Showing 20 results for K.
F.d. Javanroodi , K. M. Nikbin ,
Volume 17, Issue 3 (IJES 2006)
Abstract
There is an increasing need to assess the service life of components containing defect which operate at high temperature. This paper describes the current fracture mechanics concepts that are employed to predict cracking of engineering materials at high temperatures under static and cyclic loading. The relationship between these concepts and those of high temperature life assessment methods is also discussed. A model for predicting creep crack growth initiation and growth in terms of C* and the creep uniaxial ductility is presented and it is shown that this model gives good agreement with the experimental results. The effects of cyclic loading on crack growth behaviour are considered and fractography evidence is shown to back a simple cumulative damage concept when dealing with creep/fatigue interaction. Finally a discussion is presented which highlights the important aspect of life assessment methodology for high temperature plant.
M. Nikian, , M. Naghashzadegan, S. K. Arya ,
Volume 17, Issue 3 (IJES 2006)
Abstract
The cylinder working fluid mean temperature, rate of heat fluxes to combustion chamber and temperature distribution on combustion chamber surface will be calculated in this research. By simulating thermodynamic cycle of engine, temperature distribution of combustion chamber will be calculated by the Crank-Nicolson method. An implicit finite difference method was used in this code. Special treatments for piston movement and a grid transformation for describing the realistic piston bowl shape were designed and utilized. The results were compared with a finite element method and were verified to be accurate for simplified test problems. In addition, the method was applied to realistic problems of heat transfer in an Isuzu Diesel engine, and gave good agreement with available experimental.
K. Maleknejad , M. Rabbani ,
Volume 18, Issue 1 (International Journal of Engineering 2007)
Abstract
Abstract: There are some methods for solving integro-differential equations. In this work, we solve the general-order Feredholm integro-differential equations. The Petrov-Galerkin method by considering Chebyshev multiwavelet basis is used. By using the orthonormality property of basis elements in discretizing the equation, we can reduce an equation to a linear system with small dimension. For numerical examples, the solutions may be produced with good accuracy, by choosing suitable trial and test spaces in Petrov-Galerkin method.
K. Farhadi ,
Volume 18, Issue 4 (International Journal of Engineering 2007)
Abstract
Abstract: This paper presents the results of an experimental examination of the effect of non-uniform wall temperature on local heat transfer coefficient in a rotating smooth-walled square channel. Three different thermal boundary situations were investigated: (a) even and odd (four) wall uniform temperature, (b) even and odd (four) wall uniform heat flux, and (c) even (leading and trailing) walls hot with two side walls kept cold. It is demonstrated that the local heat transfer coefficients on the trailing edge are much higher than that of the leading edge. For situation (a) of even (leading and trailing) walls with two sides uniform temperature, the leading edge heat transfer coefficient decreases and then increases with increasing rotational numbers. And the trailing edge heat transfer coefficient increases monotonically with rotational numbers increasing. However, the trailing edge as well as the side walls heat transfer coefficient for situation (b) is higher than situation (a) and the leading edge local heat transfer coefficients for situations (b) and (c) are significantly higher than situation (a). The obtained results suggest that the local non-uniform wall temperature creates the local buoyancy force that diminishes the effect of the Coriolis force. Consequently, the local heat transfer coefficients on leading, trailing, and side edges are affected by the wall non-uniform temperature.
A. Allahverdi, K. Mehrpour , E. Najafi Kani,
Volume 19, Issue 3 (International Journal of Engineering 2008)
Abstract
Abstract: In recent years, many research works have been done to investigate the possibility of utilizing a broad range of materials as raw materials in the production of geopolymer cements. The use of artificial pozzolans or aluminosilicate-type industrial waste materials such as granulated blast-furnace slag and fly ash has been reported in many research works. Natural pozzolans are also aluminosilicate-type materials which can be activated with solutions of NaOH and Na2SiO3. Using a pumice-type natural pozzolan from Taftan Mountain located at the south east of Iran and different alkali-activators based on combinations of Na2SiO3 and NaOH, a number of natural-pozzolan-based geopolymer cement systems were designed and prepared. Final setting time, workability, and 28-day compressive strength of the systems were studied. The results obtained reveal that Taftan pozzolan can be activated using a proportioned mixture of Na2SiO3 and NaOH resulting in the formation of a geopolymer cement system exhibiting suitable workability and relatively high 28-day compressive strengths up to 63 MPa.
