supply chain management
Mehrdad kiani; davood andalib ardakani; Habib Zare Ahmadabadi; Seid Heydar Mirfakhraddini
Abstract
Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society ...
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Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society and address the environmental and economic challenges related to managing organizational operations. This research aims to analyze the factors enabling the implementation of circular economy and Industry 4.0 in the supply chain of Yazd glass factories. In the initial phase of the research, a review of various articles was conducted using the meta-synthesis method to identify and categorize relevant enablers. This process resulted in the identification of 15 enablers categorized into four dimensions: economic, human resources, organizational management, and infrastructure. In the subsequent step, the Fuzzy DEMATEL technique was employed to examine the cause-and-effect relationships. The findings indicate that, within the economic dimension, the most influential enablers are "budget allocation for the implementation of circular economy and Industry 4.0" and "stimulation of demand for circular products." In the human resources dimension, "training and development of employees" and "organizational culture" play crucial roles. In the organizational-management dimension, "support and commitment of senior management" and "cooperation and networking with supply chain partners (industrial coexistence)" are highly significant. Lastly, within the infrastructure dimension, "development of information technology standards and infrastructures" and "security and protection of intellectual property rights" are considered the most effective enablers for the implementation of circular economy and Industry 4.0 in the Yazd glass factories. The results indicate that the Ardakan glass factories of Yazd should prioritize attention to economic and infrastructural enablers when implementing circular economy and Industry 4.0.
Introduction
The concept of the circular economy can be regarded as a solution to reduce production costs within a sustainable supply chain. In this context, the integration of cyber-physical systems, big data, data mining, data analytics, the Internet of Things, and novel business models can offer significant opportunities for the creation of sustainable industrial value, value capture, and the promotion of the circular economy (Antikainen et al., 2018). Industry 4.0, often referred to as the future of supply chains, can have numerous implications for sustainability, including the optimal utilization of resources and technology (Quezada et al., 2017). Based on the sustainability axis, the concept of Industry 4.0 aids industrial managers in encompassing not only environmental protection and control initiatives but also aspects of process safety, such as resource efficiency, human resource and societal well-being, and the development of smarter and more flexible supply chain processes (Luthra & Mangla, 2018). Numerous studies have explored the factors that impact the implementation of circular economy and Industry 4.0, and these factors have been broadly classified into categories such as barriers, challenges, drivers, and enablers (Fedotkina et al., 2019). Identifying the enablers that are effective in implementation is a crucial step in enhancing the performance of a circular and intelligent supply chain. Until these enablers are identified, it is impossible to determine their relative importance. Following their identification, industry practitioners and policymakers can develop appropriate strategies for their implementation. As such, this current research aims to identify, categorize, and analyze the effective enablers for implementing circular economy and Industry 4.0 at the Ardakan Glass Factory in Yazd, which is the largest glass factory in West Asia. To achieve this, both a qualitative method for enabler identification and the technical Dimtel method using fuzzy logic for establishing cause-and-effect relationships between enablers are employed. What sets this research apart from others is its focus on identifying the combined enablers for implementing the circular economy and Industry 4.0 at the Ardakan Glass Factory Group of Yazd, as well as the network approach that examines the relationships and interactions between these enablers. Given these key elements, this research aims to address the following questions:
-What are the effective enablers for implementing the circular economy and Industry 4.0 at the Ardakan glass factories in Yazd?
-What is the effectiveness and influence, including cause-and-effect relationships, of these enablers?
Materials and Methods
This research is categorized as applied-developmental research in terms of its purpose and is classified as a field-library study in terms of its methodology. Its objective is to formulate a novel scientific model of enablers for implementing circular economy and Industry 4.0 within organizational supply chains. Given the significant number of qualitative articles that have explored the enablers of Industry 4.0 and the circular economy across various industries and the need to establish a shared understanding of these enablers, the first stage of this research involved identifying effective enablers using the meta-synthesis qualitative method. Their validity was assessed through content validity, which involved obtaining opinions from 15 organizational experts. In the second phase of the research, the researchers evaluated the effectiveness and impact of these enablers using the Fuzzy DEMATEL method. The statistical population for the first stage of the research comprised all studies published in the Scopus database, the largest text database, related to the enablers that influence the implementation of circular economy and Industry 4.0 within organizational supply chains up until the commencement of this research. In the second stage of the research, the statistical population included all professors and managers with expertise in sustainability, familiar with circular economy, and knowledgeable about Industry 4.0 technologies at Ardakan Glass Factories in Yazd. For this phase, a purposeful sampling method was used to select ten participants.
