PRODUCTION AND OPERATIONS MANAGEMENT
Year:2020 | Volume:11 | Issue:2 (21)|Papers Count:6

Purpose: The problem of wheat production sustainability is an important issue that quarantines the availability of people's food at present as well as the nutrition of the next generations. Food is the essential human's need and has been used from human beings' creation until the end of its life. The existence of systems satisfying such requirements and the sustainability of them is always essential for the survival of the human race. Therefore, this study aims to investigate the sustainability of the wheat production system in Iran. Design/methodology/approach: In this research, using the system dynamics approach, the sustainability of Iran's wheat production has been studied. The literature review section of this paper concentrates on several research papers in this context, considering the systems dynamics approach. In this study, an introduction has been expressed to the human's need for food and the position of wheat as the primary source of food in meeting this need in Iran. System dynamics is one of the most commonly used approaches for modeling and simulating environmental and socio-economic phenomena. The wheat production system covering environmental, economic, and social subsystems has been taken into consideration as a case to model the problem. Key factors affecting wheat production have been collected based on a literature review. 50 years historical data for essential factors such as rain, wheat harvesting area, agricultural technology, fertilizers, population, wheat imports, and exports have been used in modeling and hence in the mathematical formulation of the problem. Based on the history of these factors and related research, the dynamic hypothesis of the problem has been defined, and the causal diagrams of the relationships between critical factors and the wheat production have been developed. After modeling and formulation, the problem has been simulated and validated. Then, various scenarios have been proposed and simulated for the sustainability of the wheat production system, and the results have been addressed. The scenarios for changing the machinery level, reducing chemical fertilizer's use, increasing organic fertilizer use, and rainfall fluctuations have been simulated one by one, and their combinations have been simulated, respectively. Findings: The simulation results indicated that the production of wheat is highly sensitive to precipitation and technology levels in the field. Therefore, it is better to focus more on such two factors and to have more concentration on them. Since water is the most crucial resource in wheat production, it would be better to concentrate the research and development efforts on water management technologies in the field. Due to the high sensitivity of wheat production to precipitation fluctuations and technology levels, more investment and better plans should be provided for the better and more efficient use of the two sources. Research limitations/implications: While numerous factors such as pesticides, seeds, planting and harvesting, irrigation methods, management, human resources, and related requirements affect wheat production, due to the large scale of this research, only the most critical factors were selected for the study. Examining the behavior of each of the above-mentioned factors will result in a better awareness of the existing reality and better planning for wheat production. Practical implications: The wheat production system includes environmental, economic, and social subsystems as well as numerous and complex relationships between the human and the environment. The systemic nature of such interdependencies and interactions needs systematic approaches and integrated assessment tools. Identifying and modeling correctly the intrinsic characteristics of the wheat production system assure preserves or increases its essential results over the time and help governmental organizations and institutes to move towards sustainable development and to set policies that encourage positive changes. Social implications: Since the proposed model is expected to help the government and agricultural institutions in planning wheat production efficiently, it will make the country move towards selfsufficiency in wheat production, which in turn results in psychological and social security in terms of food and increases social sustainability. Originality/value: To the best knowledge of the authors, there is no comprehensive investigation on the sustainability of wheat production in Iran. The literature review indicates that the agricultural context is almost limited to a particular zone and this problem has not been addressed on the national scale. Thus, this is the first research that examines such a problem.

