaneously perform an arbitrary task in addition to parts transportation task. Giving a real-life example of MFRs, the use of a class of grippers performing in-process control is significantly increased in industry. The grippers, install at the end of MFR arm, can perform quality control tasks (e.g. accurately measure diameters) while part is carried to next machine. Figure 1 shows an example of these grippers used for measuring the diameter of crankshaft [1]. The measuring heads are integrated into the automation by adding gages and crankshaft locating features to MFR using in these lines. Also, there is a special kind of MFR, namely SDA10, which is suitable for assembly and part transfer in production lines especially if fixturing is costly [2]. Thus, it is crucial to undertake a comprehensive research onto effect of MFRs on production rate.
Development of a spherical parallel manipulator as a haptic device for a tele-operation system: Application to robotic surgery
- Authors: Saafi, Hadi , Laribi, Med Amine , Zeghoul, Said , Ibrahim, Yousef
- Date: 2013
- Type: Text , Conference proceedings
- Relation: IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society, Nov. 2013, Vienna, Austria p. 4097-4102
- Full Text: false
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- Description: In tele-operation applications, especially in surgery, haptic devices need to exhibit a high degree of rigidity and accuracy. This paper deals with the development of a spherical parallel manipulator (SPM) that enables the satisfaction of those characteristics. The parallel architecture enables the use of this kind of robot as master in a tele-operation system. Moreover, the SPM has a center of rotation that makes it a natural candidate and more adapted to minimally invasive surgery application. However, the parallel manipulator presents a poor behavior in singular configuration. In this paper we discuss the technique we used to overcome the singularity effects. We also present the methodology of using additional sensor to avoid kinematic structure problem without design changes. The investigation of the developed solution is detailed in this paper. Also, the experimental results of the newly developed haptic device are presented in this paper.
Investigation on system reliability optimization based on classification of criteria
- Authors: Khorshidi, Hadi , Gunawan, Indra , Ibrahim, Yousef
- Date: 2013
- Type: Text , Conference proceedings
- Relation: Industrial Technology (ICIT), 2013 IEEE International Conference, Capetown, SA. 25-28 Feb. 2013 p.1706-1711
- Full Text: false
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- Description: System reliability optimization has been considered as an area to improve the operational availability of electrical and manufacturing systems. This research area addresses system reliability estimation and mathematical model development. This paper presents a -review on system reliability optimization techniques based on different classification of criteria. The main criteria considered in this study are system structure, system state, optimization model, allocation model, modeling and solution methods. The classification can provide an overview of all criteria that should be used to make optimal decisions in a system by taking the reliability into account. Not only it can assist the researchers to develop new optimization models, but also it presents the practitioners how system reliability optimization models can help industries. The paper also discusses the limitations of the present techniques in this area.
Quantifying the impact of using multi-function robots on productivity of rotationally arranged robotic cells
- Authors: Foumani, Mehdi , Ibrahim, Yousef , Gunawan, Indra
- Date: 2013
- Type: Text , Conference proceedings
- Relation: Industrial Engineering and Engineering Management (IEEM), 2013 IEEE International Conference , Bangkok, Thailand, 10-13 Dec. 2013 p 1194-1198
- Full Text: false
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- Description: Generally, an industrial robot is named the Single-Function Robot (SFR) if it is only able to perform one task like material handling. However, a Multi-Function Robot (MFR) predominantly performs two tasks concurrently: material handling and a special operation. This type of recent robot with this ability can raise production rate. A robot equipped by a special kind of gripper namely Grip-Gage-Go is a real-life applications of MFRs. This gripper makes MFR competent to measure the diameter of the part in transit. These MFRs are widely employed in the inspection of automotive products including crankshaft, gears, and engine valves [1]
Scheduling dual gripper robotic cells with a hub machine
- Authors: Foumani, Mehdi , Ibrahim, Yousef , Gunawan, Indra
- Date: 2013
- Type: Text , Conference proceedings
- Relation: Industrial Electronics (ISIE), 2013 IEEE International Symposium, Taipei, Taiwan, 28th-31st May 2013 p1-6
- Full Text: false
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- Description: This paper introduces a new methodology to optimise the cycle time of dual-gripper robotic workcells. The workcell under study is composed of a group of m production machines. In order to produce a completed part, a chain of m-1 secondary operations are performed by m-1 different machines, and a hub machine is alternately visited for m primary operations. Indeed, parts must reenter the hub machine after any one of secondary operations. Those types of robotics workcells are used for high capacity production such as in photolithography manufacturing, These cells are cluster tools for semiconductor manufacturing where a wafer visits a processing stage several times for the atomic layer deposition (ALD) processes. For electroplating lines, these cells are also common in practice where there is a multifunction production stage that is visited by parts over once. This optimisation methodology is limited to the dual-gripper robotic cells, where identical parts are produced and these parts completely follow a similar sequence. The lower bound of cycle time for such dual-gripper robotic cells is obtained by finding the cycle time of all related robot move cycles, and subsequently optimal robot task sequence, which is a two-unit cycle, is determined.
A bio-inspired computational language for kinesin nanomotor
- Authors: Khataee, H. , Ibrahim, Yousef
- Date: 2012
- Type: Text , Conference proceedings
- Relation: Industrial Technology (ICIT), 2012 IEEE International Conference, Athens, Greece, 19-21 March 2012
- Full Text: false
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- Description: Kinesin nanomotor is a tiny vehicle that transports molecular cargoes within the cells. Many kinesin nanomotors can attach to a single cargo and coordinate their behaviors to transport the cargo. This behavioral coordination of kinesin nanomotors can be defined through a communicational language that kinesin nanomotors follow to transport the cargo. This paper proposes a computational language for kinesin nanomotor which is inspired by the nanomotor's natural behavior. In this technique, we have used behavioral Deterministic Finite Automaton (DFA) model of kinesin nanomotor which indicated internal intelligent and autonomous decision-making process of the nanomotor in response to its cell. In addition, the behavioral responses of kinesin nanomotor to its cell, behavioral DFA model of the nanomotor, were mapped to a computational regular language for the nanomotor. The proposed computational language for kinesin nanomotor was acceptable by the behavioral DFA model and also in good agreement with the natural behavior of the nanomotor. The development of such computational languages among intelligent and autonomous nanoparticles in nature paves the way for constructing potential bio-inspired nanorobotic systems as well as designing of some computational languages for their controlling.
Utilisation of data mining in mining industry: Improvement of the shearer loader productivity in underground mines
- Authors: Balaba, Benhur , Ibrahim, Yousef , Gunawan, Indra
- Date: 2012
- Type: Text , Conference proceedings
- Relation: Industrial Informatics (INDIN), 2012 10th IEEE International Conference, Beijing, China, 25-27 July 2012 p. 1041- 1046
- Full Text: false
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- Description: This paper presents an investigative study in which data were gathered and used in underground mining to improve the planned maintenance program and reliability of the shearer loader in the underground mining. A cost effective maintenance and operation strategy and practices is mandatory to meet the production demand and the required level of service of this critical asset of the plant. The study conducted and presented in this paper includes a detailed review of failure history data and the use of analytical technique available to understand failure characteristics and its effect on the throughput and the overall performance of the longwall operation. This is to achieve further productivity increases to meet business goals. Analytical tools such as Failure Mode and Effect and Criticality Analysis (FMECA) and Weibull analysis were used in this investigation. The study has highlighted the criticality of some failures and the actions needed in this industrial case to improve the reliability and planned maintenance for a better mining productivity.