Showing 225 results for Ai
Khatereh Rajinia, Mostafa Razmkhah,
Volume 0, Issue 0 (10-2024)
Abstract
A periodic maintenance policy through either an imperfect repair or replacement is proposed for a repairable system. It is assumed that the system is subject to an inverse Gaussian degradation process. The effect of imperfect repair is modeled through both arithmetic reduction of degradation and arithmetic reduction of age approaches. The degradation level of the system is measured after each imperfect repair in periodic time intervals. The system is replaced if its deterioration level exceeds a pre-determined technical threshold or at the nth inspection time, whichever occurs first. The main goal of the paper is to find the optimal value of n based on cost rate function. Some theoretical results are derived and then the optimal policy is obtained numerically. The effect of imperfect repair, the inspection time interval, the value of technical degradation threshold, and the costs of interest are all studied on the optimal policy.
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k. Nageswara, Bereket Haile Woldegiorgis,
Volume 0, Issue 0 (10-2024)
Abstract
So far, a number of models for measuring supply chain performance (SCP) have been proposed. The supply chain operation reference (SCOR) model has been suggested as the most important model for the manufacturing industry. However, none of the models, including the SCOR model, are complete enough for measuring the overall SCP of manufacturing firms. In practice, the SCOR model is used only in some of the many steps required to measure the overall SCP. In addition, it lacks features that enable it to determine which supply chain components have the most or least contribution to the overall SCP. Furthermore, even though the model is meant to be a reference mode-as its name implies-it does not include numerically set performance standards for the various levels of SCP achievements that may be used for benchmarking. This study develops a complete supply chain operations measurement (C-SCOM) model that has many features. It is developed mainly by combining the best features of the existing models extracted from 91 high-standard articles employing a systematic literature review (SLR) approach. The proposed model is unique in its explicitness for real-world industrial applications. It consists of four main components and provides users with the ability to calculate the overall SCP, conduct gap analysis, conduct benchmarks, and link the outputs of the gap analysis to existing supply chain management practices. Validation has been performed using the fuzzy Delphi method, with 17 experts from the manufacturing industry providing their opinions. The validation confirms that the proposed model could tackle the real problem that manufacturing firms have due to the lack of a comprehensive and user-friendly SCP measurement model. Finally, this paper contributes to the body of knowledge by presenting an alternative approach to measuring the performance of the manufacturing supply chain.
Souad Lahmine, Fatima Bennouna,
Volume 0, Issue 0 (10-2024)
Abstract
Quality 4.0 is the fusion between the long-standing quality management tenets and Industry 4.0 technologies like AI, Blockchain, IoT, and Big Data. Although it can improve product quality, control operational efficiency, and supply chain transparency for organizations, adopting these technologies comes with high challenges. This study, therefore, carries out a meta-analytic review incorporating 80 peer-reviewed papers from between 2018 to 2024 to exposit the effectiveness, challenges, and prospects of Quality 4.0. Results show that machine learning-based predictive analytics significantly reduce defect rates and production costs, while Blockchain enhances visibility into the supply chain. On the other hand, organizational readiness and workforce training are major barriers. The paper can give much-needed input to practitioners through actionable recommendations and suggest avenues for further research that would advance Quality 4.0 adoption.
Nadera Hourani,
Volume 0, Issue 0 (10-2024)
Abstract
AI has been integrated into human resource management, enabling the transformation of the field through automation of routine jobs, enhancement of decision-making, and the establishment of evidence-based strategies. The research study will systematically review the role of AI in HRM, focusing on applications related to recruitment, employee engagement, workforce planning, and retention. By analyzing ten peer-reviewed studies using advanced statistical analysis, the research underlines significant benefits of AI adoption: efficiency gains, increased employee satisfaction, and strategic workforce optimization. Yet, there are significant challenges in the form of algorithmic bias, data privacy concerns, and organizational readiness. Regression and correlation analyses show a strong positive relationship between AI use and HR performance metrics, with a greater effect on recruitment and retention. Though it has the huge potential for transformation, the findings have brought into focus the need for ethical guidelines, strong data protection, and employee upskilling for the full realization of AI's capabilities in HRM. This study provides actionable insights for organizations seeking to adopt AI technologies while addressing the associated challenges.
