production planning
Ommolbanin Yousefi; Saeed Rezaeei Moghadam; Neda Hajheidari
Abstract
One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps ...
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One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps the decision makers to make such decisions. The proposed model comprises four main objectives, the first one of which considers minimizing costs (including costs of manufacturing product, supplying, maintenance, inventory stock shortage, and expenditures related to man power). The second objective is defined as maximizing customers’ satisfaction. Minimizing suppliers’ satisfaction makes up the third objective and maximizing the quality of the manufactured products constitutes the fourth objective. In this model, the demand parameter is investigated under uncertain conditions; hence, other parameters influenced by this parameter are also presented under uncertain conditions occurring within three differing scenarios. This model is solved through LP- metric and the LINGO v14.0.1.55 software. At first the model is solved by means of numerical example; then it is solved by the actual data that are related to a military industry. Finally, process, variables like inventory level, overtime work hours etc, are valued with the help of closed-loop supply chain of the proposed model.
Case studies in industry and services
Walid Meslameni; Taoufik Kamoun
Abstract
The evolution of the means aimed at improving the availability of strategic equipment requires a credible level of maintenance with the development of original monitoring techniques such as vibration diagnostics. The vibration monitoring of strategic equipment through a vibration diagnosis requires mainly ...
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The evolution of the means aimed at improving the availability of strategic equipment requires a credible level of maintenance with the development of original monitoring techniques such as vibration diagnostics. The vibration monitoring of strategic equipment through a vibration diagnosis requires mainly the identification of vibrational images of the different types of damage. However, one of the important vibration problems is essentially due to the phenomenon of imbalance. This phenomenon corresponds to an imbalance of the rotor due to the offset between the axis of inertia and the axis of rotation, which causes significant and cyclical vibrations. The aim of this study is to analyze the vibratory behavior of a screw compressor to improve its reliability and consequently its availability. To identify the imbalance fault, two sets of vibration measurements on April and January were fundamentally examined at the compressor level. Fourier transform based on spectral analysis was used to create a vibration detection approach with vibration signals. The comparison of the results obtained with that of the simulation resulting from the model of dynamic behavior of the compressor is conclusive.
Supply chain management
Jaber Ghanbari; Ebrahim Abbasi; Hosein Didekhani; Majid Ashrafi
Abstract
The present study investigated the role of strategic cost management as a moderating variable on the relationship between supply chain practices, Top Management Support (TMS), and financial performance improvement. Financial performance improvement was considered as a dependent variable, while supply ...
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The present study investigated the role of strategic cost management as a moderating variable on the relationship between supply chain practices, Top Management Support (TMS), and financial performance improvement. Financial performance improvement was considered as a dependent variable, while supply chain practices, strategic cost management, and TMS were taken as the main independent variables. Besides, the financial structure and the firm size were considered as control variables. The research sample included 165 companies that were selected using random sampling from among companies listed on the Tehran Stock Exchange. The data were collected using the Senior Management Survey (SMS) to measure supply chain practices, TMS, and strategic cost management. The results of the structural equation modeling after discriminant tests showed that strategic cost management had a positive and significant effect on the relationship between different subscales of supply chain practices and different measures of financial performance improvement. The results also showed that the relationship between strategic cost management, senior management support, supply chain activities and improving financial performance is non-linear and so that Supply Chain Integration (SCI) is more effective at low and medium levels and at higher levels. The above has a lesser or even negative effect.
Scheduling
Behnaz Zanjani; Maghsoud Amiri; Payam Hanafizadeh; Maziar Salahi
Abstract
Scheduling is an important decision-making process that aims to allocate limited resources to the jobs in a production process. Among scheduling problems, Hybrid Flow Shop (HFS) scheduling has good adaptability with most real world applications including innumerable cases of uncertainty of parameters ...