Discussion and Results
The purpose of the current research is to analyze the enablers that are effective in implementing the circular economy and Industry 4.0 within the supply chain of Ardakan Glass Factories in Yazd. In the first stage of the research, various articles were reviewed, and the meta-combination method was employed to identify and categorize relevant enablers. This process led to the identification of 15 enablers across four dimensions: economic, human resources, organizational management, and infrastructure. In the second stage, the Fuzzy DEMATEL technique was utilized to investigate the cause-and-effect relationships between these enablers. The research results revealed that the economic and infrastructural enablers are considered influential dimensions that affect human resources and organizational management dimensions. Within the economic dimension, "budget allocation for the implementation of the circular economy and Industry 4.0" and "stimulation of demand for circular products" emerged as the most effective enablers. Additionally, in the infrastructure dimension, "development of IT standards and infrastructure" was identified as the most influential enabler for the implementation of the circular economy and Industry 4.0 within the supply chain. In the organizational management dimension, "the support and commitment of senior management" was recognized as the most influential enabler.
Conclusion
While the enablers mentioned are considered among the most effective ones in implementing circular economy and Industry 4.0 in the Ardakan Glass Factories of Yazd, it's crucial for the glass industry to prioritize the most important enablers. It's essential to pay adequate attention to all identified enablers. Using specific guidelines and a checklist of effective enablers during decision-making can facilitate the decision-making process and enhance decision-making capabilities. Therefore, based on the identified enablers and their importance in this research, it's recommended to develop and provide guidelines and checklists for executive managers. Among the significant limitations of this research is the reliance on a single scientific database, Scopus, for sourcing research. It's advisable to supplement this by utilizing other databases such as Google Scholar and Web of Science. Additionally, the classification of enablers was conducted using a qualitative approach. Researchers are encouraged to name and categorize enablers using survey and quantitative methods, such as cluster analysis, to expand their research scope. Another limitation pertains to the research's statistical population, which was restricted to Ardakan Glass Factories in Yazd due to time and cost constraints. To generalize the research results, it's advisable to investigate the same research topic in other glass factories across the country. Future researchers could employ methods like fuzzy cognitive mapping and systems dynamics to examine relationships and interactions between enablers. Moreover, the enablers identified and analyzed in this research were primarily based on international studies. To adapt these enablers to the specific conditions of Iran's industries, it's suggested that in-depth interviews be conducted with industry owners. This way, certain enablers that may be unique to Iran's circumstances or require different interpretations can be revised.
supply chain management
Fatemeh Arjmandi; Parvaneh Samouei
Abstract
Planning and scheduling operating rooms and required equipment is very important for hospital managers from the perspective of cost, social, and health principles. Because operating rooms are one of the sources of income for hospitals that can provide the services needed by emergency patients who arrive ...
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Planning and scheduling operating rooms and required equipment is very important for hospital managers from the perspective of cost, social, and health principles. Because operating rooms are one of the sources of income for hospitals that can provide the services needed by emergency patients who arrive randomly and elective patients whose surgery is preplanned. Since some tools used in operating rooms need to be sterilized each time, and in the real world, due to various reasons such as the physical condition of each patient, the duration of surgeries is uncertain, in this research, as well as considering the uncertainty of surgery times for emergency and elective patients, a robust scenario-based integrated mathematical model with two objective functions is presented. In this model, in addition to minimizing the cost of operating rooms, sterile section, and penalties for delay in surgery, the competition time of the last operation is minimized. Solving several problems and different sensitivity analyses confirmed the validation of the presented model from the viewpoint of the hospital managers.
Introduction
The healthcare system is one of the most important topics that has attracted the attention of researchers and hospital managers. Two significant elements of healthcare systems are patients and hospitals, and their planning and scheduling are necessary for providing better services. Hospital managers aim to minimize costs or maximize profits while considering service times. Operating rooms are often the most critical sections of the hospital. Since life and death issues are at stake in the operating rooms, even the slightest delay or lack of resources can endanger human lives. Therefore, careful planning and scheduling of operating rooms and their resources is especially important. Additionally, to prevent potential hospital infections, the sterilization of reusable medical instruments is essential for every operation. Furthermore, patients can be broadly categorized into two groups: emergency patients who arrive randomly, and elective patients whose surgeries are preplanned. Planning and scheduling operating rooms, along with the required equipment, is of utmost importance for hospital managers, taking into account cost, social factors, and health considerations. Some items used in operating rooms need to be sterilized after each use, which incurs both time and cost.
