Scheduling
N. MD. Sarfaraj; Md. L. R. Lingkon; N. Zahan
Abstract
The continuous growth of the population causes an increased demand for our healthcare services. Insufficient hospitals face challenges to serve the patient within a preferable duration. Long lines in front of counters increase the processing time of a patient. From the entry to the completion, plenty ...
Read More
The continuous growth of the population causes an increased demand for our healthcare services. Insufficient hospitals face challenges to serve the patient within a preferable duration. Long lines in front of counters increase the processing time of a patient. From the entry to the completion, plenty of time waste just for unscheduled hospital management system. Job shop scheduling is an optimization process in which jobs are assigned with maintain a particular sequence. In this paper, we proposed flexible job shop scheduling to solve this type of problem by considering patients as job and test counter as machine for the optimization of the processing time and increase the efficiency of a hospital or a clinic. Genetic Algorithm was used to analyze the processing time for multiple counter of a hospital for a stable and effective scheduling. The results showed that an optimized makespan was generated and patients could fulfill their needs much quickly after applying flexible job shop scheduling.
Operations Research
Kizito Paul Mubiru; Maureen Nalubowa Ssempijja
Abstract
The paper considers a modelling framework for a set of households in residential areas using electricity as a form of energy for domestic consumption. Considering the demand and availability of units for electricity consumption, optimal decisions for electricity load allocation are paramount to sustain ...
Read More
The paper considers a modelling framework for a set of households in residential areas using electricity as a form of energy for domestic consumption. Considering the demand and availability of units for electricity consumption, optimal decisions for electricity load allocation are paramount to sustain energy management. We formulate this problem as a stochastic decision-making process model where electricity demand is characterized by Markovian demand. The demand and supply phenomena govern the loading and operational framework, where shortage costs are realized when demand exceeds supply. Empirical data for electricity consumption was collected from fifty households in two residential areas within the suburbs of Kampala in Uganda. Data collection was made at hourly intervals over a period of four months. The major problem focussed on determining an optimal electricity loading decision to minimize consumption costs as demand changes from one state to another. Considering a multi-period planning horizon, an optimal decision was determined for loading or not loading additional electricity units using the Markov decision process approach. The model was tested, and the results demonstrated the existence of optimal state-dependent decision and consumption costs considering the case study used in this study. The proposed model can be cost-effective for managers in the electricity industry. Improved efficiency and utilization of resources for electricity distribution systems to residential areas were realized, with subsequently enhanced service reliability to essential energy market customers.
Banking industry
Keivan Goodarzi; Mohammadreza Kashefi Neishabori; Abdollah Naami; Mojtaba Dastoori
Abstract
The current research has been done pursuing the goal to present a content marketing model with brand improving approach in banking industries. This study is applied in terms of goal and survey- exploratory concerning the approach. The statistical community is made up of a group of experts including the ...
Read More
The current research has been done pursuing the goal to present a content marketing model with brand improving approach in banking industries. This study is applied in terms of goal and survey- exploratory concerning the approach. The statistical community is made up of a group of experts including the senior executives of the banking industries, academic faculty in marketing and marketing consultants acquainted with the banking industries who were posed in-depth interview. Selecting the experts and their interviews continued until reaching theoretical saturation and then stopped. In this research, snowball sampling method was used and this process continued until the researcher reaching theoretical saturation. And ultimately, the study finished with interviewing 9 experts. Since the data-driven theory has been utilized in this research, collecting the data has been mainly done by in-depth and unstructured interview. Finally, after three steps known as open, axial and selective coding, the conceptual model has been designed based on the paradigm model.
Data Envelopment Analysis, DEA
Sarvar Sadat Kassaei; Farhad Hosseinzadeh Lotfi; Alireza Amirteimoori; Mohsen Rostamy-Malkhalifeh; Bijan Rahmani
Abstract
Congestion is one of the important concepts in data envelopment analysis that occurs when excessive inputs reduce the maximally possible outputs. Identification and elimination of congestion have a significant impact on reducing inputs along with increasing outputs. Hence, various studies have been conducted ...