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Scheduling is an important decision-making process that aims to allocate limited resources to the jobs in a production process. Among scheduling problems, Hybrid Flow Shop (HFS) scheduling has good adaptability with most real world applications including innumerable cases of uncertainty of parameters that would influence jobs processing when the schedule is executed. Thus a suitable scheduling model should take parameters uncertainty into account. The present study develops a multi-objective Robust Mixed-Integer Linear Programming (RMILP) model to accommodate the problem with the real-world conditions in which due date and processing time are assumed uncertain. The developed model is able to assign a set of jobs to available machines in order to obtain the best trade-off between two objectives including total tardiness and makespan under uncertain parameters. Fuzzy Goal Programming (FGP) is applied to solve this multi objective problem. Finally, to study and validate the efficiency of the developed RMILP model, some instances of different size are generated and solved using CPLEX solver of GAMS software under different uncertainty levels. Experimental results show that the developed model can find a solution to show the least modifications against uncertainty in processing time and due date in an HFS problem.
Case studies in industry and services
Robert S Keyser; Parisa Pooyan
Abstract
Root cause analysis techniques are often applied to problems in the workplace; however, they may also prove very useful to home projects. This research explores the application of two root cause analysis techniques in home projects: (1) 5 Whys to determine the root cause of a home air conditioning unit ...
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Root cause analysis techniques are often applied to problems in the workplace; however, they may also prove very useful to home projects. This research explores the application of two root cause analysis techniques in home projects: (1) 5 Whys to determine the root cause of a home air conditioning unit that runs continuously but does not cool, and (2) an innovative Lean PFMEA to repair a John Deere riding mower that starts, then stops. Employing the 5 Whys technique led to the discovery of incorrect color-coded wiring from the original air conditioning unit to the thermostat. Lean PFMEA enabled a correct diagnosis and resolution of the mower start/stop issue via a Kaizen event, grass clippings in the fuel line, which was remedied by cleaning the fuel tank and replacing the fuel lines, fuel filter, and carburetor. These techniques provide Lean methodological approaches to problem-solving, which often leads to reduced homeowner aggravation, repair time, and repair expense.
Engineering Optimization
Osarobo Osamede Ogbeide; Kolawole Akeredolu; Samuel Ayodeji Omotehinse
Abstract
The service life of engineering structure is mostly affected by the quality and strength of the welded joints. Tensile tests are performed for several reasons. The results are used in selecting materials for engineering applications. Tensile properties are frequently included in material specifications ...
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The service life of engineering structure is mostly affected by the quality and strength of the welded joints. Tensile tests are performed for several reasons. The results are used in selecting materials for engineering applications. Tensile properties are frequently included in material specifications to ensure quality. The tests are measured during development of new materials and processes, so that different materials and processes can be compared. The objective of this study is to predict and optimize the tensile strength of a butt joint weldment on mild steel plate using Response Surface Methodology (RSM). The RSM was applied to predict and optimize the maximum tensile strength of a butt joint weldment on an I-section mild steel plate using Tungsten Inert Gas (TIG) welding process. The mild steel plate was cut into dimension 60mm x 40mm x 10mm with a power hacksaw, grinded and cleaned before the welding process. The experimental matrix was made of twenty (20) runs, generated by the design expert 11.1.0.1 software adopting the central composite design. The response (tensile strength) was measured and then modelled using the RSM. The result obtained show that the current and voltage has a very strong influence on the tensile strength. Based on the findings, the maximum tensile strength of 450Mpa was attained at the welding voltage (V) of 24V, current of 170A and gas flow rate of 13lit/min respectively. This study will serve as a guide to welding operators on parameter settings selection.
Energy Saving
Silas Oseme Okuma; Ejiroghene Kelly Orhorhoro; Amos Adesoji Idowu
Abstract
The significance of energy in human lives cannot be overemphasized. It is crucial to all facets of economic growth, progress, and development as well as poverty eradication and security. Household energy is generally required for a variety of purposes. It is required for lighting and heating. This ...
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The significance of energy in human lives cannot be overemphasized. It is crucial to all facets of economic growth, progress, and development as well as poverty eradication and security. Household energy is generally required for a variety of purposes. It is required for lighting and heating. This study evaluated domestic energy utilization in major Nigeria cities using Warri, Benin, Port Harcourt, and Calabar as a case study. A total of four locations with the highest population were targeted at each selected city. Responses were randomly selected from energy utilization in the selected region. A total of 1439 questionnaires were administered all through the selected cities in this study. Data obtained were evaluated using descriptive statistic. The result obtained revealed that kerosene has the highest percentage of utilization (88%), LNG (68.9%), electricity (67.7%), PMS (67.1), diesel (5.6%), charcoal (16.4%), wood (28.2%), and solar (3%) within these cities. Therefore, kerosene is the most preferred energy and this can be as a result of cost when compared to LNG, electricity, PMS, diesel, charcoal, solar, and wood fuel.