Methodology
Due to high fluctuations of the duration of surgery, the different condition of each patient, and in order to get as close as possible to the real conditions, the duration of each surgery is considered uncertain. In this research, in addition to considering selected patients, considering the uncertainty of the duration of surgery, emergency patients have also been investigated, and dealing with uncertainties, the robust optimization approach is used. This approach is stable against changes, and minimizes the fluctuation of changes and maintains optimal and feasible. Therefore, in this research, as well as considering the uncertainty of surgery times for emergency and elective patients, a robust scenario-based integrated mathematical model with two objective functions is presented. In this model, in addition to minimizing the cost of operating rooms, sterile section, and penalties for delay in surgery, the competition time of the last operation is minimized. There are costs for performing elective and emergency operations, and in order to give priority to emergency patients, the cost of performing the operation of these patients is lower than the cost of performing elective operations surgeries of emergency patients, such as those injured in accidents, must be performed as soon as possible and these patients should be paid less. Also, for emergency patients, a maximum waiting time is considered, which they should not wait more than it. Obviously, surgeries that cannot be scheduled during the working hours of the operating room are postponed. Every patient needs a number of reusable medical tools that require sterilization. The sterile duration of reusable tools and the capacity of each sterile machine are known.
There are various techniques for solving multi-objective problems, one of which is the epsilon constraint method. In this method, one of the objective functions is considered as the main objective function and other objective functions are applied as constraints to the problem. Various developments for the epsilon constraint method have been presented to make it more efficient, among which we can mention the Augmented Epsilon Constrain (AEC) method. Moreover, in order to solve the bi-objective integrated mathematical model, Mulvey's robust method is implemented on the model, and its validation is carried out in the GAMS software with the AEC method.
Results and Conclusion
Different sensitivities all confirm the validity and accuracy of the model from the point of view of hospital managers. According to the obtained results, the changes of the three parameters of surgery delay cost, duration of surgery and sterile duration times have more effects on the both objective functions of the mathematical model than other parameters of the problem. Furthermore, the obtained results show that the first objective function, which includes the total cost, will have the highest value when the delay cost parameters and the duration of the surgical operations increase. For the second objective function, which shows the complete time of the last operation, the most challenging situation occurs when the parameters of the duration of surgical operations and the sterile duration increase. Therefore, the most ideal situation from the point of view of the hospital manager is to reduce all three parameters, which will reduce, the total cost and the completion time of the last operation; Moreover, the results show, the separate costs of planning and scheduling of the operating room and the sterile department are more than when the planning and scheduling of the operating rooms and the sterile department were examined in an integrated manner. The results of this research can be used for the integrated planning and scheduling of the operating rooms and sterilization department in all hospitals as a suitable management tool.
Maryeh Nematizadeh; Alireza Amirteimoori; Sohrab Kordrostami; Leila Khoshandam
Abstract
The electricity industry plays a pivotal role in a country's economic growth and development. Therefore, it is imperative to assess its performance and identify the strengths and weaknesses of its different sectors, such as production, transmission, and distribution, to enhance economic growth in diverse ...
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The electricity industry plays a pivotal role in a country's economic growth and development. Therefore, it is imperative to assess its performance and identify the strengths and weaknesses of its different sectors, such as production, transmission, and distribution, to enhance economic growth in diverse areas. Given the significance of the transmission sector, this research focuses on analyzing and evaluating the performance of 16 regional electricity companies in Iran from 1390 to 1398, with the aim of comprehending the impact of contextual variables on efficiency. To achieve this, the study will utilize two techniques - Data Envelopment Analysis (DEA) and Ordinary Least Squares (OLS) - to determine the efficiency score and estimate the effect of contextual variables on efficiency, respectively. In the first stage, the DEA technique is employed to calculate the technical efficiency of each company, considering their specific inputs and outputs. In the second stage, the logarithm of the efficiency scores obtained is regressed on contextual variables to establish their effect on efficiency. The residual derived from the regression is referred to as managerial ability. Finally, the companies are ranked based on their modified efficiency after removing the impact of contextual variables.
Introduction
The electricity industry comprises three key sectors: production, transmission, and distribution. It stands as one of the most crucial economic infrastructures in the country, exerting significant influence on industrial, agricultural, service, and other sectors. Undoubtedly, the growth of the electricity industry drives the nation's economic development and progress, contributing to the prosperity and comfort of its citizens (Tavassoli et al., 2020). Consequently, analyzing and examining the growth trajectory of each sector across different years becomes pivotal in mitigating adverse effects and fostering progress within this domain.
In recent years, numerous researchers have conducted studies in this field. Some have independently evaluated each production, transmission, and distribution sector, while others have adopted a comprehensive approach by considering the integrated three-stage network structure. The research background highlights that the transmission sector has received less attention from researchers than other sectors. This is noteworthy because, following electricity production, the transmission process and energy accessibility to consumers are paramount. The absence of proper energy transfer can result in consumer dissatisfaction, financial losses, and stagnation within the competitive economic market. Therefore, identifying the strengths and weaknesses of the transmission sector's performance and comparing regional electricity transmission companies can effectively help enhance the performance level of each.
