DECISION SUPPORT MODEL IN FAILURE-BASED COMPUTERIZED MAINTENANCE MANAGEMENT SYSTEM FOR SMALL AND MEDIUM INDUSTRIES

Maintenance decision support system is crucial to ensure maintainability and reliability of equipments in production lines. This thesis investigates a few decision support models to aid maintenance management activities in small and medium industries. In order to improve the reliability of resources in production lines, this study introduces a conceptual framework to be used in failure-based maintenance. Maintenance strategies are identified using the Decision-Making Grid model, based on two important factors, including the machines’ downtimes and their frequency of failures. The machines are categorized into three downtime criterions and frequency of failures, which are high, medium and low. This research derived a formula based on maintenance cost, to re-position the machines prior to Decision-Making Grid analysis. Subsequently, the formula on clustering analysis in the Decision-Making Grid model is improved to solve multiple-criteria problem. This research work also introduced a formula to estimate contractor’s response and repair time. The estimates are used as input parameters in the Analytical Hierarchy Process model. The decisions were synthesized using models based on the contractors’ technical skills such as experience in maintenance, skill to diagnose machines and ability to take prompt action during troubleshooting activities. Another important criteria considered in the Analytical Hierarchy Process is the business principles of the contractors, which includes the maintenance quality, tools, equipments and enthusiasm in problem-solving. The raw data collected through observation, interviews and surveys in the case studies to understand some risk factors in small and medium food processing industries. The risk factors are analysed with the Ishikawa Fishbone diagram to reveal delay time in machinery maintenance. The experimental studies are conducted using maintenance records in food processing industries. The Decision Making Grid model can detect the top ten worst production machines on the production lines. The Analytical Hierarchy Process model is used to rank the contractors and their best maintenance practice. This research recommends displaying the results on the production’s indicator boards and implements the strategies on the production shop floor. The proposed models can be used by decision makers to identify maintenance strategies and enhance competitiveness among contractors in failure-based maintenance. The models can be programmed as decision support sub-procedures in computerized maintenance management systems

Collective Approach for Repair time Analysis

Machine downtime can be defined as a total amount of time the machine would normally be out of service from the moment it fails until the moment it is fully repaired and back to operate. Once a unit experiences a service downtime or downgrade, the covariates or risk factors can directly impact on the delay in repairing activities. Our study reveals the model to identify the potential risk factors that either delay or accelerate repair times, and it also demonstrates the extent of such delay, attributable to specific risk factors. Once risk factors are detected, the maintenance planners and maintenance supervisors are aware of the starting and finishing points for each repairing job due to their prior knowledge about the potential barriers and the facilitators. There are not many sufficient studies made on the application of artificial intelligence techniques to access troubleshooting activities as it always taken into consideration in a verbal sense and yet is not dealt with mathematically. The proposed study extended Choy, John, Thomas & Yan [1] models using either semi-parametric or non-parametric approaches of reliability analysis to examine the relationship between repair time and various risk factors of interest. Then the models will be embedded to neural networks to provide better estimation of repairing parameters. The proposed models can be used by maintenance managers as a benchmarking to develope quality service to enhance competitiveness among service providers in corrective maintenance field. Also the models can be deployedfarther to develop a computerized decision support system

A Costing Analysis For Decision Making Grid Model In Failure-Based Maintenance

In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for computerized maintenance management system

Contractor selection for maintenance in Small and Medium Industries using Analytical Hierarchy Process

The research based on the fact that the investment of information technology is needed for supporting daily operation and maintenance management in commonly industries. Although many models with varieties optimization and techniques have been proposed, there are limited actions to be linked into the actual industrial maintenance process. This paper introduce Analytical Hierarchical Process (AHP) method to provide important maintenance decision strategy for Small and Medium Industries (SMIs). The method is suitable for maintenance decision based on multiple maintenance criteria’s and their alternatives. In case study, the maintenance contractor’s selection problem have been demonstrated and the best decision result using maintenance decision support been achieved. The goal of this paper is to illustrate on how SMIs can use AH

