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Showing 10 results for Rahman

Rahman Farnoosh, Behnam Zarpak,
Volume 19, Issue 1 (International Journal of Engineering 2008)
Abstract

  Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we have learned Gaussian mixture model to the pixels of an image. The parameters of the model have estimated by EM-algorithm.

  In addition pixel labeling corresponded to each pixel of true image is made by Bayes rule. In fact, we introduce a new numerically method of finding maximum a posterior estimation by using EM-algorithm and Gaussians mixture distribution. In this algorithm, we have made a sequence of priors, posteriors and they converge to a posterior probability that is called the reference posterior probability. Maximum a posterior estimated can determine by the reference posterior probability that will make labeled image. This labeled image shows our segmented image with reduced noises. We show this method in several experiments.


M. Jahir Bin Alam, M.a. Ansery, R.k Chowdhuary, J. Uddin Ahmed, S. Islam , S. Rahman ,
Volume 19, Issue 3 (International Journal of Engineering 2008)
Abstract

Abstract: Sylhet is the northeastern region of Bangladesh and probability of earthquake in Sylhet is higher than other areas of this zone. Among 27 wards, Ward no. 14 is one of the important largest Wards in Sylhet city and a densely populated one. It was clear from the survey works, 42.8% buildings are belongs to Building with RCC frame 54.03% buildings are Masonry buildings. Another interesting finding is 325 houses fall in the category of Houses with resident 1-10. The occurrence of an earthquake of PGA value 0.9g on ward no. 14 causes massive loss of lives and damage to buildings. Depending on the time of the day 147 to 603 people may be killed due to structural collapse and the buildings of worth approximately TK.32.00 core may be damaged.


Mahdi Karbasian, Mohammad Farahmand, Mohammad Ziaei,
Volume 26, Issue 2 (IJIEPR 2015)
Abstract

This research aims at presenting a consolidated model of data envelopment analysis (DEA) technique and value engineering to select the best manufacturing methods for gate valve covers and ranking the methods using TOPSIS.To do so, efficiency evaluation indices were selected based on the value engineering approach and different manufacturing methods were evaluated using DEA technique.Finally, effective methods were ranked based on TOPSIS. Accordingly, 48 different methods were identified for manufacturing the part. The DEA results showed that only 12 methods have complete efficiency. Meanwhile manufacturing method No. 32 (A216 WCB casting purchased from Chinese market as the raw material, machining by CNC+NC and drilling by radial drill) was ranked the first.Major limitations of the research include time limitations, place limitation, lack of access to the standards adaptability index in different machining and drilling methods, limitation on evaluating all parts of a product, limitation on a technique evaluating efficiency and ranking, and mere satisfying with superior indices in each factor of value engineering. Most previous studies only evaluated efficiency of manufacturing methods based on a single approach.By applying value engineering, which is in fact a combination of three approaches (including quality approach, functional, and cost approaches), the present research provided a far more comprehensive model to evaluate manufacturing methods in industrial.

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Armaghn Shadman, Ali Bozorgi-Amiri, Donya Rahmani,
Volume 28, Issue 2 (IJIEPR 2017)
Abstract

Today, many companies after achieving improvements in manufacturing operations are focused on the improvement of distribution systems and have long been a strong tendency to optimize the distribution network in order to reduce logistics costs that the debate has become challenging. Improve the flow of materials, an activity considered essential to increase customer satisfaction. In this study, we benefit cross docking method for effective control of cargo flow to reduce inventory and improve customer satisfaction. Also every supply chain is faced with risks that threaten its ability to work effectively. Many of these risks are not in control but can cause great disruption and costs for the supply chain process. In this study we are looking for a model to collect and deliver the demands for the limited capacity vehicle in terms of disruption risk finally presented a compromised planning process. In fact, we propose a framework which can consider all the problems on the crisis situation for decision-making in these conditions, by preparing a mathematical model and software gams for the following situation in a case study. In the first step, the results presented in mode of a two-level planning then the problem expressed in form of a multi-objective optimization model and the results was explained.


Gholamreza Gholampour, Abdul Rahman Bin Abdul Rahim, Faezeh Gholampour,
Volume 29, Issue 4 (IJIEPR 2018)
Abstract

Nowadays, automakers have faced complexity of supply chain that have to improve procedures and processes in order to access high performance in both strategic and operational. The main purpose of this research is to evaluate model of strategic performance of supply chain (SPSC), which include information technology (IT), organizational learning (OL), and Product innovation (PRI) via qualitative research. In fact, this research follows how these factors effect on SPSC. IRANKHODRO Company (IKCO) as the biggest automaker in Middle East is our case study in order to research and evaluate mentioned model. A total number of 12 interviews were done based on a list of semi-structured open-ended questions in order to evaluate constructs and model. The development of constructs in IKCO according to respondents’ opinion was classified at three categories including high, medium and low levels. In high level, IT has been developed in IKCO more than another constructs, which consists of development of ORACLE system, SAP and KANBAN in order to cover information, procedures and processes across supply chain. While SPSC has been developed less than others.
 