Purpose: The Technology readiness level (TRL) measure is a scale for calculating the maturity of a unique technology according to operational application in the environment of a system. when the TRL from level 1 of unique technology is transferred to the context of the system, a more comprehensive set of communications may establish. Similarly, the consideration of integration, interoperability, and stability from the perspective of the system in an operational environment is important. To alleviate the concerns of the operating system level, the dynamic measure of system readiness level (SRL) is studied, which includes both TRL and integration readiness level (IRL), simultaneously. Design/methodology/approach: Since SRL is a mathematical combination of TRL and IRL and is a criterion for Improvement evaluation in the development of the main-system and infrastructure, in this paper uses the error mean method and utilization of TRL and IRL have been used and the level of readiness of the electric system of an ejection seat of a fighter has been examined and estimated. To facilitate the calculation, the design structure matrix (DSM) has been used to visualize the components and perform the necessary calculations. Findings: According to the estimated value of the readiness level of the system (3. 95), it is concluded that the system under study is at the entrance of the construction development stage, and stabilization at this phase is achieved by performing various and frequent tests of the system. The system meets the needs of the mission by achieving the ability to be operational. Research limitations/implications: The most important limitation of this paper is the lack of accurate access to tests and experiments performed to evaluate system performance and components within the system (to check how the connections work, establish a common language, ability to control, etc. ). Therefore, to determine the levels of readiness at each level, considerable time should be spent to explain the requirements to the industry and to receive information from the engineers in the industry. This in turn can affect the accuracy of the work to some extent. Practical implications: One of the most important applications of this paper is that it can provide some of the information needed for the managers of authorized or sanctioned institutions so that a project can move to the next stage of development in a step-by-step process through specific review gates. Also, industry managers can increase the speed of achieving the design and development of their desired products by formulating the requirements for readiness and maturity (management) of the required technologies. Social implications: The results of this study can determine the level of readiness of a system. In addition to avoiding the very high costs (human and financial) resulting from the failure of operations, as expected from the designed system, by the application of the proposed approach, the managers and designers can be informed about the current state of the project. This enables them to plan the next steps of their project. Originality/value: This paper aims to propose a relatively new method for estimating the level of readiness of a system based on understanding the level of readiness and maturity of the system designed to be used in a specific mission using the error mean method, block diagram, and DSM. This study contributes to the examination of the level of readiness of a simple subsystem of the main system, i. e. ejection seat. Also, in this paper, the exact design structure matrices have been used which were obtained from the previous study of the authors. Similar to the previous research work, the symmetric matrix was not studied for simplicity. Therefore, the findings are more valid than the earlier study.

Purpose: To connect and share resources between industrial units with unused resources on the one hand, and production systems in need on the other, a concept called “ sharing economy " can be used. If sharing economy is sufficiently explained, and its theoretical aspects strengthened, more actions perform to make this concept practical. Therefore, in the present study, after studying the literature and previous studies, the components of sharing economy are identified and generalized to production systems. Utilizing a sharing economy will have a significant impact on increasing the productivity of production systems through resources sharing. Design/methodology/approach: In the first phase of this research, the library study method used to collect data and information. Content analysis method used to analyze the data and identify the dimensions and components of the sharing economy. Then, in the second phase of the research, the interview process and expert opinions were used to determine the dimensions, elements, and examples of sharing economy in production systems. After extracting questions from the concepts extracted from the first phase of the research and after conducting the interview process and summarizing it, the components and dimensions of the sharing economy in production systems validated and their examples identified. Findings: In this study, the components of sharing economy in production systems identified as follows: resource sharing, shared parties, forms of sharing, information and communication exchange system, ownership and access conditions, surplus capacity, exchange benefits for sharing parties and others, and social issues in sharing. These elements categorized into four dimensions: sharing mechanism, sharing requirements and conditions, sharing purpose, and sharing consequences. Research limitations/implications: Considering the wide range and levels of coverage of the concept of sharing economy and its various operational areas, summarizing the definitions and extracting the components is highly complicated. It also seems hard to reach experts who work in the field of production systems and sharing economy or those who are familiar with its concepts. The following study subjects suggested to develop sharing economy in production systems: i) counting and examining the challenges facing the sharing economy, such as legal issues, building trust, ethical issues, insurance and taxes, and providing solutions to solve it; ii) the role of resource sharing and sharing economy in lean, agile, sustainable, green, and resilience of production systems; iii) the role of social issues regarding the sharing economy in production systems or designing a socio-economic model for it; and iv) determining the type of relationship between the dimensions and components of the sharing economy and how they affect and intensify each other with the help of methods such as structural equation modelling. Practical implications: The use of sharing economy leads to better use of resources and reduced cost of using it, reduced product cost, increased competitiveness and ultimately improved efficiency and productivity of the production system. For the supplier of resources, resource sharing in production systems leads to the prevention of stock death, earned profit and strengthened financial resources; and for the recipient of resources, it leads to reduced cost of access to resources and investment, and thus saved liquidity. In addition to the sharing parties, intermediaries and service providers, government and government agencies, the country's economic market, the working community, society, consumers and even scientific and research centres benefit. Social implications: Resource sharing in production systems can affect or be affected by social issues. The attitude of rulers and politicians in governing society and passing laws, and overseeing their implementation can affect the concept of a sharing economy. Sharing helps in increasing social capital in the areas of education and public awareness, building trust, increasing interactions, and connecting production systems with social participation, and increasing the general level of community culture. Sharing strengthens a sense of social responsibility and can also be significant in the field of social justice and reducing social harm. Originality/value: If the concept of sharing economy explained sufficiently and its theoretical aspects strengthened, it can be operational in the next steps. In this regard, in this study, the dimensions and elements of the sharing economy in production systems identified. These dimensions and components can provide the basis for designing a practical and operational model for implementing a sharing economy in production systems, can reduce the gap between practice and theory, and can guide managers and business activists and those involved in the field.