One technique that has captured researchers' attention for evaluating the electricity industry's performance is the data envelopment analysis (DEA) technique. DEA is a non-parametric method used to assess the performance of homogeneous units, considering multiple inputs and outputs. It was initially introduced in 1978 by Charnes et al. The initial model was built upon the assumption of constant returns to scale. Subsequently, Banker et al. (1984) extended it by presenting a model under the assumption of returns to a variable scale.
Importantly, traditional DEA models evaluate a system's performance based on specific inputs and outputs consumed and produced by the unit. However, various factors, such as contextual variables, managerial ability, and skill, can significantly influence performance and productivity. A crucial point to consider is that managerial abilities are not always overtly visible. This lack of direct visibility can impede accurate measurement. Hence, recognizing these variables among the existing indicators and assessing their influence on the performance and efficiency of each unit holds particular significance. This procedure enhances the precision of evaluation and opens avenues for delivering enhanced solutions aimed at improving the system's overall performance.
Methodology
The objective of this study is to analyze and evaluate the performance of Iran's regional electricity transmission sector while considering contextual variables and establishing a ranking methodology based on managerial ability. This perspective enables the identification of strengths and weaknesses in the system's structure from various angles and offers appropriate solutions for enhancement. To accomplish this, the first step involves identifying all variables within the transmission section, encompassing inputs, outputs, and contextual factors. Subsequently, we determine the technical efficiency of each regional power transmission company, taking into account specific inputs and outputs, using meta-frontier technology. The concept of meta-frontier in DEA measures the gap or distance between decision-making units (DMUs) across different boundaries. This approach assumes a unified boundary for all subgroups, enabling efficiency estimation based on a single boundary (Battese, 2004; O'Donnell, 2008). Its primary advantage lies in resolving the challenge of evaluating efficiency at varying levels. As a result, meta-frontier technology enhances the precision of evaluating regional power companies over multiple periods. After assessing the efficiency of each regional electricity transmission company, we employ the linear regression method to estimate the impact of contextual variables on efficiency, subsequently yielding a measure of managerial ability. Ultimately, we introduce a method for ranking each company based on managerial ability. The advantage of the proposed method is that, in addition to reviewing and analyzing the technical efficiency of each of the companies in the regional electricity transmission sector during different periods, it will be possible to evaluate the managerial ability of each of the companies. Such a perspective allows for companies to be compared from different dimensions. Moreover, providing a new ranking criterion based on managerial ability also facilitates a better and more accurate comparison.
Results
In this study, the performance of Iran's regional power companies was analyzed and evaluated from two systems and management perspectives during the years 1390-1398. Additionally, a new rating criterion based on managerial ability was presented to compare the performance of companies during 9 time periods. In this regard, firstly, the technical efficiency of 16 regional electricity companies during 9 time periods was calculated based on the inputs of the number of employees and receiving energy from neighboring companies and the outputs of sending energy to neighboring companies and delivering energy to distribution companies, using meta-frontier technology and the DEA approach. Then, the effect of contextual variables, such as line length, transformer capacity, and loss magnitude, on the efficiency score of each company was estimated using the ordinary least squares method (OLS). Furthermore, the managerial ability of each company was determined during different periods. Ultimately, a ranking criterion was established based on the results of technical efficiency after removing the effect of contextual variables.
Conclusion
The results of efficiency measurements over 9 time periods indicate that the highest and lowest average efficiencies were observed in the years 1390 and 1398, respectively. Furthermore, it's evident that, in general, the performance of Iran's 16 regional electricity companies exhibited a consistent upward trend from 1390 to 1398. Among the 16 evaluated companies, the Guilan regional electricity company consistently achieved the highest level of efficiency across all 9 time periods, reflecting its strong performance. Conversely, the Fars regional electricity company consistently had the lowest efficiency, indicating its weaker performance compared to other companies. When analyzing the companies' performance by year, it's noteworthy that the Tehran regional electricity company secured the highest rank in 1390, 1391, and 1394, while the Fars regional electricity company held the top spot in the remaining years. In contrast, the Sistan regional electricity company consistently displayed the lowest performance throughout all periods. The assessment of management performance over the 9 time periods indicates that the Kerman regional electricity company demonstrated superior performance from 1390 to 1393, whereas the Guilan regional electricity company excelled from 1394 to 1398, outperforming other companies. Conversely, the Gharb regional electricity company exhibited weaker performance compared to its counterparts. Additionally, the results of the regression analysis highlight a positive relationship between the efficiency score and two variables: line length and transformer capacity. Conversely, the relationship with loss magnitude is observed to be inversely correlated.
