M. Yousef Ibrahim

New technique of mobile robot navigation using a hybrid adaptive fuzzy-potential field approach

This paper presents a summary of the research aimed at developing a new reliable methodology for robot navigation and obstacle avoidance. This new approach is based on the artificial potential field (APF) method, which is used extensively for obstacle avoidance. The classical APF is dependent only on the separation distance between the robot and the surrounding obstacles. The new scheme introduces a variable, which is used to determine the importance that each obstacle has on the robots future path. The importance variable is dependent on the obstacles position, both angle and distance, with respect to the robot. Simulation results are presented demonstrating the ability of the algorithm to perform successfully in simple environments.

On Reliability Evaluation of Multistate Weighted -out-of- System Using Present Value

A new reliability evaluation methodology for multistate weighted k-out-of-n systems is presented in this article. The present value of the cash flow generated by the system components is used as a reliability value. We take a financial view of reliability and consider functioning periods and the time value of money in system reliability analysis. Two approaches, the universal generating function (UGF) and recursive algorithm, are applied to evaluate the reliability of the multistate weighted k-out-of-n system. An illustrative example is calculated based on the proposed system reliability evaluation methodology. It is shown that this evaluation method can also be used to find the value of the maintenance policy. Finally, the UGF and recursive algorithm approaches are compared with each other for large system reliability assessment.

Data-Driven System Reliability and Failure Behavior Modeling Using FMECA

System reliability modeling needs a large amount of data to estimate the parameters. In addition, reliability estimation is associated with uncertainty. This paper aims to propose a new method to evaluate the failure behavior and reliability of a large system using failure modes, effects, and criticality analysis (FMECA). Therefore, qualitative data based on the judgment of experts are used when data are not sufficient. The subjective data of failure modes and causes have been aggregated through the system to develop an overall failure index (OFI). This index not only represents the system reliability behavior, but also prioritizes corrective actions based on improvements in system failure. In addition, two optimization models are presented to select optimal actions subject to budget constraint. The associated costs of each corrective action are considered in risk evaluation. Finally, a case study of a manufacturing line is introduced to verify the applicability of the proposed method in industrial environments. The proposed method is compared with conventional FMECA approach. It is shown that the proposed method has a better performance in risk assessment. A sensitivity analysis is provided on the budget amount and the results are discussed.

Investigation on system reliability optimization based on classification of criteria

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.

Applying UGF concept to enhance the assessment capability of FMEA

The purpose of this paper is to propose a modified version of Failure Mode and Effects Analysis (FMEA) to alleviate its drawbacks. FMEA is an important tool in risk evaluation and finding the priority of potential failure modes for corrective actions. In the proposed method, the Universal Generating Function (UGF) approach has been used to improve the assessment capability of the conventional Risk Priority Number (RPN) in ranking. The new method is named as URPN. It generates the most number of unique values in comparison with the previous methods and considers relative importance for the parameters while it is easy to compute. More unique numbers help to avoid from having the same priority level for different failure modes which represent various risk levels. A case study has been employed to demonstrate that the URPN not only can improve the shortcomings but also is able to provide accurate values for risk assessment. Copyright

Notes on Feasibility and Optimality Conditions of Small-Scale Multifunction Robotic Cell Scheduling Problems With Pickup Restrictions

Optimization of robotic workcells is a growing concern in automated manufacturing systems. This study develops a methodology to maximize the production rate of a multifunction robot (MFR) operating within a rotationally arranged robotic cell. An MFR is able to perform additional special operations while in transit between transferring parts from adjacent processing stages. Considering the free-pickup scenario, the cycle time formulas are initially developed for small-scale cells where an MFR interacts with either two or three machines. A methodology for finding the optimality regions of all possible permutations is presented. The results are then extended to the no-wait pickup scenario in which all parts must be processed from the input hopper to the output hopper, without any interruption either on or between machines. This analysis enables insightful evaluation of the productivity improvements of MFRs in real-life robotized workcells.

Scheduling dual gripper robotic cells with a hub machine

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.

Utilisation of data mining in mining industry: Improvement of the shearer loader productivity in underground mines

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.

Development of an adaptive fuzzy behavioural control system with experimental and industrial applications

This paper discusses a newly developed Adaptive Fuzzy Behavioural Control System which has been designed for use with an autonomous mobile robot. The merit of the system is the capability to adapt the fuzzy function to suit the environmental conditions encountered without changes to the rule base. This is compared to conventional behavioural control and demonstrated by simulation. The paper also discuses the results of both experimental and industrial applications in which this new control system was applied.

Robotization of coal harvesting in open cut lignite mines

Presents a summary of research which is currently being conducted at Monash University ‐ Gippsland Campus. The research aims at the automation of coal harvesting at a major Australian open cut mine. This mine is located at Morwell, Victoria and produces brown coal (lignite). The coal from this mine contributes significantly to the power generation in Victoria. The research aims to provide a computer assisted remote operation of mining machines and services. Also, this research aims at developing an intelligent unmanned mining system using robotics technology. Also discusses the method of robotizing such a mine for maximum economic efficiency and the proposed control configuration for the system. Describes the current automation project, which is to achieve the required alignment between the robotized mining machine and the hopper by employing a reactive/adaptive fuzzy control system for maximum economic efficiency.