Computerized Maintenance Management System for Food Processing Industries

Breakdown define as total amount of time the equipment would normally be out of operation from the moment it fails until the moment it is fully repaired and operational. Depending on these nature of the breakdown, some maintenance activities may take place before the service is restored into their normal operation. Downtimes of productions unit may result capacity loss, poor product quality, customer dissatisfaction and environmental impact. In fact, these downtimes can be forecasted and managed more effectively if an organization takes preemptive measures using artificial intelligence techniques such as data mining, neural networks, genetic algorithm etc. This will provide good estimate to predict next failures. The proposed research project reveals the risk factors that either delay or accelerate downtimes. It also demonstrates the extent of such delay, attributable to specific risk factors. Once risk factors are detected, the maintenance managers are aware of the starting and finishing points for each maintenance job due to their prior knowledge about the potential barriers or covariates. We develop a prototype of the Computerized Maintenance Management System (CMMS) as a tool for maintenance management team, which consist of work order, preventive maintenance, corrective maintenance and inventory control system

Logic Algorithm for contour following task: An evaluation using Adept SCARA Robot

This paper presents the performance evaluation of logic algorithms for contourfollowing task in order to automate the manual programming process. The main objective of this work is to evaluate and compare the performance of single logic and dual sensor logic algorithmsfor autonomous contourfollowing in industrial robot. Thosi atgorithms have been implemented using Adept SCAM robot. The algorithms were tested on a semicircle object o/ 40 millimeter radius. The result shows mean of error and standard deviation value of single logic algorithm is a bit lower than clual sensar logic algorithtn

An Improved Decision Making Grid Model to Identify Maintenance Strategies

Manufacturing industries in developing economies must produce marketable products and always meet the standards expected by their customers. This requires the investment in technology management in supporting daily operation and maintenance. Whenever there is a huge number of machines in production lines, then there will be a heavy duty of the maintenance activities. This paper shows on how to carry out computations for calculating frequency of failures and downtimes using Decision Making Grid (DMG). Then extend the theoretical and formulation in DMG using tri-quadrant approach to cluster and categorize the variables. Real dataset on machines maintenance in manufacturing industry is used to test and show the results

A Review of Optimization Models and Techniques for Maintenance Decision Support Systems in Small and Medium Industries

There are not many sufficient studies made on the application of artificial intelligence techniques to access troubleshooting activities as it always taken into consideration in a verbal sense and yet is not dealt with mathematically. The proposed study extended Choy, John, Thomas & Yan [1] models using either semi-parametric or non-parametric approaches of reliability analysis to examine the relationship between repair time and various risk factors of interest. Then the models will be embedded to neural networks to provide better estimation of repairing parameters. The proposed models can be used by maintenance managers as a benchmarking to develope quality service to enhance competitiveness among service providers in corrective maintenance field. Also the models can be deployed farther to develop a computerized decision support syste

Cognitive Radio Platforms For Disaster Response Networks, Survey

Either natural or man-made a disaster is defined as unexpected destructive event that causes damages and malfunction of existing systems and services all around the disaster area, these destructive effects are unfortunately beyond the capability of local authorities to recover and respond immediately, the disaster recovery plans are immediately initiated so that rescue and aid operations can help those who are trapped in disaster area to survive, those efforts need to be controlled and coordinated with reliable communication systems that are more likely partially or fully disabled due to the disaster, the capabilities of cognitive radio technology enables it to play a significant role in providing efficient communication services for the rescue teams and headquarters as well as trapped victims, in this paper, we survey the cognitive radio architectures that can replace the Software Defined Radio SDR in order to reduce the network expenses in terms of network size and network computational complexit

A Review of Optimization Models and Techniques for Maintenance Decision Support Systems in Small and Medium Industries

The research is based on the fact that decision support systems (DSSs) is needed for maintenance process in commonly industries. Many maintenance functions with varieties optimization models and techniques have been proposed for solving the problems. The aim of this research was to identify those optimization models and techniques to conduct maintenance decision support system in small and medium industries (SMIs). A systematic literature review was performed to gather relevant information. The results shown several trends related in the fields area. Next, the research direction has been suggested to develop the systems