Mehrdad Jalali Sepehr, Abdorrahman Haeri, Rouzbeh Ghousi,
Volume 30, Issue 4 (IJIEPR 2019)
Abstract

Abstract
Background: In this paper healthcare condition of 31 countries that are the members of Organization for Economic and Co-operative Development (OECD) is measured by considering 14 indicators that are relevant to three main pillars of sustainable development.
Method: To estimate the efficiency scores, Principle Component Analysis-Data Envelopment Analysis PCA-DEA additive model in both forms of envelopment and multiplier is used to determine efficiency scores and also to define benchmarks and improvement plan for the inefficient countries. Then Decision Tree Analysis is also used to realize that which factors were the most influential ones to make a county an efficient Decision Making Unit (DMU).
Results: According to the PCA-DEA additive model, among 31 OECD countries, 16 countries have become inefficient, that USA have taken the lowest efficiency score, and among efficient countries Iceland could be considered as a paragon which has the highest frequency between the countries that are defined as the benchmarks. Decision tree analysis also show that exposure to PM2.5 is an influential factor on the efficiency status of countries.
Conclusion: This research gives an insight about the sustainable development and healthcare system and show the impressive effect of environmental and social factors like: exposure to PM2.5 and water quality, population insurance coverage, and AIDS on the healthcare efficiency of OECD countries
Seyed Mohammad Ghadirpour, Donya Rahmani, Ghorbanali Moslemipour,
Volume 31, Issue 2 (IJIEPR 2020)
Abstract

It is indispensable that any manufacturing system is consistent with potential changes such as fluctuations in demand. The uncertainty also makes it more essential. Routing Flexibility (RF) is one of the necessities to any modern manufacturing system such as Flexible Manufacturing System (FMS). This paper suggests three mixed integer nonlinear programming models for the Unequal–Area Stochastic Dynamic Facility Layout Problems (UA–SDFLPs) by considering the Routing Flexibility. The models are proposed when the independent demands follow the random variable with the Poisson, Exponential, and Normal distributions. To validation of the proposed models, many small-sized test problems has solved that derived from a real case in literature. The large-sized test problems are solved by the Genetic Algorithm (GA) at a reasonable computational time. The obtained results indicate that the discussed models for the UA–SDFLPs are valid and the managers can take these models to the manufacturing floor to adapt to the potential changes in today's competitive market.
 
Iwa Kustiyawan, Mas Rahman Roestan, Catur Riani,
Volume 34, Issue 4 (IJIEPR 2023)
Abstract

This research aims to identify the initial OEE (Overall Equipment Efficiency) values on automated packaging machines with a 2d barcode track and trace system. Quantitative research methods used to obtain the OEE value, analysis of factors affecting the OEE values, developing a strategy to make improvements, and evaluate these strategies on the level of machine productivity. The importance of the subject lies in the need to improve the efficiency and productivity of pharmaceutical packaging processes. The pharmaceutical industry is facing increasing pressure to optimize operations and reduce waste. Implementing effective performance measurement tools such as Overall Equipment Effectiveness (OEE) can help identify areas for improvement and enhance productivity. This study found that the track-and-trace system was below the company's standard, indicating room for improvement. Then, countermeasures were implemented to increase productivity and machine effectiveness, and the initial OEE value of the automated packaging machine with 2D barcodes improved. Thus, this study demonstrated the effectiveness of the proposed framework in evaluating and improving OEE in pharmaceutical packaging processes, highlighting the significance of digitalization and automation technologies in enhancing productivity.

Welly Sugianto, Reazul Haq Abdul Haq, Mohd Nasrull Bin Abdol Rahman,
Volume 35, Issue 1 (IJIEPR 2024)
Abstract

The automobile workshop queue system has been optimized using various approaches, such as queuing theory, simulation, and probability. The utilization of response surface methodology (RSM) for optimizing automobile workshop queue systems is not yet established. The utilization of RSM with direct observation enables the detection of patterns of correlations between variables and responses, which are then represented through mathematical equations. The optimization process involves numerous factors that impact queue performance, which can be categorized into two parts. The number of servers, number of phases, number of workers, worker experience, and layout are classified in inner design. This study examines the relationship between two components of the outer design, specifically the arrival rate and the interarrival time. The responses analyzed are queue cost, service time, average customer waiting time, and number of customers. The findings indicate that queue costs are not reliable for establishing the optimum value due to the significant impact of the cost structure on the structure of the optimal location. This study discovered that the number of leaving customers is related to queue costs and is relevant in selecting the optimal point. This study also formulates mathematical equations for predicting the optimal point. This study emphasizes the necessity for further investigation to uncover alternative mathematical equations that can precisely predict the optimal conditions for various types of services.

Hana Catur Wahyuni, Rahmania Sri Untari, Rima Azzara, Marco Tieman, Diva Kurnianingtyas,
Volume 35, Issue 4 (IJIEPR 2024)
Abstract

This research discusses the application of the Failure Mode and Effect Analysis (FMEA) method in designing a blockchain system for mitigating food safety and halal risks in the beef supply chain. The complexity of the meat supply chain involving various parties increasing the risk of contamination and changes in the halal status of the meat. This research aims to identify food safety and halal risks, prioritise the risks, and design blockchain-based mitigation solutions. Blockchain was chosen for its advantages in providing high transparency and accountability, enabling real-time tracking at every stage of the supply chain. The research results show that most of the risks in the meat supply chain fall into the low category, but there are some critical medium risks, especially related to the slaughtering process. The proposed blockchain design includes product traceability features, halal certification, temperature monitoring, and smart contracts to ensure automatic validation of food safety and halal compliance. The implementation of this blockchain is expected to increase consumer trust in meat products, reduce the risk of contamination, and strengthen accountability throughout the meat supply chain.

 

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