M. Shishehsaz ,
Volume 18, Issue 4 (12-2007)
Abstract
Abstract : The effect of a bond failure and its extent is studied on stress concentration in long fibers as well as stress distribution in short fibers and their surrounding matrix bays. The material is assumed to be a finite width hybrid composite lamina which is subjected to a tensile load of magnitude "P" at infinity. The surrounding matrix is assumed to take only shear (shear-lag theory). The bay adjacent to the first intact filament is allowed to experience a bond failure of size 2d . This failure is due to excessive shear load in the matrix which exceeds the fiber-matrix bond strength. The matrix at this zone may or may not experience yielding. The short fibers are simulated by assuming two successive breaks along each filament. The effect of bond failure length on short fiber load bearing capability, as well as stress concentration in the first intact filament is fully investigated. The effect of hybridization, in presence of bond failure is also examined on short fiber load bearing behavior.
Ali Yaran,
Volume 18, Issue 6 (7-2007)
Abstract
This paper will promote many questions about the design validity of these exciting blocks. The physical design of these blocks is prone to have social and economical problems, and it is part of the visual pollution and disturbance created on the sky line of Scottish cities special Glasgow. This paper focuses on the necessity to establish a source of initial design for high rise housing design problem classes theory. A thorough research of all the estates in Glasgow area was launched. Thus, a high amount of information was classified, in an attempt to establish a theoretical approach to support the evaluation and appraisal of current blocks problems. The new class's theory in high rise housing design problems is used as a vehicle for conducting this paper analysis. Classification includes physical and social design problems domains. The physical problems domain variables of the numbers of stories, dwellings, entrances, type of corridor, access from the streets and sharing of the site. Furthermore, to the social problems domain variables of graffiti, damage, litter, crime, drugs, child density and health have been examined. Moreover, their interdependent relationships were explored throughout the new classes' theory. The study of the new classes, theory may prove to be extremely vital for future direction in adapting some from of urban design problem solving techniques. It also serves as an evaluation tool for housing design appraisal in the city from Glasgow and similar cities worldwide.
A. Amid, S.h. Ghodsypour,
Volume 19, Issue 4 (12-2008)
Abstract
Supplier selection is one of the most important activities of purchasing departments. This importance is increased even more by new strategies in a supply chain, because of the key role suppliers perform in terms of quality, costs and services which affect the outcome in the buyer’s company. Supplier selection is a multiple criteria decision making problem in which the objectives are not equally important. In practice, vagueness and imprecision of the goals, constraints and parameters in this problem make the decision making complicated. Simultaneously, in this model, vagueness of input data and varying importance of criteria are considered. In real cases, where Decision- Makers (DMs) face up to uncertain data and situations, the proposed model can help DMs to find out the appropriate ordering from each supplier, and allows purchasing manager(s) to manage supply chain performance on cost, quality, on time delivery, etc. An additive weighted model is presented for fuzzy multi objective supplier selection problem with fuzzy weights. The model is explained by an illustrative example.
S.k. Charsoghi, A. Sadeghi,
Volume 19, Issue 4 (12-2008)
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 (12-2008)
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.
H. Teimory, H. Mirzahosseinian, A. Kaboli,
Volume 19, Issue 4 (12-2008)
Abstract
The advent of e-commerce has prompted many manufacturers to redesign their traditional channel structure by engaging in direct sales. In this paper, we present a dual channel inventory model based on queuing theory in a manufacturer-retailer supply chain, consisting of a traditional retail channel and a direct channel which stocks are kept in both upper and lower echelon. The system receives stochastic demand from the both channel which each channel has an independent demand arrival rate. A lost-sales model which no backorder is allowed is supposed. The replenishment lead times are assumed independent exponential random variables for both warehouse and the retail store. Under the replenishment inventory policy, the inventory position is kept constant at a base-stock level. To analyze the chain performance, an objective function included holding and lost sales costs is defined. At the end, a proposed algorithm named, Best Neighborhood (BN) is used to find a good solution for inventory and the results are compared with Simulated Annealing (SA) solutions.