Scheduling
Vahid Bahmani; Mohammad Amin Adibi; Esmaeil Mehdizadeh
Abstract
This paper provides an integrated model for a two-stage assembly flow shop scheduling problem and distribution through vehicle routing in a soft time window. So, a mixed-integer linear programming (MILP) model has been proposed with the objective of minimizing the total cost of distribution, holding ...
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This paper provides an integrated model for a two-stage assembly flow shop scheduling problem and distribution through vehicle routing in a soft time window. So, a mixed-integer linear programming (MILP) model has been proposed with the objective of minimizing the total cost of distribution, holding of products, and penalties of violating delivery time windows. To solve this problem, an improved meta-heuristic algorithm based on whale optimization algorithm (WOA) has been developed. A comparison of the integrated and non-integrated model in a case study of industrial gearboxes production shows that the integrated model compared to the non-integrated model has saved 15.6% and 13.6% in terms of delay time and total costs, respectively. Computational experiments also indicate the efficiency of improved WOA in converging to optimal solution and achieve better solution in comparison to the genetic algorithm (GA).
Forecasting, production planning, and control
Ejiroghene Kelly Orhorhoro; Andrew Amagbor Erameh; Rogers Ibunemisam Tamuno
Abstract
In this study, the effects of corrosion rate on post welded annealed heat-treated medium carbon steel in seawater was investigated. The medium carbon steel samples were butt-welded by using the Shielded Metal Arc Welding (SMAW) technique and, afterwards, heat treated by annealing at different annealing ...
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In this study, the effects of corrosion rate on post welded annealed heat-treated medium carbon steel in seawater was investigated. The medium carbon steel samples were butt-welded by using the Shielded Metal Arc Welding (SMAW) technique and, afterwards, heat treated by annealing at different annealing temperature was carried out. The microstructure of the unwelded and post welded heated samples was characterised by means of optical microscopy. The as received (control), unwelded and post welded annealed medium carbon steel samples were immersed in sea water for a duration of one hundred (100) days, and this was to stimulate the effect on equipment in offshore and food processing applications. Post welded heat treatment on the microstructure, weight loss and corrosion rate were evaluated. The results obtained showed an initial increase in both the weight loss and corrosion rate of samples up to 40 days and started decreasing afterwards. It was equally observed that the post welded annealed samples showed more corrosion activities than the un-welded annealed samples. Above and beyond, corrosion activity was more prominent in samples with the highest annealing temperature. More so, the unwelded annealed medium carbon steel showed a dispersion of coalescence cementite and ferrite grain while the post welded annealed medium carbon steel samples showed a martensite (light area marked by arrows) distributed in the ferrite (dark area) matrix.
Heuristics and Metaheuristics Algorithms
Hojatollah Rajabi Moshtaghi; Abbas Toloie Eshlaghy; Mohammad Reza Motadel
Abstract
Conventional and classical optimization methods are not efficient enough to deal with complicated, NP-hard, high-dimensional, non-linear, and hybrid problems. In recent years, the application of meta-heuristic algorithms for such problems increased dramatically and it is widely used in various fields. ...
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Conventional and classical optimization methods are not efficient enough to deal with complicated, NP-hard, high-dimensional, non-linear, and hybrid problems. In recent years, the application of meta-heuristic algorithms for such problems increased dramatically and it is widely used in various fields. These algorithms, in contrast to exact optimization methods, find the solutions which are very close to the global optimum solution as possible, in such a way that this solution satisfies the threshold constraint with an acceptable level. Most of the meta-heuristic algorithms are inspired by natural phenomena. In this research, a comprehensive review on meta-heuristic algorithms is presented to introduce a large number of them (i.e. about 110 algorithms). Moreover, this research provides a brief explanation along with the source of their inspiration for each algorithm. Also, these algorithms are categorized based on the type of algorithms (e.g. swarm-based, evolutionary, physics-based, and human-based), nature-inspired vs non-nature-inspired based, population-based vs single-solution based. Finally, we present a novel classification of meta-heuristic algorithms based on the country of origin.