Ahmad Ebrahimi; laya olfat; Maghsood Amiri; Mohammad Taghi Taghavifard
Abstract
The current research has considered the design of the four-level supply chain of perishable goods, including manufacturing factories, distribution centers, wholesalers, and retailers, in conditions of uncertainty in important parameters. The aim is to make strategic and tactical decisions, including ...
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The current research has considered the design of the four-level supply chain of perishable goods, including manufacturing factories, distribution centers, wholesalers, and retailers, in conditions of uncertainty in important parameters. The aim is to make strategic and tactical decisions, including the location, number, and size of distribution centers and wholesalers, stock levels in stocking centers, determining the flow of goods between facilities at different supply chain levels, and choosing the type of means of transporting goods between facilities. This is achieved through a three-objective mathematical model. The goals include minimizing the expected total cost in the supply chain, achieving the shortest travel time of goods in the chain, and at the same time minimizing the amount of deviation from customer demand. The presented model tries to pay attention to environmental uncertainty and consider different operational scenarios, as well as the possible approach in important parameters. This takes into account the product life cycle, the different rate of spoilage of the goods in different storage facilities, the different capacity of the facilities in different scenarios, and considering different methods of product transportation with different rates of product spoilage. All of this aims to cover the lack of previous research in the field of perishable goods supply chain design. Considering the multi-objective nature of the model and the need to create flexibility in decision-making for decision-makers, this research uses Normal Boundary Intersection (NBI), which allows decision-makers to choose the most optimal solution according to the importance of different goals. GAMS 24 software and MILP solver were used to solve the mathematical model.
Materials and Methods
This study presents a multiobjective model for designing a four-echelon supply chain (SC) in the strategic and tactical levels for fixed lifetime perishable products. The targeted SC levels include production plants, distribution centers (DC), wholesalers, and retailers. The locations of the plants and retailers are predetermined, while the locations of DCs and wholesalers will be selected from potential locations. The elaborated model seeks to minimize the total cost and product transportation time in the SC and minimize expected demand deviation as well. The Normal Boundary Intersection (NBI) method is employed for solving the model, and GAMS software is used to determine the optimal values of decision variables.
Results
This study utilizes a case study of an Iranian broad dairy company that produces eleven product groups. Data for the study were collected from historical company records and expert interviews. According to the opinions of the experts, three different operational scenarios have been extracted, and the data related to each scenario, especially the customer demand, has been estimated according to historical data as well as the corrective opinions of the managers. The results of the proposed mathematical programming model showed that changes in demand did not have unexpected effects on the values of the objective function and did not change the general trend of the answer to the problem. On the other hand, changes in the percentage of perishability of the product had far less impact on the values of the objective functions as well as the membership function. The overall result is normal, and as a result, in general, these changes represent the stability of the model against the fluctuations of important parameters. A comparison of optimal results and reality reveals that the examined SC needs a redesign of its DCs and wholesalers' locations, and hybrid transportation methods should be used.
Conclusion
Supply chain design (SCD) of fixed lifetime perishable products at the strategic and tactical levels is indeed an important issue. By considering the research gap, this study developed a multi-objective and multi-level model for SCD of fixed lifetime perishable products, and new concepts such as varying perishability rates in storage and transportation facilities are considered. On the other hand, with regard to environmental uncertainty, important parameters such as demand and capacity of facilities are considered as probable parameters. Adding environmental and social factors as new objectives, hybrid transportation methods, and horizontal interactions in the same SC levels can be considered for model development. In order to solve the proposed model, NBI has been used, which has significant advantages compared to other solution methods. By turning the answer of the optimization model into a kind of decision-making problem, this technique gives flexibility to the decision-maker to choose the best solution for their supply chain design according to the weight of each goal. Also, the decision-maker can redesign and increase the adaptability of the supply chain by changing the important parameters of the problem over time.
supply chain management
shahryar marzban; Morteza Shafiee; Mohammad Reza Mozaffari
Abstract
There is a growing concern about the social and environmental impact of the food supply chain, and the food industry faces numerous challenges. This has created significant pressure from various stakeholders to enhance the sustainable performance of the life cycle of perishable products. In this study, ...