Read More
Congestion is one of the important concepts in data envelopment analysis that occurs when excessive inputs reduce the maximally possible outputs. Identification and elimination of congestion have a significant impact on reducing inputs along with increasing outputs. Hence, various studies have been conducted to detect and evaluate congestion. However, in today's world, no organization can achieve its final output with just one process of input. In other words, today's organizations have a network structure that consists of several subsections. Ignoring the existing influences among the subsections processes may lead to inadequate or even incorrect results for evaluating the congestion. While all of the existing methods only evaluate the congestion of each subsection or the whole system independently. Therefore, in this paper, the concept of congestion is developed for a specific and so practical case of network structure called “two-stage network structure”. This case of network structure consists of two series stage such that stage 1 consume some primary inputs to produce some intermediate outputs. In the following, the intermediate outputs are used as the inputs of stage 2 to produce the final output. Here, the concept of congestion is defined for systems with a two-stage structure. Then, to examine the congestion of each stage as well as the congestion of the whole system, a single linear programming model is proposed. The validity of the proposed model is investigated using several theorems and it is shown that the new definition is a generalization of the previous definitions of the congestion for the black-box systems. Finally, the proposed model is applied to a case study including 24 non-life insurance companies in Taiwan.
Industrial Management
E. Shadkam; F. Ghavidel
Abstract
The use of assembly lines is one of the important approaches in mass production of industrial products. Imbalance of assembly lines increases cycle time and idle times, resulting in reduced production rates, line efficiency, and increased system costs, which ultimately lead to low productivity. A hybrid ...
Read More
The use of assembly lines is one of the important approaches in mass production of industrial products. Imbalance of assembly lines increases cycle time and idle times, resulting in reduced production rates, line efficiency, and increased system costs, which ultimately lead to low productivity. A hybrid model assembly line is a type of production line on which various models of products are assembled. These assembly lines are increasingly accepted in the industry in order to overcome the diversity of customer demand. The hybrid model assembly line is able to respond quickly to sudden changes in demand for different models of a product without maintaining a large inventory.The purpose of this paper is to present a multi-objective integer linear mathematical programming model for balancing assembly lines, which is solved using the general criteria method. The three objective functions considered in this model are: (1) Minimizing cycle time (2) Minimize the idle time of each station and (3) increase the efficiency of the assembly line. In order to investigate the model, Iran-Shargh Neishabour Company has been considered as a case study. After implementing the proposed model of the paper, the results show the optimal performance of the proposed model and the studied parameters in line balancing have been significantly improved.
Data mining
Abdolmajid Imani; Meysam Abbasi; Farahnaz Ahang; Hassan Ghaffari; Mohamad Mehdi
Abstract
Accurate identification, attracting, and keeping the customers particularly loyal Customer Relationship Management (CRM) with the goal of optimum allotment of resources and achievement to higher profit is not a competitive profit, but it is a life persistence necessity of companies in virtual space. ...
Read More
Accurate identification, attracting, and keeping the customers particularly loyal Customer Relationship Management (CRM) with the goal of optimum allotment of resources and achievement to higher profit is not a competitive profit, but it is a life persistence necessity of companies in virtual space. One of the challenges of companies in this part is how to identify the customer’s traits and the separation of different segments of them. Now Customer Lifetime Value (CLV) is the comparison priority in the segmentation of customers to congruous segments. The main goal of this research is to identify key or strategic customers using the RFM model. In this part after determining the amount of Recency, Frequency and Monetary (RFM) in, registered transactions of one store in Iran (Refah Chain Store) at a time about seven months from 23 September 2017 to 20 April 2018 (71161 transactions as final inputs were used), the weight of each variable according to the fuzzy Analytic Hierarchy Process (AHP) was determined. At the next stage customers using the K-means and Two-step’s algorithms were clustered and K-means the method according to the Silhouette index was the better algorithm of this letter. According to the results, customers were segmented into three parts and CLV was calculated and for identifying key or strategic customer segmentation, the clustering process was repeated and priorities of all clusters were indicated. Results of data analysis are below: Segment 3: customers of this segment were 3425 members and 11.5% of all company customers were the most loyal customers those are identified as golden customer's segment and all of the variables were higher than average of all data. This research identified the valuable customers for the shop, and it gives them a chance to choose goal customers and invest in them.
