Showing 683 results for Type of Study: Research
Mehdi Dadehbeigi, Ali Taherinezhad, Alireza Alinezhad,
Volume 36, Issue 1 (3-2025)
Abstract
Today, data mining and machine learning are recognized as tools for extracting knowledge from large datasets with diverse characteristics. With the increasing volume and complexity of information in various fields, decision-making has become more challenging for managers and decision-making units. Data Envelopment Analysis (DEA) is a tool that aids managers in measuring the efficiency of the units under their supervision. Another challenge for managers involves selecting and ranking options based on specific criteria. Choosing an appropriate multi-criteria decision-making (MCDM) technique is crucial in such cases. With the spread of COVID-19 and the significant financial, economic, and human losses it caused, data mining has once again played a role in improving outcomes, predicting trends, and reducing these losses by identifying patterns in the data. This paper aims to assess and predict the efficiency of countries in preventing and treating COVID-19 by combining DEA and MCDM models with machine learning models. By evaluating decision-making units and utilizing available data, decision-makers are better equipped to make effective decisions in this area. Computational results are presented in detail and discussed in depth.
Ahmad Padhil, Hari Purnomo, Hartomo Soewardi, Imam Djati Widodo,
Volume 36, Issue 1 (3-2025)
Abstract
Occupational safety and health (OSH) challenges in the Micro, Small, and Medium Enterprises (MSMEs) sector are serious issues that Warrant significant attention. This study aims at developing an integrative model investigation of Occupational Safety and Health for SMEs that use Job Shop production floors with a macro-ergonomics approach and Human Factors Analysis and Classification System (HFACS) to reduce the number of work accidents in this sector. Firstly, the organizational structure and management system of UMKM Job Shop are analyzed, including work procedures, training, and Occupational Health and Safety (OHS) policies. Then, HFACS is used to identify human factors that contribute to incidents and accidents, including human error, organizational factors, and environmental factors. Finally, the relationship between macroergonomic variables and HACFS variables is tested using the SEM-PLS (Structural Equation Modelling - Partial Least Squares) method. The results show that the resulting model can improve OHS in the MSME sector including key variables including Physical Environment, Good Supervision, Good Organization, Balanced Division of Tasks, Use of Technology that is in accordance with needs and Human resources will reduce the occurrence of Unsafe Action in MSMEs with the Job Shop Layout model
Maryam Ghasemi, Mehdi Seifbarghy, Nezir Aydin, Wichai Chattinnawat,
Volume 36, Issue 1 (3-2025)
Abstract
One of the most important issues regarding community health is animal health, followed by the health of animal products. Providing a sustainable environment for production facilities like livestock centers is essential. In this study, we have proposed designing four fuzzy inference systems for managing the sustainability of livestock centers. The first, second, and third systems are applied for the economic, social, and environmental dimensions. The fourth is for a system whose output is the sustainability level while its inputs are the three addressed sustainability dimensions. The data source was experts' judgment, and the major limitation of this research was access to a limited number of experts in making system rules. The validation is made by cross-checking with other experts. Considering a maximum of 10 points for each sustainability dimension and supposing that the economic dimension is 5.05, the social dimension is 7.77 and the environmental dimension is 8.12, the sustainability level turns out to be 7.92
Khalil Abbal, Mohammed El Amrani, Youssef Benadada,
Volume 36, Issue 1 (3-2025)
Abstract
In this paper, we study the Multi-Level Multi-Capacitated Facility Location Problem (ML-MCLP), which was first introduced in 2022 as a double generalization of the Capacitated P-Median Problem (CPMP). The objective of this problem is to determine the optimal facilities to open at each level, and their appropriate capacities to meet customer demands, while minimizing assignment costs. We adopt the Benders Decomposition exact approach, complemented by modern acceleration techniques to enhance convergence speed. The performance of the accelerated BD algorithm is evaluated using a dataset generated based on justified difficulty criteria and data generation methods from the literature. The results showed that hybridization of acceleration techniques, such as subproblem reformulation and cut selection, significantly improves convergence. However, decomposition-based technique proved to be inefficient, particularly due to the structure of the ML-MCLP, and was therefore excluded.