Purpose: Cross-docking is a strategy in logistics management in which products from one or more suppliers are distributed directly to customers with a minimum loading or storage time. Cross docks act more as an inventory coordinator than as a storage warehouse. Finding a proper location is a critical issue in cross-docking. The page rank algorithm in social networks is one of the methods used to locate the accessible nodes in urban-networks. However, in the application of page rank algorithm in the location problems, only location access to the other nodes of the network has been considered, whereas, in cross docks’ location problem, the distance between the nodes, directly and indirectly, is of high importance due to the one-way nature of some routes and the average closeness of the cross docks to all nodes of the network in general. Thus, this research aims to develop the page rank algorithm in cross docks’ location problem, recognizing the distance between nodes with a weighted distanced adjacency matrix, besides considering the access and closeness to the different nodes of the network. Design/methodology/approach: The page rank algorithm developed by Agryzkov et al. (2012) in a way that the binary adjacency matrix of the path between nodes is changed into a weighted adjacency matrix, in which each element of the matrix in a row ‘ i’ and column ‘ j’ denotes the distance between ith and jth locations in the map. Besides, the main criteria of the Social Network Analysis (SNA) approach, such as Closeness centrality and Eigenvector centrality, also used to develop the model. Finally, the maximum covering location model in the network has been created by considering the output of the developed page rank algorithm as the input. To investigate the validity of the developed algorithm, it is applied in a practical cross docking problem and is solved by using the GAMS software. Findings: The developed page rank algorithm was applied to find the best locations of cross docks for an online store in the western half of district 3 in Tehran. The location points identified by the algorithm seem reasonable since they have access to the main highways allowing for easy and timely delivery of orders to customers distributed all over the investigated area. Research limitations/implications: Authors did not consider limitations such as the cost of renting and purchasing warehouse and the physical and traffic feasibility of the location points in the developed model. As a suggestion for future study, the model can be further developed by considering such features. Practical implications: By using the developed algorithm, the time of delivering goods and services to the customers by online stores would reduce, which not only increases the customers’ satisfaction but it also declines the company’ s costs, significantly. Social implications: Timely delivery of orders to customers elevates customers’ feeling of safety and trust. Thus, it augments the online shopping habit of customers, leading to saving time, energy, and cost. Originality/value: Previously, the page ranking algorithm used in finding the best locations of advertising billboards in the urban map. Regarding the nature of a billboard location problem, only access/lack of access to a point determines the importance of a place, while in cross-docking location problem, in addition to access points, the distance of these warehouses, directly and indirectly, and the average proximity of them to all points of the network is of great importance. The algorithm developed in this study, in comparison with the previous version, not only considers the access of location points but also reflects the proximity of points through direct or indirect paths.

Purpose: One of the salient features of today's competitive world is the widespread use of Information Technology. E-business, which has grown significantly in recent years, has many benefits for organizations, customers and the community. The purpose of this study is to find the best policies to improve the demand response rate in online sales in e-business. In this study, the main variables of the study is identified, using system dynamics and the demand response rate is forecasted and described as the core variable. By creating a simulation model, different policies implemented, and the results and consequences of each are studied. Out of them, only those policies that guarantee the growth and success of the business, in reality, are selected. Design/methodology/approach: Using System Dynamics, the main variables of an online home food distribution system has been identified and their interrelationships created in the form of cause and effect loops and state-flow model. The data needed to simulate the system, obtained from interviews with business executives as well as internet search, and the model simulated using the Vensim software for 72 months. After validating the model using appropriate tests, to validate the model, the proposed policies implemented, and their results compared with the current performance of the system. For this purpose, SPSS software and paired comparison test used to analyze the data obtained from the simulation and to find the policy that made a significant difference at the 5% error level under conditions of the current system. Findings: The simulation results of the proposed policies indicated that it is possible to improve the demand response rate by holding training courses, increasing production to the extent of capacity, as well as combining these two policies. Findings also indicated that increasing the food prices and implementing advertising programs did not affect improving demand response rates. The statistical analysis resulted in an insignificant difference for the second policy at 95% confidence level. The third policy emphasized increasing the number of food produced to the production capacity. The results of this policy indicated a significant difference between this policy and the current system at the 5% error level. The fourth policy suggested an increase in the final price of food. There was a significant difference at the 5% error level. However, due to the value close to the significance level of 0. 