Operations Research
Hamiden Abd El-Wahed Khalifa; Dragan Pamučar; Seyyed Ahmad Edalatpanah
Abstract
The current study investigates to characterize the Complex Programming Problem (CPP) solution in a fuzzy environment. The paper is divided into two parts: 1) the first presents a Fuzzy Complex Programming Problem (F-CPP) with fuzzy complex constraints, and 2) the second presents the optimality criteria ...
Read More
The current study investigates to characterize the Complex Programming Problem (CPP) solution in a fuzzy environment. The paper is divided into two parts: 1) the first presents a Fuzzy Complex Programming Problem (F-CPP) with fuzzy complex constraints, and 2) the second presents the optimality criteria using the fuzzy complex cone. The CPP is suggested by involving fuzzy numbers in the constraints in parts. Using the cut set concepts, the problem is converted into the complex programming. A number of basic theorems with proofs are established concerning the basic results for the fuzzy complex set of solutions for the F-CPP, and the optimality criteria of the saddle point for F-CPP with fuzzy cones is derived.
Engineering Optimization
Sh. Ghasemi; A. Aghsami; M. Rabbani
Abstract
Data Envelopment Analysis (DEA) is one of the non-parametric methods for evaluating each unit's efficiency. Limited resources in the healthcare system are the main reason for measuring the efficiency of hospitals. Because Operating Rooms (OR) are the most vital part of any hospital, we determine the ...
Read More
Data Envelopment Analysis (DEA) is one of the non-parametric methods for evaluating each unit's efficiency. Limited resources in the healthcare system are the main reason for measuring the efficiency of hospitals. Because Operating Rooms (OR) are the most vital part of any hospital, we determine the factors affecting operating rooms' efficiency and evaluate the performance and ranking of operating rooms in 10 of Tehran's largest hospitals. This model's inputs include accuracy in scheduling surgeries, average turnover time, number of successful surgeries and live patients, number of canceled surgeries, number of surgical errors, and number of emergency surgery. Also, outputs consist of the number of operating rooms and equipment, the average number of beds, the number of employees, and the patient satisfaction rate. First, we determine the weight of inputs and outputs by Group Analytic Hierarchy Process (GAHP) with considering experts' ideas in 10 hospitals; then, we utilize three types of DEA model which are input-oriented CCR (CCR-I), output-oriented CCR (CCR-O), input-output oriented CCR (CCR_IO) and AP models to estimate the efficiency of ORs and rank them.
Machine Learning
Mohammad Reza Nazabadi; Seyed Esmaeil Najafi; Ali Mohaghar; Farzad Movahedi Sobhani
Abstract
Adopting an integrated production, maintenance, and quality policy in production systems is of great importance due to their interconnected influence. Consequently, investigating these aspects in isolation may yield an infeasible solution. This paper aims to address the joint optimal policy of production, ...
Read More
Adopting an integrated production, maintenance, and quality policy in production systems is of great importance due to their interconnected influence. Consequently, investigating these aspects in isolation may yield an infeasible solution. This paper aims to address the joint optimal policy of production, maintenance, and quality in a two-machine-single-product production system with an intermediate buffer and final product storage. The production machines have degradation levels from as-good-as-new to the breakdown state. The failures increase the production machine's degradation level, and maintenance activities change the status to the initial state. Also, the quality of the final product depends on the level of degradation of the machines and the correlation between the degradation level of the production machines and the product's quality in the case that high degradation of the previous production machines leads to a high probability to produce wastage by the following machines is considered. The production system studied in this research has been modeled using the agent-based simulation, and the Reinforcement Learning (RL) algorithm has obtained the optimal integrated policy. The goal is to find an integrated optimal policy that minimizes production costs, maintenance costs, inventory costs, lost orders, breakdown of production machines, and low-quality production. The meta-heuristic technique evaluates the joint policy obtained by the decision-maker agent. The results show that the acquired joint policy by the RL algorithm offers acceptable performance and can be applied to the autonomous real-time decision-making process in manufacturing systems.