S.k. Charsoghi, A. Sadeghi,
Volume 19, Issue 4 (IJIE 2008)
Abstract
In this paper, a two-echelon supply chain, which includes two products based on the following considerations, has been studied and the bullwhip effect is quantified. Providing a measure for bullwhip effect that enables us to analyze and reduce this phenomenon in supply chains with two products is the basic purpose of this paper. Demand of products is presented by the first order vector autoregressive time series and ordering system is established according to order up to policy. Moreover, lead-time demand forecasting is based on moving average method because this forecasting method is used widely in real world. Based on these assumptions, a general equation for bullwhip effect measure is derived and there is a discussion about non-existence of an explicit expression for bullwhip effect measure according to the present approach on the bullwhip effect measure. However, bullwhip effect equation is presented for some limited cases. Finally, bullwhip effect in a two-product supply chain is analyzed by a numerical example.
K. Shahanaghi, V.r. Ghezavati,
Volume 19, Issue 4 (IJIE 2008)
Abstract
In this paper, we present the stochastic version of Maximal Covering Location Problem which optimizes both location and allocation decisions, concurrently. It’s assumed that traveling time between customers and distribution centers (DCs) is uncertain and described by normal distribution function and if this time is less than coverage time, the customer can be allocated to DC. In classical models, traveling time between customers and facilities is assumed to be in a deterministic way and a customer is assumed to be covered completely if located within the critical coverage of the facility and not covered at all outside of the critical coverage. Indeed, solutions obtained are so sensitive to the determined traveling time. Therefore, we consider covering or not covering for customers in a probabilistic way and not certain which yields more flexibility and practicability for results and model. Considering this assumption, we maximize the total expected demand which is covered. To solve such a stochastic nonlinear model efficiently, simulation and genetic algorithm are integrated to produce a hybrid intelligent algorithm. Finally, some numerical examples are presented to illustrate the effectiveness of the proposed algorithm.
M. Ghazanfari, K. Noghondarian, A. Alaedini,
Volume 19, Issue 4 (IJIE 2008)
Abstract
Although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. Identifying the real time of the process changes is known as change-point estimation problem. There are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. In this paper we propose a novel approach based on clustering techniques to estimate Shewhart control chart change-point when a sustained shift is occurrs in the process mean. For this purpose we devise a new clustering mechanism, a new similarity measure and a new objective function. The proposed approach is not only capable of detecting process change-points, but also automatically estimates the true values of the out-of-control parameters of the process. We also compare the performance of the proposed approach with existing methods.
T.b. Pankhania, V.k. Modi,
Volume 22, Issue 3 (IJIEPR 2011)
Abstract
For any organization sound marketing strategy and quality assurance play vital role in the growth of the organization. The price, quality and service, service centers, friendly attitude, Discounts on sales, esthetics, store location and appearance, ease of operations, guarantees and warranties, adopting new ideas, and flexible payments terms were considered to study the perceptions of the respondents. The ultimate aim is to uphold the turnover of the organization and to create good market penetration of the goods produced in highly competitive business world .
P.k Shahabadkar, J.s Sujit Kumar , K.s Prashant ,
Volume 22, Issue 4 (IJIEPR 2011)
Abstract
There has been a recent development and explosion of interest among academicians across a wide range of disciplines in the use of virtual Class room. Utilization of the virtual class room as a laboratory experimentation for teaching and learning has increased significantly in recent years as development tools for web based applications have become easier to use and computers have become more capable and less expensive. But, does the virtual class-room improve students learning? Herein we describe the results of two experiments conducted on sections of a Manufacturing and Operation Management course [MIME - 3240] at one of the Colleges of Technology in the Sultanate of Oman during fall semester. Two experiments were designed to determine if student learning of Manufacturing and Operation Management course was significantly affected by two treatments: 1) Virtual class room environment for the students of section S2 and 2) Real Class-room environment for students of section S1. The actual final scores of students of section S1 and S2 were compared in order to determine the effectiveness of virtual class room on student learning for the Manufacturing and Operation Management course.
In this study Web-based virtual Class room (WVC) is developed to communicate, to share and to disseminate knowledge from the teacher to student. Further, in this study web based tools are also used to create, store, and manage contents of class room instructions and course material .
Ali Bonyadi Naeini, Barat Mojaradi, Mehdi Zamani, V.k. Chawla,
Volume 30, Issue 3 (IJIEPR 2019)
Abstract
The frequency of chronic diseases such as cardiovascular diseases has significantly increased in recent years. This study is a developmental research which is categorized as descriptive-survey in terms of data collection method. The aim of this study is to prioritize 22 districts of Tehran for the purpose of prevention from cardiovascular diseases. In the present study, after extraction of the effective factors on the prevalence of cardiovascular diseases from previous studies, the weight of each factor with their specific data for each 22 districts of Tehran (collected from relevant organizations) is obtained using two levels of Fuzzy Delphi method and one level of fuzzy best-worst method, for confirming or denying factors and weighting them based on the opinion of 25 cardiologists, respectively, and transferred to Arc GIS software for prioritizing 22 districts of Tehran.Using a combination of fuzzy best-worst method, which is one of the newest methods for making multi-criteria decision, and GIS, for weighting parameters and prioritizing 22 districts of Tehran, gives an acceptable worth to the present study.Our results-after classification, drawing, and combination of maps- indicated that the 8th district (except a little part in the west) is the best district, and 16th and 19th districts (approximately whole district) are in the last priority for prevention of cardiovascular diseases. Other districts respectively placed in the second to 21th places.