Atef Fakhfakh, Amr Noureldin, Mohamed Aboueldahab, Basem Nabil,
Volume 36, Issue 1 (3-2025)
Abstract
This paper focuses on mobile telecommunication companies (MTCs) in Egypt to investigate the impact of digital leadership (DL) on sustainable performance (SP). The mediating role played by digital organizational culture (DOC) in the relationship between DL and SP is also examined. The survey method is employed to conduct this research, and data is collected from 331 respondents. The proposed hypotheses are tested using structural equation modeling and analyzed using structural equation modeling Smart PLS V.4. The results indicate that DL directly influences DOC. SP and DOC partially mediate the relationship between DL and SP. Previous research has not extensively examined the mediating role of DOC in the relationship between DL and SP. This research is one of the first studies to demonstrate that DL positively impacts the SP of Egyptian MTCs through the mediating role of DOC.
Dwi Kurniawan, Sabila Rafa Budiyanto,
Volume 36, Issue 1 (3-2025)
Abstract
This paper studied the impact of relationships and past positive experiences on the dimensions of trust (ability, benevolence, integrity) and the influence of these trust dimensions on customer purchase intention. The measurement instrument was developed based on the literature. The study was conducted using a questionnaire completed by two hundred customers of an Indonesian Marketplace in Bandung and its surrounding areas. The data were then processed using Structural Equation Modeling (SEM). The results showed that ability and integrity affect customer purchase intentions, while benevolence does not. Additionally, we found that relationships and positive experiences in the past significantly affect ability and integrity.
Nor Hasrul Akhmal Ngadiman, Nur Syahirah Mustafa, Izman Sudin, Denni Kurniawan,
Volume 36, Issue 1 (3-2025)
Abstract
Bone tissue scaffolds that closely mimic the mechanical and biological properties of natural bone is critical for enhancing the outcomes in treatment of bone tissue damages. This study introduces an optimisation approach to designing bone tissue engineering scaffolds using Triply Periodic Minimal Surface (TPMS) structures, evaluated through a Full Factorial Design methodology. Finite Element Analysis was applied to simulate the TPMS scaffolds under mechanical loading. The influence of key factors of strut thickness, unit cell configuration, and TPMS type, on the scaffold’s mechanical performance, specifically targeting Young's modulus was evaluated. By employing Full Factorial Design, this study generates empirical models of Young’s modulus as a function of those key factors. Primitive and Gyroid TPMS structures emerged as optimal, achieving Young's modulus values of 4912.3 MPa and 4666.7 MPa, respectively, with configurations of 0.01 mm strut thickness in a 3-unit cell construct. These results demonstrate that optimised TPMS scaffolds can meet the mechanical demands of bone tissue while providing adequate porosity for cell proliferation and nutrient transport, essential for effective bone regeneration.
Atef Fakhfakh, Salaheldin Salaheldin, Amr Noureldin, Mohamed Aboueldahab, Neama Elwakeel,
Volume 36, Issue 1 (3-2025)
Abstract
This study investigates the interplay between manufacturing ambidexterity, Industry 4.0 readiness, and sustainable excellence in Egypt's food and beverage sector. It explores how Industry 4.0 readiness mediates and moderates the relationship between ambidexterity and sustainability outcomes. A quantitative research design was employed, utilizing a survey of 308 professionals in Egypt's food and beverage industry. Structural equation modeling (SEM) was used to analyze the relationships among manufacturing ambidexterity, Industry 4.0 readiness, and sustainable excellence. The results reveal that Industry 4.0 readiness fully mediates and significantly moderates the relationship between manufacturing ambidexterity and sustainable excellence. While manufacturing ambidexterity alone does not directly impact sustainable excellence, its effect becomes significant through Industry 4.0 readiness, highlighting the importance of digital transformation. This study focuses on a single sector in Egypt, limiting generalizability. Future research could explore other industries and regions or examine specific dimensions of Industry 4.0 readiness. The findings emphasize the need for organizations to invest in digital infrastructure and foster ambidextrous capabilities to achieve sustainability goals. Policymakers are encouraged to support Industry 4.0 adoption through incentives and training programs to enhance competitiveness and sustainability in emerging markets. This study contributes to the limited research on the application of manufacturing ambidexterity and Industry 4.0 technologies in developing economies, offering insights into achieving sustainable excellence through digital transformation.