Case studies in industry and services
Hadi Mehrabi Sharafabadi; Mohamad Ali Movafaghpour
Abstract
The main purpose of this study is to identify the delay factors and evaluate the type ranking of delays in natural gas distribution projects. We have investigated 274 projects in Khuzestan gas company from 2015 to 2020. Projects investigated in this study included urban, rural, transmission lines, industrial ...
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The main purpose of this study is to identify the delay factors and evaluate the type ranking of delays in natural gas distribution projects. We have investigated 274 projects in Khuzestan gas company from 2015 to 2020. Projects investigated in this study included urban, rural, transmission lines, industrial pipelines, and construction. We identified 22 delay factors and categorized them into owner, contractor, and other related factors. This research shows that Most of the delay factors are related to owner causes. In addition to identifying the factors, this study also deals with the extent of their relationship. In addition to identifying the delay factors, this study also deals with the extent of their relationship. We showed that delay factors may not be independent and there is a significant association between them. These Relations clearly showed that reduction or elimination of many delay factors lead to eliminating many others. The findings of the research were validated and implemented by company experts.
Operations Research
Seyed Amin Badri; Negar Yarmohamadi
Abstract
The aim of this paper is to propose a mathematical model for two dental centers in a competitive market of dental tourism. Dental tourists are looking for cheaper treatment with proper quality, and dental centers are looking to maximize their profits by providing services to tourists. Government also ...
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The aim of this paper is to propose a mathematical model for two dental centers in a competitive market of dental tourism. Dental tourists are looking for cheaper treatment with proper quality, and dental centers are looking to maximize their profits by providing services to tourists. Government also monitors dental centers by setting tariffs (subsidies or taxes). This problem is modeled and solved in the form of Stackelberg (or Leader-Follower) game. The government as the leader determines the amount of tariffs and then the dental centers as the followers simultaneously determine the price and quality level of their services. To solve the game, first the equilibrium values related to the price and quality level of the services of the dental centers have been calculated by Nash equilibrium. Then, according to the equilibrium values obtained for dental centers, the optimal amount of tariffs are calculated. Finally, to clarify the proposed model a numerical example is provided and sensitivity analysis is performed on some parameters. In this paper, for the first time a mathematical model is developed for pricing and determining the quality of services in a competitive market of dental tourism. The obtained results indicate that increasing the amount of subsidy will lead to a decrease in the prices of service provided by the dental centers. Moreover, by increasing the amount of subsidies allocated to the dental centers, the government can expand the dental tourism industry.
Data Envelopment Analysis, DEA
Jafar Pourmahmoud; Naser Kaheh; Farhad Hosseinzadeh Lotfi
Abstract
In traditional cost-efficiency models, inputs and outputs, as well as input prices were known as constant values for each decision-making unit In our daily applications, however, market entry prices vary at different times. In other words, input prices for decision-making units (DMUs) are time dependent. ...
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In traditional cost-efficiency models, inputs and outputs, as well as input prices were known as constant values for each decision-making unit In our daily applications, however, market entry prices vary at different times. In other words, input prices for decision-making units (DMUs) are time dependent. Traditional methods cannot calculate the cost efficiency of DMUs with time-dependent prices. This paper proposes a new method to calculate the cost efficiency of DMUs in the presence of time-dependent prices. The proposed model is a parametric programming problem model depending on time. In the presented model, the inputs and outputs are functions in terms of time, which is not present in the models introduced by other researchers. New definitions for time-dependent cost efficiency have also been introduced. The cost efficiency of DMUs is measured over a given time and the units are ranked according to the time obtained. Finally, a numerical example has been presented to illustrate the proposed method.