Supply chain management
Sirous Balaei; Nabiollah Mohammadi; Homa Doroudi
Abstract
Due to the importance of environmental effects of manufacturing system in recent decades, the production systems are obliged to comply different environmental regulations. The present research, aims to design a green supply chain model for Guilan steel industry with a hybrid approach. This study is applied ...
Read More
Due to the importance of environmental effects of manufacturing system in recent decades, the production systems are obliged to comply different environmental regulations. The present research, aims to design a green supply chain model for Guilan steel industry with a hybrid approach. This study is applied research in term of purpose, exploratory in term of method, quantitative and qualitative in terms of data type. A researcher made questionnaire are applied, in addition to interview, for data gathering. The under-study research population includes steel industry experts out of them, 12 experts were selected for data gathering phase. Conducting the research, first applying fuzzy Delphi method, 5 main factors and 25 important sub-factors were identified. Then, using fuzzy DEMATEL and interpretive structural modeling (ISM) methods, the importance of each facto was determined, in which two factors "external environment study" and "internal environment study" were at the highest level of the importance, while "Waste reduction", "waste recycling" and "purchasing based on environmental products" were at the last level. These variables are interrelated and affect their next levels.
Data mining
Shookoofa Mostofi; Sohrab Kordrostami; Amir Hossein Refahi; Marzieh Faridi Masooleh; Soheil Shokri
Abstract
Existing systems for diagnosing heart disease are time consuming, expensive, and prone to error. In this regard, a diagnostic algorithm has been proposed for the causes of heart disease based on a frequent pattern with the B-mine algorithm optimized by association rules. Initially, a data set of disease ...
Read More
Existing systems for diagnosing heart disease are time consuming, expensive, and prone to error. In this regard, a diagnostic algorithm has been proposed for the causes of heart disease based on a frequent pattern with the B-mine algorithm optimized by association rules. Initially, a data set of disease is used to select a feature, so that it deals with a set of training features. Then, association rules are used to classify educational and experimental sets, and then the factors affecting heart disease are analyzed. The numerical results from the experiments of real and standard datasets of cardiac patients show that the average accuracy of the proposed method is approximately 98%, which has been tested on the Cleveland database that includes 76 features in the case of heart disease dataset, 14 features of which are related to heart disease. This paper also uses four common categories such as decision tree to build the model. The data set studied in this article contains 270 records as well as 14 features. The accuracy of predicting the results of the support vector machine classifications, k nearest neighbor, decision tree and simple Bayesian is 81.11%, 66.67%, 59.72% and 19.85%, respectively, which are relatively satisfactory results.
Supply chain management
Artaphon Chansamut
Abstract
The research about information system model for educational management in supply chain for Thai higher education institutions. The objectives of research to design and to assess the suitability of an information system model for educational management in supply chain for Thai higher education institutions. ...
Read More
The research about information system model for educational management in supply chain for Thai higher education institutions. The objectives of research to design and to assess the suitability of an information system model for educational management in supply chain for Thai higher education institutions. The sample group consisted of ten experts in the field of information system, supply chain and curriculum. The data is analyzed by means and standardized deviations statistically. The research result shows that information system model for educational management in supply chain for Thai higher education institutions is consisted of 7 key elements which are 1) main elements, 2) raw materials, 3) suppliers, 4) manufacturer, 5) service provider, 6) finished product, and 7) customers. The results from experts’ agreement information system model for educational management in supply chain for Thai higher education institutions was a high level. It showed that information system model for educational management in supply chain for Thai higher education institutions could be used to develop information system.
Case studies in industry and services
Ali Ehsani; Hassan Mehrmanesh; Mahmoud Mohammadi
Abstract
This study aims to identify and prioritize the effect of technology capability drivers on the supply chain performance of automotive companies. Technology capability indicators are ranked and prioritized using the fuzzy hierarchical analysis technique. The research method is applied in terms of purpose, ...