Mohsen Nourizadeh, Moharram Habibnejad Korayem, Hami Tourajizadeh,
Volume 36, Issue 1 (3-2025)
Abstract
The purpose of this paper is to optimal control a dual-stage cable robot in a predefined path and to determine the maximum load-carrying capacity of this robot as a tower crane. Also, to expand the workspace of the robot two stages are employed. Today, cable robots are extensively used in load handling. Positive cable tension and collision-free cable control are the most important challenges of this type of robot. The high ratio of transposable loads to weight makes these robots very attractive for use as tower cranes. Dynamic Load Carrying Capacity (DLCC) is the maximum load that can be carried along a predefined path without violating the actuators and allowable accuracy constraints. State-Dependent Riccati Equation (SDRE) is employed to control the end-effector within the path to achieve the maximum DLCC. This approach is chosen since it can optimize the required motors' torque which consequently leads us to the maximum DLCC. In addition, the constraint of cables’ collision together is also checked along the predetermined path using the non-interference algorithm. The correctness of modeling is verified by comparing the results with previous research and the efficiency of the proposed optimal controlling strategy toward increasing the DLCC is investigated by conducting some comparative simulations. it is shown that the proposed cable robot by the aid of the designed optimal controller can increase the load carrying capacity successfully along any desired path using the allowable amount of motors' torque.
Muh Syarif, Ismie Roha Mohamed Jais, Iffan Maflahah, Ihsannudin Ihsannudin,
Volume 36, Issue 1 (3-2025)
Abstract
The research focuses on improving the performance of the corn supply chain in Madura Island, Indonesia. The purpose of the study is to identify, evaluate, and prioritize risks that have the potential to disrupt the smooth operation of the corn supply chain. The research method uses Failure Mode and Effects Analysis (FMEA) to identify risk levels and Root Cause Analysis (RCA) approach for mitigation strategies. Risk level assessment is based on severity, probability, and detectability at the level of farmers, middlemen, processing industries, and distributors. Based on the analysis, it shows that the risks are a priority in handling and prevention as well as proposals that can be made to improve the root cause of the occurrence of risks with the highest category based on the RPN value at the farmer level are the occurrence of pest and disease attacks (648), the middleman level is when the amount of corn is abundant (336), the processing industry level is the price of corn is unpredictable (252), and the level of distributors is a limitation in product promotion (324). To improve the efficiency and quality of the corn supply chain, namely increasing storage capacity, using more efficient processing technology, flexible production planning, and more innovative marketing strategies. The managerial implications of corn-supply chain risk assessment are the need to improve product quality, corn supply stability, price management, and strengthen partnerships and mutual benefits between all parties in the supply chain. Every element of the supply chain needs to encourage the adoption of modern technologies in maize cultivation, processing, and distribution to increase productivity and reduce risks associated with manual processes. It is necessary to establish mitigation strategies to address environmental risks, including the implementation of sustainable agricultural practices and early warning systems.
Dino Caesaron, Farell Ardani, Vidhea Nurhadi, Yusuf Yekti,
Volume 36, Issue 2 (6-2025)
Abstract
A typical definition of New Product Development is a series of actions that begins with the identification of a market opportunity and concludes with the creation, marketing, and delivery of a product. It is a knowledge-based process where constraints and needs are converted into a product description. The competition for businesses now centers on innovation and new products. Industries and investors are constantly looking for new upgrade methods and/or equipment to reduce costs and increase capability. One industry in Indonesia that has a tight competitive level is the ceramics industry with a growth rate of 10% per year. The main objective of this study was to create the design of specific machining sanitary Spare Parts production due to complexity of the design. In the proposed methodology, Quality Function Deployment is used to convert the subjective requirements from users into an objective technical response. Theory of Solving Problem Inventively is used to enhance the subpar design by reducing system conflicts and creating a balanced solution between two requirements. The implications of the integration of Quality Function Deployment and Theory of Solving Problem Inventively in this paper are a product design and concept of the specific machining for sanitary spare parts that have been adjusted to the needs of users.
Khatereh Rajinia, Mostafa Razmkhah,
Volume 36, Issue 2 (6-2025)
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 modelled 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 expected 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.
Saeed Dehnavi-Arani, Hadi Mokhtari,
Volume 36, Issue 2 (6-2025)
Abstract
The selection of material handling equipment is crucial for companies as it significantly impacts productivity in manufacturing and service operations. This decision-making process involves multiple criteria that are often conflicting and cannot be easily compared. To address this complexity, a multi-criteria decision-making framework is employed, where experts' preferences and criteria weights are expressed using fuzzy numbers, such as trapezoidal or triangular fuzzy numbers. The fuzzy VIKOR methodology is then utilized to rank the alternatives based on the aggregate fuzzy values of ratings and weights. A Monte Carlo simulation and a centroid method are employed to derive a suitable shape and obtain a precise value. This additional step enhances the robustness and accuracy of the decision-making process. To demonstrate the effectiveness of this approach, a case study is conducted at R.S-Arvin, a manufacturing company. By applying the proposed methodology to a real-world scenario, the study showcases how it can be used to make informed decisions in practical settings. The results obtained from this case study highlight the benefits of incorporating fuzzy logic and simulation techniques in material handling equipment selection processes. Overall, this research contributes to advancing decision-making practices in companies by providing a systematic and comprehensive approach that considers multiple criteria and uncertainties inherent in such complex systems. The integration of fuzzy logic and defuzzification methods (simulation and centroid method) offers a practical solution for addressing real-world challenges related to equipment selection and optimization in manufacturing environments.