Computational modelling
Zahra Mahboob Dana; Hashem Saberi Najafi; Amir Hossein Refahi Sheikhani
Abstract
In this paper, a one-dimensional fractional advection-diffusion equation is considered. First, we propose a numerical approximation of the Riemann-Liouville fractional derivative which is fourth-order accurate, then a numerical method for the fractional advection-diffusion equation using a high order ...
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In this paper, a one-dimensional fractional advection-diffusion equation is considered. First, we propose a numerical approximation of the Riemann-Liouville fractional derivative which is fourth-order accurate, then a numerical method for the fractional advection-diffusion equation using a high order finite difference scheme is presented. It is proved that the scheme is convergent. The stability analysis of numerical solutions is also discussed. The method is applied in several examples and the accuracy of the method is tested in terms of error norm. Furthermore, the numerical results have been compared with some other methods.
Quality Control
Nazila Adabavzeh; Mehrdad Nikbakht
Abstract
The airline industry plays a fundamental role in the economic and social development of societies and it also has an important impact on improving foreign trade. The airline industry is one of the main infrastructures for sustainable development of the country. The quality of the reverse engineering ...
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The airline industry plays a fundamental role in the economic and social development of societies and it also has an important impact on improving foreign trade. The airline industry is one of the main infrastructures for sustainable development of the country. The quality of the reverse engineering service of the airline industry will be effective in increasing the safety and health of structures, reducing the impact of disasters and reducing costs. The airline industry needs its own defined models to measure the quality of service which has the ability to assess the quality of the services of this industry. Purpose of this research is to present a developed SERVQUAL model to assess the quality of services in the air industry. The Developed Reverse Logistic Airline Service Quality (RL AIRQUAL) model was a descriptive and cross-sectional analysis of reverse-customer support services of six organizational units of the air industry company using a 35-item questionnaire with standard 5-point Likert scale and adjusted SERVQUAL in eight dimensions of tangibility, reliability, assurance, empathy, responsiveness, safety and security, customer satisfaction and customer loyalty dimensions. Data were analyzed by paired t-test using SPSS software. Based on the determination of reverse service support quality, the responsiveness had the highest gap and safety and security had the lowest gap. The results can be used to assess the competitive position of the organization and identifying opportunities for improving the airline industry. With the help of the results of the modified model evaluation, applicable and suitable solutions can be developed to improve customer satisfaction.
Statistical Process
Nastaran Hajarian; Farzad Movahedi Sobhani; Seyed Jafar Sadjadi
Abstract
One of the most complex and costly systems in the industry is the Gas turbine (GT). Because of the complexity of these assets, various indicators have been used to monitor the health condition of different parts of the gas turbine. Turbine exit temperature (TET) spread is one of the significant indicators ...
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One of the most complex and costly systems in the industry is the Gas turbine (GT). Because of the complexity of these assets, various indicators have been used to monitor the health condition of different parts of the gas turbine. Turbine exit temperature (TET) spread is one of the significant indicators that help monitor and detect faults such as overall engine deterioration and burner fault. The goal of this article is to use data-driven approaches to monitor TET data to detect faults early, as fault detection can have a significant impact on gas turbine reliability and availability. In this study, the TET data of v94.2 GT is measured by six temperature transmitters to show a detailed profile. According to the statistical tests, TET data are high dimensional and time-dependent in the real world industry. Hence, three distinctive methods in the field of the gas turbine are proposed in this study for early fault detection. Conventional principal component analysis (PCA), moving window PCA (MWPCA), and incremental PCA (IPCA) were implemented on TET data. According to the results, the conventional PCA model is a non-adaptive method, and the false alarm rate is high due to the incompatibility of this approach and the process. The MWPCA based on V-step-ahead and IPCA approaches overcame the non-stationary problem and reduced the false alarm rate. In fact, these approaches can distinguish between the normal time-varying and slow ramp fault processes. The results showed that IPCA could detect fault situations faster than MWPCA based on V-step-ahead in this study.
Case studies in industry and services
Yayan Saputra; Fibi Eko Putra; Taufik Hidayat
Abstract
The number of pipeline construction industry and electricity prices in Indonesia from 2013 to 2019 has increased. In order for the pipeline construction industry to be sustainable and competitive, the industry must strive to reduce electricity consumption, one of which is the ISO 50001 energy management ...