Dr V.k. Chawla, A.k. Chanda, Surjit Angra,
Volume 31, Issue 1 (IJIEPR 2020)
Abstract
The selection of an appropriate cutting tool for the production of different jobs in a flexible manufacturing system (FMS) can play a pivotal role in the efficient utilization of the FMS. The selection procedure of a cutting tool for different production operations becomes more significant with the availability of similar types of tools in the FMS. In order to select and allocate appropriate tool for various production operations in the FMS, the tool selection rules are commonly used. The application of tool selection rules is also observed to be beneficial when a system demands two or more tools for the production operations at different work centers at the same time in the FMS. In this paper, investigations are carried out to evaluate the performance of different tool selection rules in the FMS. The performance of the tool selection rules is evaluated by simulation with respect to different performance parameters in the FMS namely makespan, mean work center utilization (%) and mean automatic tool transporter (ATT) utilization (%).
K.v Krishnamraju,
Volume 31, Issue 2 (IJIEPR 2020)
Abstract
Now a days majority of commerce is taken place in electronic form. The e commerce transactions can be happened mainly in three forms. They are C2C(customer to customer), B2B(Business to business) and B2C(business to customer). Out of these B2C type of e-commerce is the most important one. Therefore there is a need of a secure protocol for performing B2C type of e-commerce transactions. The B2C type the main participating entities are customers, website and merchant. In this paper the communication between the website and merchant is represented by WM protocol. The design of WM protocol must consider several issues like problem definition, services, environment, vocabulary and message formats. The verification of WM protocol is also performed with respect to the protocol procedure rules based on linear temporal logic. The procedure rules related to the protocol is specified in process meta language. The verification is performed by using SPIN model checker and corresponding results are reported.
P Subbaraju, K. Chandra Sekhar, P.r.s.s.v. Raju, K. Satyanarayana Raju, M. K. S. Varma,
Volume 31, Issue 2 (IJIEPR 2020)
Abstract
Nowadays, data are the food for the digital world. The main rich sources for data generated by social networks such as Twitter, Face book, Instagram, and LinkedIn. The data generated from micro-blogging services are plays a vital role in business intelligence like product reviews, movie reviews, election results prediction by social media data analysis. Sentiment analysis (SA) is the key method of predicting netizens emotions behind the text expressed in social media. The main motto of this survey to give complete idea about tools and the techniques used in Sentiment Analysis and the relevant fields with brief details.
K.v.k Sasikanth, K. Samatha, N. Deshai, B. V. D. S. Sekhar, S. Venkatramana,
Volume 31, Issue 3 (IJIEPR 2020)
Abstract
The Today’s interconnected world generates huge digital data, while millions of users share their opinions, feelings on various topics through popular applications such as social media, different micro blogging sites, and various review sites on every day. Nowadays Sentiment Analysis on Twitter Data which is considered as a very important problem particularly for various organizations or companies who want to know the customers feelings and opinions about their products and services. Because of the data nature, variety and enormous size, it is very practical for several applications, range from choice and decision creation to product assessment. Tweets are being used to convey the sentiment of a tweeter on a specific topic. Those companies keeping survey millions of tweets on some kind of subjects to evaluate actual opinion and to know the customer feelings. This paper major goal would be to significantly collect, recognize, filter, reduce and analyze all such relevant opinions, emotions, and feelings of people on different product or service could be categorized into positive, negative or neutral because such categorization improves sales growth about a company's products or films, etc. We initiate that the Naïve Bayes classifier be the mainly utilized machine learning method for mining feelings from large data like twitter and popular social network because of its more accuracy rates. In this paper, we scrutinize sentiment polarity analysis on Twitter data in a distributed environment, known as Apache Spark.