Ahmad Aliyari Boroujeni, Ameneh Khadivar,
Volume 36, Issue 2 (6-2025)
Abstract
The Traveling Salesman Problem (TSP) is a well-known problem in optimization and graph theory, where finding the optimal solution has always been of significant interest. Optimal solutions to TSP can help reduce costs and increase efficiency across various fields. Heuristic algorithms are often employed to solve TSP, as they are more efficient than exact methods due to the complexity and large search space of the problem. In this study, meta-heuristic algorithms such as the Genetic Algorithm and the Teaching-Learning Based Optimization (TLBO) algorithm are used to solve the TSP. Additionally, a discrete mutation phase is introduced to the TLBO algorithm to enhance its performance in solving the TSP. The results indicate that, in testing two specific models of the TSP, the modified TLBO algorithm outperforms both the Genetic Algorithm and the standard TLBO algorithm in terms of convergence to the optimal solution and response time.
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k. Nageswara, Bereket Haile Woldegiorgis,
Volume 36, Issue 2 (6-2025)
Abstract
So far, several models for measuring supply chain performance (SCP) have been developed. The supply chain operation reference (SCOR) model is regarded as the most crucial in the manufacturing business. However, none of the models, including the SCOR model, are comprehensive enough to measure the overall SCP of manufacturing firms. In practice, the existing models are only used in a few of the numerous steps necessary to calculate the overall SCP. Furthermore, the existing models lack fundamental elements that a model should include. The objective of this research is to develop a powerful SCP measurement using a systematic literature review (SLR). Accordingly, this research has proposed a complete supply chain operations measurement (C-SCOM) model. The proposed model consists of four major components: the application of the SCOR model, the application of the AHP method, a template that enables overall SCP calculation, and a direction for linking supply chain management practices (SCMPS) with gap analysis. By having these features, the model provides users with the ability to calculate the overall SCP, conduct gap analysis, carry out benchmarking, and link the gap analysis outputs to existing SCMPs, which the previous models lack. The validation using the fuzzy Delphi technique reveals that the proposed model is unique in its explicitness and will be user-friendly for real-world industrial applications. Finally, this study contributes to the body of knowledge by providing a comprehensive model that could help solve the real challenges that manufacturing firms face when measuring SCP.
Mehdi Ajalli, Narges Soleiman Ekhtiyari, Peyman Zandi,
Volume 36, Issue 2 (6-2025)
Abstract
This study aims to evaluate the traditional, lean and agility criteria that are effective in evaluating the performance of suppliers and ranking them with the combined approach Path Analysis (PA), SWARA (Stepwise Weight Assessment Ratio Analysis) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) in Automation Industry. The research method is applied from the perspective of the objective and is descriptive-survey in terms of data collection. For this purpose, the sub-criteria were first extracted by reviewing the literature. Then, using PA approach, the effectiveness of these criteria in automation industry was investigated. The statistical population in this section includes 60 experts and managers of the industry, which due to the smal size, all members of the community were considered as a sample. The PA output showed that after evaluating twentycriteria, seventeen criteria were finally approved by the experts. Then, using the SWARA and the opinions of experts, the criteria importance and weight was calculated. The results showed that the criterion of "agility" was in the first place, "lean" was in the second place and "traditional" was in the last place. Then, considering the importance of ranking of lean and agile suppliers in the industry, using TOPSIS and based on the weight of the criteria, six suppliers were evaluated by experts. The results showed that the fourth supplier was ranked first. The first supplier was also ranked sixth. Finally, a sensitivity analysis of the ranking was conducted. Overall, the results show a high degree of stability of the rankings according to the method used. Thus, the model proposed in this study provides a suitable framework for evaluating industry suppliers based on key criteria of traditional, lean and agility.