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The number of pipeline construction industry and electricity prices in Indonesia from 2013 to 2019 has increased. In order for the pipeline construction industry to be sustainable and competitive, the industry must strive to reduce electricity consumption, one of which is the ISO 50001 energy management system approach. This research identifies energy intensity data; energy performance data from Significant Energy Use (SEU) in the production process of the pipeline construction industry and comparing it with baseline values; targets to be achieved; and analyzing the effects of machines, materials, methods, human and environmental factors on energy consumption. Based on the results of the discussion, this research can conclude that the construction of piping work requires electricity for the cutting and welding process. The highest electrical intensity intensity is in the welding process, which averages 16.4 KJ/cm (88.2% of total energy consumption) and the cutting process is 2.2 KJ/cm (11.8% of total energy consumption). So a significant use of energy for corrective action is that the pipe work process is a welding process. Factors that cause high energy consumption/energy intensity in pipe construction work include method and material factors. Result of every factors can reduce the electricity consumption of the welding process from 16.4 KJ/cm to 7.5 KJ/cm (54.3%).
Forecasting, production planning, and control
Obojobo Obukeajeta Donatus; Chima Uzorh
Abstract
Economic or local disruptions that affect organizations' production activities often result in unexpected losses. An excellent example is the recent COVID-19 pandemic disruption which affected many economies globally. This study presents a deterministic model and uses simple regression analysis to estimate ...
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Economic or local disruptions that affect organizations' production activities often result in unexpected losses. An excellent example is the recent COVID-19 pandemic disruption which affected many economies globally. This study presents a deterministic model and uses simple regression analysis to estimate the average condition for production losses. Its corresponding components' input resources impact the overall estimates for selected organizations in Nigeria. It is anticipated that variability in economic activities is always accompanied by unconventional stock returns whose behaviour indicates prevailing economic trends. Here we have looked at two organizations in the manufacturing sector as a case study; Nigerian Breweries and Nestle Nigeria, whose stock prices[X] upon analysis reveal that at[X]≤N30 and [X]≤N821 are estimated conditions for zero net profit for both organizations respectively. Therefore, for Nigerian Breweries, during the four quarters of the 2020 fiscal year, the following were assessed production losses,3.47 billion naira(Q1), 4.17 billion naira(Q2), 3.72 billion naira(Q3) and 0.68 billion naira(Q4) with a total of 12.04 billion naira annual estimated losses; with COGS,OPEX and SAEX having 39.6%,44.5% and 15.9% impact on the estimates. Nestle Nigeria records estimated production losses of 5.8 billion naira (Q1), 6.4 billion naira(Q2),4.2 billion naira(Q3), and -0.8 billion naira(Q4) (gain), resulting in a total 15.6 billion naira annual estimated loss; and COGS,OPEX, and SAEX having 45.9%, 48.2% and 5.9% impact on the estimates respectively. This implies, Selling and Advertising Expenses (SAEX) had the most negligible percentage impact on overall estimated production losses for both organizations compared to Costs of Goods Sold (COGS) and Operating Expenses (OPEX).This study, therefore, reiterates the position of other economic reports describing the adverse effects of the pandemic in Nigeria; while also serving as an investment analysis guide to potential investors..
Case studies in industry and services
Farkhondeh Mortaz Hejri; Changiz Valmohammadi; Mahmood Alborzi
Abstract
This study aimed to identify factors affecting the green management process readiness of banks and determining the interactions and priority of these factors. To this end, factors affecting the green management process readiness in the banking industry were extracted by using an in-depth study of the ...
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This study aimed to identify factors affecting the green management process readiness of banks and determining the interactions and priority of these factors. To this end, factors affecting the green management process readiness in the banking industry were extracted by using an in-depth study of the extant research and qualitative content analysis. Also, fuzzy DEMATEL method was used to explain and assess the interrelationships between the identified factors. The research sample included 14 experts in the process management field in the industry and academicians with knowledge of the concepts of emerging technologies and more than 10 years of experience at the level of managerial activities in the banking industry. Application of DEMATEL revealed that “green awareness”, “green attitude”, “green governance”, and “green technology” are the influential factors, while “green operation”, “green infrastructure”, “green lifecycle”, “green strategy”, and “green policies” are permeable factors. It was also found that “green awareness” has the greatest impact on other factors and "green operations "is the most permeable factor. The obtained results might help to raise the awareness of individuals including managers, policymakers of the organizations toward establishing and fostering a green attitude to adopting green operations.