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There is a growing concern about the social and environmental impact of the food supply chain, and the food industry faces numerous challenges. This has created significant pressure from various stakeholders to enhance the sustainable performance of the life cycle of perishable products. In this study, we aim to assess the sustainability of the supply chain for perishable products in the food industry. After examining both external and internal factors and identifying a research gap, the structure of the present study involves a four-stage supply chain. Input and output variables were selected based on perishable products and the three dimensions of sustainability. To achieve this goal, we conducted field and library studies to identify and extract relevant input, output, and intermediary indicators for evaluating the relative efficiency of supply chains in various sectors. Subsequently, we examined the supply chain's efficiency and ranked the efficient units. Given the primary focus on perishable materials, our study involved 18 dairy and meat factories in Fars province as the statistical population. We utilized WinQSB software to analyze network downtime and to model and solve the data. The results highlight that the most significant challenges faced by the companies are in the supply sector. Based on these findings, we provide recommendations for companies to enhance their performance.IntroductionIn the food industry, there are numerous inventory systems that deal with perishable items, which have a limited shelf life. These perishable items encompass a wide range of products, including food, fruits, and medicine. Given the extensive use of these products, it is crucial to model perishable products within a supply chain context. Furthermore, reviewing the contracts and regulations among the supply chain members is of great importance for decision-making in interactive conditions. This study aims to determine the most effective ordering policies at different levels of the perishable food supply chain. The goal is to maximize the overall profit of the chain while minimizing social and environmental negative impacts. Our supply chain consists of four levels, including suppliers, manufacturers, distributors, and retailers. We have thoroughly investigated the dimensions of sustainable development, ultimately leading to an assessment of the overall performance of the chain. The primary research question we seek to answer is: 'How does the performance of the perishable product supply chain align with a sustainable development approach?MethodologyIn this section, we employed the network data overlay analysis model to assess the performance of the research supply chain and determine the efficiency of the research units, with a particular focus on perishable products. Conventional Data Envelopment Analysis (DEA) models typically overlook the steps and internal processes within Decision-Making Units (DMUs). These conventional DEA models treat each company as a DMU and limit their calculations to initial inputs and final outputs. Given that DEA has been increasingly used in recent years for buyer-seller relationships, production-distribution processes, and performance evaluations in supply chains, and recognizing that a supply chain is a unique decision-making unit with not only input and output indicators but also intermediary indicators that flow from one stage to the next, traditional data envelopment analysis models may fall short in accurately and comprehensively evaluating supply chain performance due to the network or multi-stage nature of the supply chain. Hence, this study adopts the NDEA model with a fresh approach, calculating efficiency based on sustainability indicators related to perishable products in 18 manufacturing supply chains of dairy, meat, and protein products. Conducting an in-depth study to identify the significant parameters in the research field is a prerequisite for any applied research. To this end, we conducted extensive field and library research to investigate variables and indicators across various supply chain activities. This allowed us to identify and extract meaningful input, output, and intermediate indicators for evaluating supply chain performance in the supplier's sector. After reviewing existing literature, we identified 51 specific indicators that play a crucial role in the research.ResultsAccording to research findings, it is shown that the average efficiency of the supply chain for the production and distribution of perishable products in the financial year studied by the research was 0.9634% in the suppliers' sector. This average was 0.9899 in the producers' sector, 0.9903 in the distributors' sector, and 0.9707 in the retailers' sector. Therefore, the average efficiency indicates that the most significant inefficiency problems of the studied companies are related to the supplier sector. Furthermore, the overall average efficiency is 0.9950. According to the results obtained from the Anderson-Piterson Method for Employer Units Ranking, DMU3's Supply Chain demonstrates strong efficiency, and the supply chains of DMU7, DMU2, and DMU4 followed in the subsequent rankings. All supply chains were rated based on efficiency.ConclusionAmong the supply chains of the 18 companies studied in the research that deal with perishable products, the supplier process exhibits lower efficiency scores compared to the production, distribution, and sales processes. Consequently, it is recommended that inefficient companies at each stage take action to identify the factors causing inefficiency in the production, distribution, and sale processes of perishable products. This can be achieved by modeling the performance of efficient companies, with the goal of improving the efficiency at each stage and overall efficiency. Based on the model and research results, the following topics are suggested for future research: Given that most of the inefficiency is associated with the first stage of the model, it is advisable to pay greater attention to the supply of raw materials and transportation, or to select different input indicators. The supply of raw materials for factories emerged as one of the major challenges in this research, highlighting the inefficiency at the first stage. It is recommended that separate modeling be conducted to address the supply of raw materials in the food industry. The highest inefficiency in the fourth stage of the model is attributed to the limited consideration of the social dimension in sustainable development. For future research, it is suggested to focus more on social dimension indicators, such as satisfaction, motivation, empowerment, respect, mutual trust, social commitment, and the creation of suitable working conditions, as well as workers' health and safety. Regarding the inefficiency in the second stage (manufacturers), future research could explore strategies to enhance the freshness of raw materials and the shelf life of perishable products. For the inefficiency in the third stage (distributors), future research should concentrate on modeling and designing innovative distribution systems and routing for perishable products.
production and operations management
fahimeh tanhaie
Abstract
The mix model assembly line has attracted the attention of many industrial manufacturers due to its special features and the ability to adapt to market changes. This article has discussed and investigated a new approach in relation with customers, the results of which indicate the proper management of ...