Ahmad Mohammadpour Larimi, Babak Shirazi, Iraj Mahdavi,
Volume 36, Issue 2 (6-2025)
Abstract
location-inventory problem (LIP) is a significant issue in supply chain management (SCM), aiming to reduce and integrate the costs of inventory and location. Perishable-LIP (PLIP) includes products, particularly those with a short expiration date, also known as perishable items. This feature necessitates the supply chain to maintain high reliability and resilience to minimize costs faced with disruption risks. Implementing reliability and resilience in PLIP (R2-PLIP) requires methods such as lateral transshipment. These methods not only enhance the reliability and resiliency of the SC but also mitigate the risks associated with supply disruptions and demand fluctuations. Demand for perishable products is influenced by their expiration dates. By incorporating lateral transshipment, companies can ensure a more balanced inventory distribution. This study investigates the role of lateral transshipment in enhancing supply chain robustness. A multi-objective optimization model is developed, focusing on minimizing costs while maximizing resilience and service levels. The project aims to optimize the overall system efficiency. Additionally, the sensitivity analysis conducted in the research indicates that the shortage cost and the DC capacity each had the greatest variations in one of the objective functions. This research provides practical insights for designing resilient perishable supply chains.
Hendro Prassetiyo, Said Muhammad Baisa, Arif Imran, Sri Suci Yuniar, Rangga Try Anugrah,
Volume 36, Issue 2 (6-2025)
Abstract
This study focuses on optimizing vendor selection in laser cutting services through a comprehensive evaluation framework integrating the Vendor Performance Indicator (VPI) and the Fuzzy Analytical Network Process (F-ANP). The methodology quantifies vendor performance across five key criteria: quality, cost, delivery, flexibility, and responsiveness. The results indicate that product quality (39.7%) and cost efficiency (41.4%) are the most influential factors in vendor selection. Sensitivity analysis reveals that a 10% increase in quality consistency improves overall vendor ranking stability by 15%, while cost variations above 8% significantly affect final rankings. The study recommends implementing performance-based contracts, quality assurance protocols, and digital supply chain solutions to enhance vendor assessments. Collaborative partnerships with top-performing vendors can yield mutual benefits and foster sustainable practices, aligning with the company's resilience and operational excellence objectives.
Alemayehu Derege,
Volume 36, Issue 2 (6-2025)
Abstract
The booming of construction sector, including cement factories, has been great success, however, the price of cement has been quadrupled. Among others, critical shortage of cement is observed throughout the country regardless of the success, demanding a critical investigation into its supply chain, governance and regulatory system. Mixed, qualitative and quantitative approaches are applied to investigate the value chain, its administration and regulatory framework. SEM was used to index the level of cement supply distortions in the country. Samples are taken through referral technique from stratified target group across Ethiopian cement supply chain, starting from factory CEO to end-users, from purposively selected major factories. Multinomial logit model is used to analyze the determinant of cement supply distortion. The study found mis-management of regulation, high intervention with ineffective regulatory measure, opened up a room for bribery, favoritism, government interventionism and amplified the roles of intermediaries beyond the market requirement. Brokers are involved in about 85 percent of the country's total cement distribution. Besides, not only intermediaries but also the factories and their agents are contributing a lot in cement supply distortion. The supply chain distortion is observed in all market types, black, gray, and white respectively. The regulatory framework is ineffective and few regulatory bodies are fixed towards reactive measures. Majority of cement distribution is facilitated by brokers and factory agent. Hoarding and smuggling emerge as the most influential factors, with their increase being strongly and significantly linked to a rise in high and severe illegal cement distribution. Regulatory strength and administrative malpractice display complex patterns, indicating that having policies in place is not sufficient; effective enforcement is crucial. Strengthening regulatory, good governance and law enforcement system reduces the cement supply distortion while long run digitalization should be targeted along with supply side intervention.
Mehdi Abdollahi Kamran, Samira Afsharfar, Fatma Al Mawali, Reza Babazadeh, Marya Al Balushi,
Volume 36, Issue 2 (6-2025)
Abstract
One of the most critical concerns in supply chain management (SCM) is supplier selection, which significantly impacts an organization's efficiency and market agility. Balancing ordinal and basic criteria in supplier selection has become increasingly crucial in recent years within SCM. This research presents three multi-criteria decision-making (MCDM) methods including Fuzzy analytic hierarchy process (AHP) and Fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods to assess and select suppliers in oil and gas (O&G) industry. The critical criteria for supplier selection in the O&G sector have been reviewed in the literature and validated by experts actively working in the field. Initially, the Fuzzy AHP technique determines criterion weights and ranks suppliers. Subsequently, the Fuzzy TOPSIS approach is applied to rank prospective suppliers identified through objective evaluation. The findings show the capability of the utilized approaches in supplier selection procedure in O&G industry.