Sangapu Venkata Appaji, R Shiva Shankar, K.v.s. Murthy, Chinta Someswara Rao,
Volume 31, Issue 3 (IJIEPR 2020)
Abstract
Cancer is a consortium of diseases which comprises abnormal increase in cells growth by having potential to occupy and attack the entire body. According to study breast cancer is the most likely occurs in the women and which became the second biggest cause of women death. Due to its wide spread and importance some of the researchers work on this, but still there is a need to improvement. During this work in order to partially fulfill this proposed technique of deep learning along with RNN in predicting breast cancer disease which will help the doctor while diagnosis the patient. To assess the efficiency of the proposed method we used breast cancer data belong to UC Irvine repository. Precision, recall, accuracy and f1 score of proposed method shows good scores and proposed technique performs well Consortium
A.k.v.k Sasikanthr, K. Samatha, N. Deshai, B.v.d.s Sekhar, S. Venkatramana,
Volume 32, Issue 1 (IJIEPR 2021)
Abstract
The Today’s digital world computations are tremendously difficult and always demands for essential requirements to significantly process and store enormous size of datasets for wide variety of applications. Since the volume of digital world data is enormous, this is mostly generated unstructured data with more velocity at beyond the limits and double day by day. In last decade, many organizations have been facing major problems to handling and process massive chunks of data, which could not be processed efficiently due to lack of enhancements on existing and conventional technologies. In this paper address, how to overcome these problems as efficiently by using the most recent and world primary powerful data processing tool, which is hadoop clean open source and one of the core component called Map Reduce, but which has few performance issues. This paper main goal is address and overcome the limitations and weaknesses of Map Reduce with Apache Spark.
Sundaramali G., Santhosh Raj K., Anirudh S., Mahadharsan R., Senthilkumaran Selvaraj,
Volume 32, Issue 3 (IJIEPR 2021)
Abstract
One of the goals of the manufacturing industry in the globalisation era is to reduce defects. Due to a variety of factors, the products manufactured in the industry may not be defect-free. Six Sigma is one of the most effective methods for reducing defects. This paper focuses on implementing Six Sigma in the automobile industry's stator motor shaft assembly. The high decibel noise produced by the stator motor is regarded as a rejected piece. Six Sigma focuses on continuous improvement and aids in process optimization by identifying the source of the defect. In the Six Sigma process, the problem is measured and analysed using various tools and techniques. Before beginning this case study, its impact on the company in terms of internal and external customer cost savings is assessed. This case study was discovered to be in a high-impact area. The issue was discovered during the Core and Shaft pressing process. Further research leads to dimensional tolerance, which reduces the defect percentage from 16.5 percent to 0.5 percent.
Tesfaye K. Torban, Mathewos Ensarmu, Chala Dechassa,
Volume 34, Issue 3 (IJIEPR 2023)
Abstract
Environmental sustainability is a growing concern for businesses and organizations due to climate change trends. This study aims to examine the direct impact of institutional pressures, green procurement (GP), and reverse logistics (RL) on environmental performance (EVP). The mediating influences of RL and GP on institutional pressure and EVP are also examined. The study uses a quantitative method where data is gathered from the CEO, operations, human resources, logistics, and procurement managers of 165 industrial park firms using customized questionnaires. The data is analyzed using the PLS-SEM software (SmartPLS 4). The results suggest that the adoption of institutional pressures has a significant effect on GP and RL, and the findings show that GP does not improve EVP. However, the implementation of RL mediates the relationship between institutional pressure and EVP. The study develops a comprehensive empirical model that tests the joint influence of institutional pressure- GP-RL-EVP model was developed and validated. The findings indicate that institutional pressure and RL help firms advance EVP.
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k.nageswara, Bereket Haile Woldegiorgis,
Volume 35, Issue 2 (IJIEPR 2024)
Abstract
Ethiopia has made enormous efforts in the leather industry to gain manufacturing capabilities that can be scaled up to other sectors. Those efforts have resulted in the industry shifting its role from raw material supplier to producer of value-added products for the global supply chain (GSC). However, the industry has faced severe challenges in generating the expected revenue, utilizing capacity, and finally coping with the global competitive environment. Studies reveal that manufacturing firms tackle similar challenges by improving their supply chain performance (SCP). The challenges that appeared in the leather industry of Ethiopia could also be solved by improving its SCP. Nonetheless, there is a lack of study on the basic characteristics and SCP of the industry after it has shifted its role. The main objective of this study is, therefore, to measure the SCP to know where it stands using a bench mark and identify the elements that contribute considerably to the low overall SCP in order to lay the foundation for subsequent improvement. To achieve the research objective, data was collected from primary and secondary sources through a questionnaire, survey, observation, and focus group discussion. The data is analyzed using the supply chain operations reference model (SCOR version 12.0). Accordingly, the overall SCP is found to be 67.33%, suggesting an average rating as per the set benchmark. The source process is identified as the most influential element for the overall low SCP, with a percentage gap of 17.23%. Taking corrective action on the identified elements could help the industry overcome the existing challenges by improving its SCP.