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The mix model assembly line has attracted the attention of many industrial manufacturers due to its special features and the ability to adapt to market changes. This article has discussed and investigated a new approach in relation with customers, the results of which indicate the proper management of demand. The proposed model pays more attention to priority customers, and a parallel production line is defined that is faster than the main line and has workers with special skills. According to the rapid process of environmental changes, one of the things that can be considered to increase flexibility in the make to order environment is to set the conditions for rebalancing the line. In this article, the rebalancing of the line is also considered and included in the modeling, and the minimization of its costs is considered as another goal. Therefore, in this article, a multi-objective line balancing problem is proposed by examining rebalancing and vertical balancing problems. Benders decomposition algorithm is used to solve this problem. The results show that exact methods do not have the ability to solve large-sized problems in a reasonable time, but the solution time for Bander's decomposition method, considering the size of the problem, shows the appropriate efficiency of this algorithmIntroductionMix model assembly lines, known for their ability to adapt to changing market demands with minimal adjustments, are currently employed in active industries worldwide. The findings of this article also hold potential for reducing assembly line waste in the country's manufacturing sector. Drawing from the principles of lean production and the theories of Scholl and Becker, achieving an optimal production line balance can lead to the reduction of at least five out of the ten types of waste. While the topic of line balancing is crucial in itself, this research sheds light on a significant aspect often overlooked in most studies on planning mixed model assembly lines: the order-based environment. Many previous studies have focused solely on the 'make-to-order' environment and its assumptions, often neglecting balance issues. Given the paramount importance of customer roles in industries, it is imperative to introduce a framework for managing customer orders within line balancing problem models. The aim of this article is to enhance cost management and productivity in mixed assembly lines across various industries, ensuring that demands are met and assembly process constraints are addressed. To achieve this, we first develop the necessary mathematical models for each component and subsequently devise algorithms for their solutions.Materials and MethodsAn express line is defined in parallel and faster than the main line, as well as having workers with special skills. Considering the rapid process of environmental changes, another thing that can be considered to increase flexibility in the base order environment is to create conditions for rebalancing the line so that both the workload and the cost can be balanced at the same time. This reduced the reassignment of duties. From this point of view, in the proposed model in this part, rebalancing of the line is also desired and it is included in the modeling, and the minimization of its costs is considered as another goal of this model. Also, the goal of balancing the assembly line, which is to distribute the total workload between the stations as smoothly as possible, is also included in the proposed model of this part, which is also called vertical balance, so that each station has a balanced amount of work. Be in a work shift. Therefore, in this model, a multi-objective problem of determining the balance is designed by examining the problems of rebalancing and vertical balance. The orders coming into the organization are prioritized first, because in the order-based production environment, the delivery time of orders is very important, especially for high-priority orders, because customers expect an appropriate response in a short period of time. This prioritization can be done by any method, the output of which determines regular customers and priority customers. After determining the priority of the orders and paying attention to the main line and the designated vanguard, priority orders can be entered into the Parallel line, which operates faster and has multi-purpose operators.Discussion and ResultsIn order to validate the model and ensure the correct performance of the combined benders algorithm with the LP metric method, first the mathematical model in a small size is solved and a comparison between the results and the proposed algorithm is done. Finally we used the proposed algorithm in the large size that the gams software is not able to determine the answer. The L-P metric method obtains the optimal solution in small sizes, but in large sizes, when we give 3600 to 10800 seconds to the solver, it cannot obtain the optimal solution and requires another method to solve. The results of the comparisons show that the LP-metric method does not have the ability to solve large-sized problems in a reasonable time, but the solution time for the benders decomposition method, considering the size of the problem and the obtained answers, shows the appropriate efficiency of this algorithm.ConclusionsFlexibility in the production lines is very important and it should be able to respond to the demand when customer orders change. Therefore, the definition of a mix model line provides flexibility in responding to customer demand and reducing the delivery time for priority orders. When we are faced with a large volume of orders, it can be useful to do things in parallel line. This issue, which is rarely seen in research, is presented in the balance model of this article in the form of two parallel lines. This issue is especially effective in industries such as automobile manufacturing.
Industrial management
davod dehghan; Kiamars Fathi Hafshejani; Jalal Haghighat monfared
Abstract
The importance of mass biology has increased due to pollution caused by biomass burial, the profitability of biomass energy, and the demand for energy in the supply chain network. The goal of this research is to design a model for the biomass supply chain network with an economic and ecological approach ...