Read More
This study aims to identify and prioritize the effect of technology capability drivers on the supply chain performance of automotive companies. Technology capability indicators are ranked and prioritized using the fuzzy hierarchical analysis technique. The research method is applied in terms of purpose, is described as the data collection method, and is considered quantitative research. After reviewing the theoretical literature of the research, the drivers of technology capability on the organization's performance were identified for prioritization; they were weighed by a number of experts in the field of automotive companies using questionnaires and fuzzy hierarchical analysis. Indicators and sub-indices of variable technology capability were ranked and prioritized. Based on the results of this research model, it was found that of the eight indicators examined, "strategic technology capability", "product technology capability", and "supplier technology" was the most important, and of the 38 technology capability sub-indicators examined, "Technology Development" is the most important.
Machine Learning
Parvaneh Afzali; Abdoreza Rezapour; Ahmad Rezaee Jordehi
Abstract
The authentication of writers through handwritten text stands as a biometric technique with considerable practical importance in the field of document forensics and literary history. The verification process involves a meticulous examination of the questioned handwriting in comparison to the genuine ...
Read More
The authentication of writers through handwritten text stands as a biometric technique with considerable practical importance in the field of document forensics and literary history. The verification process involves a meticulous examination of the questioned handwriting in comparison to the genuine handwriting of a known writer, aiming to determine whether a shared authorship exists. In real-world scenarios, writer verification based on the handwritten text presents more challenges compared to signatures. Signatures typically consist of fixed designs chosen by signers, whereas textual content can vary and encompass a diverse set of letters, numbers, and punctuation marks. Moreover, verifying a writer based on limited handwritten texts, such as a single word, is recognized as one of authentication's open and challenging aspects. In this paper, we propose a Customized Siamese Convolutional Neural Network (CSCNN) for offline writer verification based on handwritten words. Additionally, a combined loss function is employed to achieve more accurate discrimination between the handwriting styles of different writers. The designed model is trained with pairs of images, each comprising one authentic and one questioned handwritten word. The effectiveness of the proposed model is substantiated through experimental results obtained from two well-known datasets in both English and Arabic, IAM and IFN/ENIT. These results underscore the efficiency and performance of our model across diverse linguistic contexts.
Industrial Mathematics
Evgeny L. Pankratov
Abstract
In this paper we introduce an approach to increase density of field-effect transistors framework a C-multiplier. Framework the approach we consider manufacturing the inverter in heterostructure with specific configuration. Several required areas of the heterostructure should be doped by diffusion or ...
Read More
In this paper we introduce an approach to increase density of field-effect transistors framework a C-multiplier. Framework the approach we consider manufacturing the inverter in heterostructure with specific configuration. Several required areas of the heterostructure should be doped by diffusion or ion implantation. After that dopant and radiation defects should by annealed framework optimized scheme. We also consider an approach to decrease value of mismatch-induced stress in the considered heterostructure. We introduce an analytical approach to analyze mass and heat transport in heterostructures during manufacturing of integrated circuits with account mismatch-induced stress.
Game theory
Javid Ghahremani Nahr; Mirreza Zahedi
Abstract
The design of a repurchase agreement related to the amount of goods remaining in the two-echelon supply chain between the retailer and the manufacturer is examined. Two scenarios are considered quite separately; In the first scenario (decentralized) in which the retailer determines the price of the product ...
Read More
The design of a repurchase agreement related to the amount of goods remaining in the two-echelon supply chain between the retailer and the manufacturer is examined. Two scenarios are considered quite separately; In the first scenario (decentralized) in which the retailer determines the price of the product and the optimal amount of the economic order and the producer is persuaded to follow this method. In the second (centralized) scenario, the goal is to maximize the profit of the whole chain, in which case the price of the product and the amount of the economic order are determined based on the profit of the whole chain. Then, a model of repurchase agreement related to the remaining goods was considered based on cooperative play and contract between two members of the supply chain, in which the goal is to maximize the profit of chain members. Due to the uncertainty of the competitive environment, the demand is considering under uncertain in modeling to determine the optimal level of cooperation in a competitive and cooperative market. The results of the implementation of this contract in a numerical example showed that the profit of the whole chain and the amount of economically optimal order in the centralized state increased compared to the decentralized state and the optimal price of the product decreased. Due to the fact that in the decentralized state the retailer determines the values of the optimal variables, the profit of this member decreases in the centralized state and the producer's profit increases.