R. Sadeghian, G.r. Jalali-Naini, J. Sadjadi, N. Hamidi Fard ,
Volume 19, Issue 4 (12-2008)
Abstract
In this paper Semi-Markov models are used to forecast the triple dimensions of next earthquake occurrences. Each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. Semi-Markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. In Semi-Markov models each zone can be considered as a state of proposed Semi-Markov model. At first proposed Semi-Markov model is explained to forecast the three mentioned dimensions of next earthquake occurrences. Next, a zoning method is introduced and several algorithms for the validation of the proposed method are also described to obtain the errors of this method.
F. Rashidinejad, M. Osanloo , B. Rezai ,
Volume 19, Issue 5 (7-2008)
Abstract
Cutoff grade is a grade used to assign a destination label to a parcel of material. The optimal cutoff grades depend on all the salient technological features of mining, such as the capacity of extraction and of milling, the geometry and geology of the orebody, and the optimal grade of concentrate to send to the smelter. The main objective of each optimization of mining operation is to maximize the net present value of the whole mining project, but this approach without consideration of environmental issues during planning is not really an optimum design. Lane formulation among the all presented algorithms is the most commonly used method for optimization of cutoff grades. All presented models for optimum cutoff grades are ore-oriented and in none of them the costs related to waste materials which must to be minimized during the mine life are considered. In this paper, after comparison of traditional and modern approaches for cutoff grade optimization in open pit mines, a real case study is presented and discussed to ensure optimality of the cutoff grades optimization process.
F. Sereshki, S.a. Hosseini, N. Aziz , I. Porter ,
Volume 19, Issue 5 (7-2008)
Abstract
The Outburst can be defined as a sudden release of coal and rock accompanied by large quantities of gas into the underground coal mine workings which represents a major hazard in underground coal mines. Gas drainage has been proven to be successful in reducing outburst hazards by decreasing the in-situ gas pressure. One of aspect of gas drainage from coal seams is coal matrix volume changes. Current study is primarily concerned with experimental studies related to coal volume change (coal shrinkage) under various gas types and pressures. Two types of tests were conducted on each sample, the adsorption test for coal swelling and the desorption test for coal shrinkage. The gases used in the study were CH4, CO2, CH4/CO2 (50-50% volume), and N2. In this research, tests were conducted with respect to volumetric change behavior in different gases and their corresponding comparative results were presented.
A.d. Akbari, M. Osanloo , M.a. Shirazi ,
Volume 19, Issue 5 (7-2008)
Abstract
Planning and design procedure of an open pit mining project just can be started after ultimate pit determination. In the carried out study in this paper it was shown that the most important factor in ultimate pit determination and in consequence in the whole planning and design procedure of an open pit mine is the metal price. Metal price fluctuations in recent years were exaggerated and imposed a high degree of uncertainty to the mine planning procedure while none of the existent algorithms of the pit limit determination consider the metal price uncertainty. Real Option Approach (ROA) is an efficient method of decision making in the condition of uncertainty. This approach usually used for evaluation of defined natural resources projects up to now. This study considering the metal price uncertainty used real option approach to prepare a methodology for determining the Ultimate Pit Limits (UPL). The study was carried out on a non-ferrous metallic cylindrical ore deposit but the achieved methodology can be adjusted for all kinds of the deposits. The achieved methodology was comprehensively described through the examples in a way that can be used by the mine planners.
N. Parvini Ahmadi, T. Czerwiec ,
Volume 19, Issue 5 (7-2008)
Abstract
Low temperature plasma assisted nit riding treatments of 316 stainless steel produce a complex layer constituted by tow different metastable f.c.c. solid solution denoted ( γ N1 and γ N2 ). About the formation of these double layers, different hypothesis was proposed in the literature. For verifying these hypotheses, the effects of differentes conditions such as nit riding temperature, cleaning and nit riding duration and cooling state have been studied. The results show that γ N2 sub layer produce during the ion bombardment cleaning procedure, before the nit riding treatment. Also the formation of the γ N2 layer is not connected to the cooling state of the sample after nit riding treatment.