Management and Entrepreneurship
Younos Vakil Alroaia
Abstract
The aim of this study is providing a developed model for SMEs' in open innovation activities. In this regard, an appropriate model was defined by studying the literature. Then, after selecting a sample of 60 small and medium enterprises the data were collected by a questionnaire and were analyzed with ...
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The aim of this study is providing a developed model for SMEs' in open innovation activities. In this regard, an appropriate model was defined by studying the literature. Then, after selecting a sample of 60 small and medium enterprises the data were collected by a questionnaire and were analyzed with the Smart PLS software. In the third stage, the relative importance of factors was tested from the perspective of 10 experts in the field of open innovation along with experienced managers of the small and medium enterprises with more than 15 years of work experience with the help of ANP and PROMETHEE methods. The results showed that these factors include the parameters: Product Characteristics, Inter-organizational Factors, and Environmental Factors. In addition, the most important factors include Product Characteristics. Finally, several implications were made such as changing the degree of SMEs' participation in open innovation activities over time according to continuous monitoring of these moderators.
Supply chain management
Ali Mansory; Abbas Nasiri; Nabiollah Mohammadi
Abstract
The main purpose of this paper is to identify the traditional, green and effective resilience criteria in the performance of green and resilient suppliers and their ranking with path analysis, SWARA and TOPSIS combined approach in Fanavaran Petrochemical Company. The research method is applied in terms ...
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The main purpose of this paper is to identify the traditional, green and effective resilience criteria in the performance of green and resilient suppliers and their ranking with path analysis, SWARA and TOPSIS combined approach in Fanavaran Petrochemical Company. The research method is applied in terms of goal and descriptive-survey in terms of data collection. By a comprehensive review of the literature, first a set of key performance criteria and sub-criteria (traditional, green, and resilience) were extracted. Then, using the path analysis approach, the effectiveness of these criteria was evaluated in Fanavaran Petrochemical Company. The statistical population included 55 experts of the mentioned company, which due to the limited size of the population, all members were considered as the research sample. The path analysis result showed that all identified criteria affect the company’s supplier’s performance. Then, using new SWARA decision-making technique and also the opinions of 30 experts, the criteria and sub-criteria were evaluated and their weight (importance) was extracted. In the final evaluation of the main criteria, the criterion of “resilience” was in the first rank, the criterion of “green” in the second rank and the criterion of “traditional” in the last rank. Subsequently, due to the sensitivity of the ranking of green and resilient suppliers in the company, using the TOPSIS decision-making technique and based on the extractive weight of the criteria, seven suppliers of the company were evaluated by the experts and the final ranking of the suppliers in terms of performance was determined. Thus, the proposed approach of this research provides a valuable conceptual framework for company’ managers to improve the situation of the suppliers in terms of the environmental issues and resilience. Also, the development and improvement of traditional criteria and selection of suppliers of the company based on green standards and resilience were the main goals of this research.
Data mining
Aboosaleh Mohammad Sharifi; Kaveh Khalili Damghani; Farshid Abdi; Soheila Sardar
Abstract
Cryptocurrencies are considered as new financial and economic tools having special and innovative features, among which Bitcoin is the most popular. The contribution of the Bitcoin market continues to grow due to the special nature of Bitcoin. The investors' attention to Bitcoin has increased significantly ...
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Cryptocurrencies are considered as new financial and economic tools having special and innovative features, among which Bitcoin is the most popular. The contribution of the Bitcoin market continues to grow due to the special nature of Bitcoin. The investors' attention to Bitcoin has increased significantly in recent years due to significant growth in its prices. It is important to create a prediction system which works well for investment management and business strategies due to the high chaos and volatility of Bitcoin prices. In this study, in order to improve predictive accuracy, Bitcoin price dataset is first divided into a time interval through time window, then propose a new model based on Long Short-Term Memory (LSTM) neural networks and Metaheuristic algorithms. Chaotic Dolphin Swarm Optimization algorithm is used to optimize the LSTM. Performance evaluation indicated that the proposed model can have more effective predictions and improve prediction accuracy. In addition, the performance of the optimized model is better and more reliable than other models.