Manufacturing and Logistics
Hamid Saffari; Morteza Abbasi; Jafar Gheidar-Kheljani
Abstract
In recent years, responsiveness in the Supply Chain Network (SCN) has been considered to improve competitiveness because customers are the most significant part of a supply chain, and promptly meeting customer demand is substantial. In this article, to deal with the technological risks, the Reinforcement ...
Read More
In recent years, responsiveness in the Supply Chain Network (SCN) has been considered to improve competitiveness because customers are the most significant part of a supply chain, and promptly meeting customer demand is substantial. In this article, to deal with the technological risks, the Reinforcement Policy (RP) before the disruption and the Assets-Sharing (AS) policy before and after the disruption has been used as Resilience Policies for Disruption (RPD). Also, the responsiveness of the network, as well as the risks associated with AS, have been considered in mathematical modeling. In addition, Lateral Sending (LS), delivery time deviations, and penalties for lost sales for increasing customer satisfaction in the cost objective function are considered responsiveness policies. A solution method has been developed based on the augmented ɛ-constraint to solve the model. Finally, the results show an improvement in cost by up to 14% and responsiveness by up to 17% by using the proposed policies, as well as the effectiveness of the developed technique to cope with the Multi-Objective (MO) model.
Human factors, ergonomics, and safety
Mobasshira Zaman
Abstract
Optimization and selecting effective design parameters are a big issue in the field of product design and development. The optimal value determination for design parameters is a challenge for the furniture industry. Therefore, an appropriate statistical approach is required. In this research the full ...
Read More
Optimization and selecting effective design parameters are a big issue in the field of product design and development. The optimal value determination for design parameters is a challenge for the furniture industry. Therefore, an appropriate statistical approach is required. In this research the full factorial two-level four-factor design of experiment method was used to determine the optimal values for a shape changeable furniture. For the m-chair’s- which can be used as a chair, floor bed, and table, four design parameters- bending axis material surface roughness, density of body material, width of the surface plane, and the number of bending axis were evaluated on basis of the performance time of shape changing where the optimal value of influential parameters were determined for a minimum reshaping time using Minitab. This method can be implemented for unique product design. But for further study, different form changing times should be considered individually.
Operations Research
Chokri Ben Salem; Walid Meslameni
Abstract
Bending is a sheet forming operation in excess of the elasticity limit of the material. Currently, in the industry, bending operation is carried out by a successive test method in order to have the geometry of the part, which generates the operation quite long and too expensive. In fact, springback brings ...
Read More
Bending is a sheet forming operation in excess of the elasticity limit of the material. Currently, in the industry, bending operation is carried out by a successive test method in order to have the geometry of the part, which generates the operation quite long and too expensive. In fact, springback brings about geometric changes in the folded parts. This phenomenon affects the angle and radius of curvature and can be primarily influenced by multiple factors. In this work, we predict the springback during the air v-bending procedure with the finite element calculation software ABAQUS to pass the test on the first try. The simulation parameters followed the real setting taking into account the characteristics of the punch and the die of the hydraulic press. The simulation was then checked using experimental tests and analytical models, we study this particular springback in 1050A Aluminum specimens through the analytical models of Gardiner and Queener. As a final result, the springback comparison effect between simulation and experiment is presented, and the evaluation of the experimental results with those of the simulation and theoretical models is conclusive. The simulated data show good agreement with the experimental and the analytical models the Finite Element Method (FEM) is a reliable tool for the analysis and simulation of the air v-bending process of Aluminum 1050 A sheet.
Data Envelopment Analysis, DEA
Abbasali Monzeli; Behrouz Daneshian; Gasem Tohidi; Shabnam Razavian; Masud Sanei
Abstract
We extend the concept of returns to scale in Data Envelopment Analysis (DEA) to the weight restriction environments. By adding weight restrictions, the status of returns to scale, i.e. increasing, constant, and decreasing, may need a change. We first define "returns to scale" underweight restrictions ...