M. Riahi , M. Ansarifard ,
Volume 19, Issue 7 (8-2008)
Abstract
In this research, the life expectancy of ball bearings in industrial applications is estimated based on known parameters. The overall mathematical calculation of such behavior is based on the theory of Lundberg and Palmgren. The proposed life estimation equation however lacks certain points to make it qualified as universal. A firm conclusion therefore could not be obtained on the basis of this equation alone, particularly when different operating conditions are involved. One such example is the life of ball bearings while operating in clean lubricant environment, which is approximately up to 20 times longer than the calculated life based on the previously prescribed equations. On the other hand, active life under contaminated lubricants is nearly close to one-tenth of the calculated life originally thought to be correct .
L. Garooci Farshi, A. H. Mosafa , S. M. Seyed Mahmoudi ,
Volume 19, Issue 7 (8-2008)
Abstract
The exhaust gases of gas turbine power plant carry a significant amount of thermal energy that is usually expelled to the atmosphere this causes a reduction in net work and efficiency of gas turbine. On the other hand, the generated power and efficiency of gas turbine plants depend largely on the temperature of the inlet air, So that they both increase as the inlet air temperature decreases. The mentioned two problems can be solved by installing an absorption refrigeration cycle (ARC) at gas turbine inlet, working with thermal energy of exhaust gases. In this research, effect of inlet air cooling on gas turbine performance is studied. The work shows that, the net work and the efficiency will increase by 6-10% and 1-5% respectively for every 10°C decrease of inlet temperature. Since, coefficient of performance (COP) of ARC is low, with high pressure ratios in simple gas turbine (SGT) and with low pressure ratios in regenerative gas turbine (RGT), thermal energy of exhaust gases can not supply all the needed thermal energy for refrigeration cycle. The results show that, when an ejector is included in refrigeration cycle, the need for external energy source required for refrigeration cycle is reduced .
M. Rafeeyan ,
Volume 19, Issue 7 (8-2008)
Abstract
In this paper a non-diagonal regulator, based on the QFT method, is synthesized for an uncertain MIMO plant whose output and control signals are subjected to hard time-domain constraints. This procedure includes the design of a non-diagonal pre-controller based on a new simple approach, followed by the sequential design of a diagonal QFT controller. We present a new formulation for the latter stage, which shows the role of off-diagonal elements in the design procedure. A numerical example is given to illustrate the effectiveness of the proposed method .
Kamran Shahanaghi, Hamid Babaei , Arash Bakhsha,
Volume 20, Issue 1 (5-2009)
Abstract
In this paper we focus on a continuously deteriorating two units series equipment which its failure can not be measured by cost criterion. For these types of systems avoiding failure during the actual operation of the system is extremely important. In this paper we determine inspection periods and maintenance policy in such a way that failure probability is limited to a pre-specified value and then optimum policy and inspection period are obtained to minimize long-run cost per time unit. The inspection periods and maintenance policy are found in two phases. Failure probability is limited to a pre-specified value In the first phase, and in the second phase optimum maintenance thresholds and inspection periods are obtained in such a way that minimize long-run expected.
S. G. Jalali Naini , M. B. Aryanezhad, A. Jabbarzadeh , H. Babaei ,
Volume 20, Issue 3 (9-2009)
Abstract
This paper studies a maintenance policy for a system composed of two components, which are subject to continuous deterioration and consequently stochastic failure. The failure of each component results in the failure of the system. The components are inspected periodically and their deterioration degrees are monitored. The components can be maintained using different maintenance actions (repair or replacement) with different costs. Using stochastic regenerative properties of the system, a stochastic model is developed in order to analyze the deterioration process and a novel approach is presented that simultaneously determines the time between two successive inspection periods and the appropriate maintenance action for each of the components based on the observed degrees of deterioration. This approach considers different criteria like reliability and long-run expected cost of the system. A numerical example is provided in order to illustrate the implementation of the proposed approach.