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The importance of mass biology has increased due to pollution caused by biomass burial, the profitability of biomass energy, and the demand for energy in the supply chain network. The goal of this research is to design a model for the biomass supply chain network with an economic and ecological approach to reduce costs and carbon emissions. Research gaps have been addressed, which include determining desired and undesired process outputs, along with simultaneously examining material supply disruptions and final product demand. The mathematical model used is a mixed-integer linear programming model. The primary objective is to minimize costs, and the secondary objective is to minimize carbon emissions. To address this in a single-target function under uncertainty, the fuzzy TH mathematical model has been employed. Uncertainty and disruptions have been studied through scenario building. The model's validation includes a case study in Fars province, where the findings justify the construction of four power plants. The proposed model improved the accuracy of electricity production predictions by 2.1 percent. An analysis and sensitivity study was performed on the TH method's parameters and changes in customer demand values according to predictions. The results show that the proposed model performs well, achieving cost-effectiveness through the integration of economic and ecological approaches. It also successfully reduces greenhouse gas emissions, enhances energy security and stability, and demonstrates a positive impact.
Introduction
More than 70 thousand tons of biomass waste are produced in Iran daily. These waste products result in the generation of methane gas and carbon dioxide, leading to severe air pollution and climate changes in the country. Given that 14% of Iran's electricity production comes from hydropower, and the nation is grappling with drought, electricity generation has decreased, leading to government-imposed power cuts, particularly in industrial areas. To address the need for biomass resource investment in energy production, the main challenge is the absence of an optimization model for the biomass supply chain that encompasses all relevant factors. Hence, this research aims to design a flexible optimization model for the biomass supply chain, offering insights to investors on how to produce energy with reduced costs and lower carbon emissions. Key research gaps identified are as follows: 1-Simultaneously addressing uncertainty arising from disruptions in the first two levels of the supply chain, encompassing biomass supply from raw materials, and examining the fourth level - the customer level - by defining scenarios. 2- Innovatively considering capacity levels in the context of the biomass supply chain, a subject not widely explored before. 3- Focusing on the production of bioenergy in conjunction with by-products. 4- Deliberating on the definition of desired outputs at separation centers. 5- Highlighting the importance of considering undesired outputs at separation centers. 6- Proposing a stochastic-probabilistic-fuzzy planning approach to enhance flexibility, particularly in managing risks and operational disruptions.
Research Method
This network encounters two types of uncertainty, both of which cause disruptions. Consequently, four scenarios have been devised to address these disruptions: 1- The scenario involving reduced raw material supply due to drought's impact. 2- The scenario in which electricity demand decreases in response to specific conditions. 3- The scenario where both of the aforementioned scenarios occur simultaneously. 4- A scenario without any disturbances. As a result, a resilient model has been developed to manage disturbances while ensuring environmental sustainability. The proposed model is a mixed-integer linear programming mathematical model with two objective functions: cost minimization and carbon emission minimization. The model is solved using the exact solution method in conjunction with Gomes software. To address function targeting under uncertainty, the fuzzy TH mathematical model has been employed. The model's validation has been examined through a case study in Fars province.
Findings
Several findings have emerged from the study: The construction of four power plants is recommended, each to be located at one of the ten proposed sites, with each having a different capacity. The proposal includes the establishment of four biomass separation centers. Different types of biomass are utilized in the power plants in varying proportions. Biomass transportation involves three types of transporters with capacities of ten tons, fifteen tons, and twenty tons. The quantity of these transporters varies across different separation centers and power plants. Electricity is supplied to six different applicants. The quantity of fertilizer produced varies according to different scenarios and time periods. The sensitivity analysis reveals that increasing the coefficient of the first objective function results in a decrease in the values of the first objective function. Conversely, decreasing the coefficient of the second objective function simultaneously leads to an increase in the value of the second objective function.
Conclusion
The model designed for this purpose is a sustainable development model that encompasses two of the three sustainability aspects, namely, the reduction of greenhouse gas emissions and the minimization of economic costs. Therefore, it is a resilient model that employs a scenario-based approach to address various forms of uncertainty. In the case of this study, raw materials were procured from nine out of ten biomass supply centers, indicating resilience in terms of biomass supply. The model optimally allocates resources among the supply chain members to minimize greenhouse gas emissions while also considering cost-effectiveness. The inclusion of favorable and unfavorable outputs in the model impacts the annual electricity production of each power plant. Without these variables, the model would overestimate electricity production. Sensitivity analysis reveals the trade-off between objective functions, confirming the model's correct and logical performance. Therefore, the model's validity is established. It is recommended that, in further development of this model, specific travel times for trucks between locations be included in the model.