Read More
We extend the concept of returns to scale in Data Envelopment Analysis (DEA) to the weight restriction environments. By adding weight restrictions, the status of returns to scale, i.e. increasing, constant, and decreasing, may need a change. We first define "returns to scale" underweight restrictions and propose a method for identifying the status of returns to scale. Then, we demonstrated that this addition would usually narrow the region of the most productive scale size (MPSS). Finally, for an inefficient decision-making unit (DMU), we will present a simple rule for determining the status of returns to the scale of its projected DMU. Here, we carry out an empirical study to compare the proposed method's results with the BCC model. In addition, we demonstrate the change in the MPSS for both models. We have presented different models of DEA to determine returns to scale. Here, we suggested a model that determines the whole status to scale in decision-making units.Different models of DEA to determine returns to scale are presented. Here, we suggested a model that determines the whole status to scale in decision-making units.
Total quality management and quality engineering
Supriyati Supriyati; Tri Ngudi Wiyatno
Abstract
SMEs is one of the pillars that can improve people's lives and is very meaningful for the government. In order for SMEs to continue to develop, even increase, it is necessary to measure service quality and customer satisfaction so that SMEs can identify weaknesses in their business as evaluation material. ...
Read More
SMEs is one of the pillars that can improve people's lives and is very meaningful for the government. In order for SMEs to continue to develop, even increase, it is necessary to measure service quality and customer satisfaction so that SMEs can identify weaknesses in their business as evaluation material. The research method begins by reviewing the literature related to the SMEs service industry, classifying, choosing what is appropriate for this research. The results of the research show that several methods can be used to measure, analyze, evaluate, and develop products. The KANO method with functional dysfunction assessment to identify customer desires based on attributes can have a significant influence on customer satisfaction. Servqual with a 5 gap analysis model for customer satisfaction analysis, IPA can be used to measure, test, analyze and determine service priority improvements, while QFD is broader. In addition to evaluating the quality of services and products, it is also for development or innovation and is not limited to the service industry but can be used to develop products for the manufacturing industry. Every business needs to be evaluated to improve performance, several approaches such as KANO, Servqual, IPA, QFD can be used as a reference for measuring, evaluating and developing to continue to improve and develop the business.
Management Sciences
Buşra Taşkan; Buket Karatop
Abstract
As well as social and cultural life, commercial life has also been affected by the industrial revolutions. Because the structures of enterprises have changed how their performance is evaluated, have indispensably changed. In today's brutally competitive environment, it is of great importance that enterprises ...
Read More
As well as social and cultural life, commercial life has also been affected by the industrial revolutions. Because the structures of enterprises have changed how their performance is evaluated, have indispensably changed. In today's brutally competitive environment, it is of great importance that enterprises constantly assess their performance so that they can maintain their existence firstly and achieve sustainable competitive advantage. Due to the current importance of the topic in this study, it was examined how the field of organizational performance has developed in the Industry 4.0 period. The purpose of this study is to reveal whether Industry 4.0 and the field of organizational performance show parallelism in terms of evolution. This parallelism was examined in terms of use of the artificial intelligence techniques in organizational performance evaluation methods. Therefore, available literature related the topic was reviewed by way of the Systematic Literature Review (SLR) protocol developed by Boell and Cecez-Kecmanovic [6] and the traditional literature review method. As a result of the research, it was seen that the field of organizational performancehas not developed in parallel with Industry 4.0 until now.
Decision analysis and methods
Ali Dehghani Filabadi; Gholamreza Hesamian
Abstract
Recently, fuzzy linguistic variables have gained a great deal of attention from researchers in many decision-making problems. In this problems, type-2 fuzzy sets have been used to better cover linguistic data uncertainty. However, many of research works in this regard have been performed in type-2 fuzzy ...