Case studies in industry and services
Annette Serwaa Agyeman; Adjei Gyamfi Gyimah; Solomon Adu-Asare
Abstract
Microfinance Institutions (MFIs) contribute significantly to the development of a country and many of these institutions are found in most developing countries including Ghana. However, many challenges have been alleged to stifle the efforts of microfinance companies in their attempt to make their all-important ...
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Microfinance Institutions (MFIs) contribute significantly to the development of a country and many of these institutions are found in most developing countries including Ghana. However, many challenges have been alleged to stifle the efforts of microfinance companies in their attempt to make their all-important contribution to the development of nations. This study explored the effect of operational flaws on the performance of microfinance institutions in Ghana. The results discovered flaws and challenges associated with the operations of the MFIs in many areas including corporate governance, credit risk management, credit administration, regulatory challenges, and training programs. The study also revealed that such flaws and challenges do harm the overall performance of the MFIs. Based on the findings, it is recommended that MFIs put in place a well-composed and resourceful credit committee to perform the duty of credit risk management in the institutions. The institutions could also reduce their interest rates to encourage their clients to apply for more loans. Lastly, it is recommended that the MFIs take all necessary steps to ensure that they reduce the flaws and challenges they face to mitigate the negative impact of such deficiencies on their performance.
Scheduling
Bahareh Vaisi; Hiwa Farughi; Sadigh Raissi; Heibatolah Sadeghi
Abstract
In this study, we model a stochastic scheduling problem for a robotic cell with two unreliable machines susceptible to breakdowns and subject to the probability of machine failure and machine repair. A single gripper robot facilitates the loading/unloading of parts and cell-internal movement. Since it ...
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In this study, we model a stochastic scheduling problem for a robotic cell with two unreliable machines susceptible to breakdowns and subject to the probability of machine failure and machine repair. A single gripper robot facilitates the loading/unloading of parts and cell-internal movement. Since it is more complicated than the other cycles, the focus has been on the S_2 cycle as the most frequently employed robot movement cycle. Therefore, a multi-objective mathematical formulation is proposed to minimize cycle time and operational costs. The -constraint method is used to solve small-sized problems. Non-dominated sorting genetic algorithm II (NSGA-II), is used to solve large-sized instances based on a set of randomly generated test problems. The results of several Test problems were compared with those of the GAMS software to evaluate the algorithm's performance. The computational results indicate that the proposed algorithm performs well. Compared to GAMS software, the average results for maximum spread (D) and non-dominated solutions (NDS) are 0.02 and 0.04, respectively.
Human factors, ergonomics, and safety
S. V. S. Raja Prasad
Abstract
Safety audit is a system for evaluating the adherence of an occupational safety and health plan to fulfill statutory requirements with prior planning. Safety audit planning is the predetermining activity of what, how, where, when and by whom the audit will be carried out to achieve its objective. Safety ...
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Safety audit is a system for evaluating the adherence of an occupational safety and health plan to fulfill statutory requirements with prior planning. Safety audit planning is the predetermining activity of what, how, where, when and by whom the audit will be carried out to achieve its objective. Safety audit planning is a complex process and an anticipatory function which will provide audit activity on time with the least audit risk and cost by assigning the auditors with the required ability and skill level to the activities to be audited. In general, the safety audit planning is based on the professional judgment of a lead auditor by considering the qualitative characteristics of the auditors. However, the audit planning is possible by framing a mathematical model with an assumption that the auditors possess similar characteristics. The objective of the study is to optimize the safety audit planning by allocating auditors to activities using a linear programming model so as to minimize the audit cost; which is not possible with statistical tools. The study was conducted in an integrated cement plant located in India and the results of the study show that the number of hours and the activity of the auditors was specified with a minimum cost. Similar studies can be conducted to optimize time and cost of safety audit for industrial units involving more number of activities with large batch size of auditors by planning the audit process in advance.