05, it was not suggested to implement the policy. The last policy implemented in the system was a combination of the first and third policies. At the 95% confidence level, the fifth policy was significantly different from the current state of the system. Research limitations/implications: Due to the large size of the model, variables such as revenue and profit entered into the system. The variables of food quality, customer's expected quality and customer's complaints removed from the model because they did not directly affect the behaviour of the main variables. Moreover, the variables of raw material prices and final food prices considered as average since it was not possible to enter different daily prices for more than 80 types of food. Practical implications: The proposed model helps managers to evaluate the results of their suggested policies efficiently before their implementation and to make effective policy. Making the first policy, i. e. holding a training course, has affected all of the three variables of demand response rate, production capacity and profitability, significantly; hence managers are advised to put significant emphasis on such policy. Also, increasing the production to the maximum capacity was associated with a slight increase in the studied variables; hence, making this policy was not recommended. Furthermore, the simultaneous implementation of the training course and equalization of the number of food produced with the production capacity, each of which alone significantly changes the behaviour of the main variables, and can significantly increase the demand response rate, production capacity and profitability. Therefore, it is a suitable choice for managers and decision-makers to combine and implement these two effective policies simultaneously. Originality/value: By the use of System Dynamics approach, the causal relationships between different variables of the internet business system transformed into a dynamic model and the interactions of variables over time simulated. In similar studies on simulated e-business by a system dynamics approach, the simultaneous impacts of the production, demand, sales, and investment subsystems have not investigated.

Purpose: Supply chain management has always been of interest to researchers because of generating competitive advantage, such as reducing costs and increasing customer service levels. However, the mathematical models that can take into account the specific conditions of today’ s supply chain are negligible. The impact of factors such as the level of production quality on the returned items rate is one of the subjects that have received less attention. In this research, the mathematical model of the closed-loop supply chain developed concerning supplier selection and the effects of the quality level of provided raw material into the returned items rate Design/methodology/approach: The investigated supply chain is a two-level closed-loop supply chain modelled with a multi-period time horizon. If there are defective products, customers can deliver the products to the collection centres and receive new products. In each period, the returned items rate depends on the level of production quality, and the level of production quality depends on the quality of raw materials provided by suppliers; thus, the returned items rate is indirectly affected by the quality of raw materials. Such is a subject that was not studied earlier. Findings: Case study represents a real example of production and recycling of LED lamps. By comparing the financial data announced by the company with the results obtained from the model, the model showed a 3. 37% improvement in the objective function. In the current situation, all materials purchased from only one supplier at quality level B (out of the three quality levels A, B and C); in the optimal case, however, most of the purchased materials are at quality level A. Research limitations/implications: The relationship between quality level and the return rate is recognized by considering nonlinear functions, resulting from the fitting of these functions with real data. Also, the assumptions of multi-products in the supply chain and lateral transshipments between distributors/suppliers suggested for further study. In the case of considering multi-products, different selling prices are reasonable for the products. Also, greater profitability is achievable by considering coordination among the members of the supply chain. Practical implications: As practical implications, manufacturers can use this optimization model to i) determine the amount and quality level of raw materials provided by each supplier at each period; ii) determine the amount and quality of the final product produced at each period; iii) specify the number of distributors' orders at each period as well as the number of backorders; iv) determine the amount of returned items at each period. Thus, solving the model provides a comprehensive plan to the manufacturer in various dimensions of production. Social implications: This theoretical-practical research performed to investigate one of the main problems of production systems. Unfortunately, in recent years, critical economic conditions, sanctions, and currency fluctuations have caused suppliers to provide raw materials with lower qualities instead of materials with high quality. These low-level materials also have an impact on the final products during production and reduce their quality level. As a result, the return rate of defective items increases and consequently, the loss of the company increases. Therefore, like what happens in the real world, the manufacturing company has to choose a combination of the materials with different qualities from the suppliers to maximize the company's profit. Mathematical modelling is needed to solve such a problem, and current research is an attempt to reach this mathematical model by considering all aspects of the production process. Originality/value: The main novelty of this research is considering the quality levels for raw materials and its indirect effect on the return rate of defective items; so that the quality level of raw materials determines the quality level of final products, and the quality level of final products affects the returns rate. For this purpose, an integer programming method developed to formulate and solve the model.