Read More
Recently, fuzzy linguistic variables have gained a great deal of attention from researchers in many decision-making problems. In this problems, type-2 fuzzy sets have been used to better cover linguistic data uncertainty. However, many of research works in this regard have been performed in type-2 fuzzy domain and in static mode. Since the decision-making problems in the real world usually fluctuate over time, so it need to use decision-making models in multi-period of time. In the present research, a Multi-Period (Dynamic) Multi-Attribute Group Decision-Making (MPMADM) method is presented based on type-2 fuzzy sets where decision-making attributes are first expressed in linguistic terms and then incorporated, as interval type-2 fuzzy numbers, into problem-solving where a new integrating operator called Multi-Period Trapezoidal Interval Type-2 Fuzzy Number Weighted Arithmetic averaging (MPTIT2FNWA) is defined on type-2 interval fuzzy numbers to integrate decision-making information in multiple periods of time. Once finished with explaining the proposed method, a numerical example is given to evaluate the proposed method in terms of effectiveness and applicability, with the results compared to those of other methods.
Design of Mechanical and Thermal Systems
Aniekan Essienubong Ikpe; Ekpenyong Akanimo Udofia; Emmanuel Odeh
Abstract
Cooling refrigeration systems ingest prime energy and contribute to universal negative impact due to ecologically unfavorable working fluids used. Hence, the quest to improve the performance of Vapour Compression Refrigeration System (VCRS) with more efficient and eco-friendly refrigerant such as nanoparticles ...
Read More
Cooling refrigeration systems ingest prime energy and contribute to universal negative impact due to ecologically unfavorable working fluids used. Hence, the quest to improve the performance of Vapour Compression Refrigeration System (VCRS) with more efficient and eco-friendly refrigerant such as nanoparticles becomes imperative. In this study, performance analysis of hybrid nanofluids-zeotropic mixtures in a VCRS were experimentally investigated to determine the best operating optimum performance using exergy based approach. To achieve this, varying concentrated mixtures were selected using ternary graph. The results revealed that all the designated ratios of the mixed refrigerant with different fractions achieved good performance improvement with optimum values obtained at (011) zero gram of TiO2, 7.5g-Al2O3/CuO. All the selected hybrid mixtures led to an improved outcome in terms of Coefficient of Performance (COP), less power consumption and high performance exergetic efficiency, with COP values ranging from 0.31% to 3.10% and exergetic efficiency from 0.32 to 1.43%. The value for thermal conductivity, dynamic viscosity, density and specific heat were found to be highest (0.0958 W/m.K; 0.00164 W/m.K; 686.82 kg/m3 and 359.82 kJ/kg.K) at the same concentration of zero grams TiO2 in the mixture. Comparison made from the performance characteristics curve (with global parameters) indicated that maximum power coefficient and cooling capacity for the various concentrations were found at (001) 7.5g-TiO2, zero grams Al2O3/CuO equal to 2.2 kW, and the minimum value at concentration of 5 was 0.61% at (111) 5g-TiO2/Al2O3/CuO, and 0.87% for (121). An increase was observed in the maximum power coefficient, cooling capacity and COP increased by 13.51%, 5.78% and 10.33%. It was also observed that hybrid nanofluid-zeotropic refrigerant worked seamlessly with VRCS, making it a sustainable, green and clean as well as eco-friendly alternative with near-zero to zero negative effects on public health safety and environment.
Decision analysis and methods
Abdella Yimam Ali
Abstract
This paper presented greedy algorithm for solving student allocation problem that has arisen in internship program. In internship program, engineering students stay one semester in industries which are located across the country and teachers visit students once/twice for supervision during the program. ...
Read More
This paper presented greedy algorithm for solving student allocation problem that has arisen in internship program. In internship program, engineering students stay one semester in industries which are located across the country and teachers visit students once/twice for supervision during the program. As the industries scatter across the country, teachers spend long time on travel. And this results in wastage of teachers working time and money spent for transport. Therefore, allocating students to universities near the internship location extensively reduces the transport time and money spent for transport. For the current study, we consider 4th mechanical engineering students who are currently working in the industry. The proposed approach extensively decrease the distance traveled from 23,210 km to 2,488.8 km and the time spent on the road from 397 hrs. 40 min to 51 hrs. 30 min. and finally, the results obtained from the greedy algorithm is compared with other heuristics (i.e., Genetic algorithm and Particle swarm optimization) and the greedy algorithm outperforms the other methods.