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Global supply chain decisions, such as facility location, manufacturing system design, resource allocation, and distribution center location are long-term strategic decisions in nature and involve many uncertainties. Traditionally, a hierarchical approach is used design supply chain networks and manufacturing systems. First, the location of the fac...
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... Supply chain management has been a buzz term especially after Covid-19 pandemic with the supply chain disruptions affected daily lives of households. Supply chains are complicated systems which integrates entities such as suppliers, manufacturers, warehouses and distributers to fulfill customer requirements (Erenay, 2016). The demand for supply chain professionals is growing, and BLS is projecting that the employment in logistics by 18% annually from 2022 to 2032 (BLS, 2024). ...
... Some studies introduced the multi-stage manufacturing system in terms of a combination of assembly, machining, semiconductor fabrication, pharmaceutical manufacturing [7]. Others studied a multi-stage manufacturing system in the supply chain system, where the products are moved through several stages from the suppliers to multi-manufacturing stages at a different place and customers [8][9][10]. Additionally, Vaghefi, and Sarhangian developed a mathematical model to maximize the inspection plans for the multi-stage manufacturing system subject to minimize total inspection-related costs [11]. ...
Over the last several decades, designing cellular manufacturing systems has remained an active research area, where the machines are assigned to cells and products to product families. Two types of cellular manufacturing systems, layered and classical manufacturing systems, have appeared in the literature dealing with deterministic and stochastic processing times and demand. However, it has been observed that designing the cellular manufacturing systems using the multi-stage approach reduces the total number of machines required in the system. In this study, two phases are utilized to design the multi-stage cellular manufacturing system under a deterministic environment. Phase I groups the machines into stages based on maximizing the similarity among machines without and with the predetermined number of stages using a novel linear mathematical model. The sequence of machines is taken into consideration, and machine duplication is not allowed between stages. Afterward, Phase II assigns the products into product families and their corresponding machines into classical mini-cells. The product families are formed in each stage based on maximizing the similarity among products in a stage using a mathematical model. However, the results obtained illustrate the ability of the multi-stage cellular manufacturing system to reduce the total number of machines compared to the single-stage cellular manufacturing system. The results also show that the total number of machines increases as the number of stages in the system decreases. Additionally, the predefined number of stages is important to reduce the total number of machines.
... SC network design describes how the many functions and activities, implemented by a variety of organizations, are integrated to achieve SC goals. Erenay (2016) indicated that SC managers should realize the issue of design considering aspects such as locations of prospective consumers, available suppliers, labor rates, transportation expenses, etc. Besides, SC designers take into consideration the boundaries of the numbers, locations and capacities of the facilities including plants/producers, warehouses, and distribution centers. Design decisions are also made on shipping aspects of goods considering quantities and delivery modes. ...
... Klibi et al., (2010) indicated some strategic issues that should be considered in SC networking design such as the targeted markets, pricing, manufacturers' location and distribution centers, technology embracing, product design, capacity planning, supplier choice, etc. The tactical decisions are made for short-duration commitment for activities on a weekly or monthly basis and made by the middle manager considering distribution management, inventory management, production planning, forecasting, etc. (Wisner, 2016;Stevenson, 2018;Erenay, 2016). Lastly, operational decisions level is considered for day-to-day operations and made by operational managers including activities such as scheduling, sequencing, production management, vehicle routing decisions, etc. (Wisner, 2016;Stevenson, 2018). ...
Not only has the COVID-19 outbreak brought about public safety challenges, but there has also been a major disruption in the business world that impacts one and all from small to large businesses. During This pandemic, supply chains (SCs) have witnessed disruptions, and this has inspired the interest of this paper. Therefore, the objective of the paper is to address two research questions pertaining to exploring the emerging SC aspects in the age of COVID-19 and future directions of SCs. To achieve this objective, a methodology is developed entailing three steps as follows. First, data is collected and included documents are identified through PRISMA strategy. Second, document analytics is performed using the web-interface of bibliometrix package in R software,the shiny app. Third, the research questions are addressed accordingly. The results showed that the most prominent terms related to SCs include supply chain disruptions, supply chain management,supply chain resilience, viability, and flexibility. Consequently, the first research question is approached in which the aspects of SC disruptions, resilient SC, viable SC,Sustainable SC, and SC management, are addressed. With more focus on building resilient SC in the short-term to recover from disruptions, viable SC can be created in the long-term perspective, which eventually build sustainable SC accordingly. Subsequently, considering these aspects enable successful SC management. Additionally, the future directions are explored including the transformation from globalization to regionalization perspective, focus on digitalization, need for holding more inventory, managing SCs for high resilience, more dependence on operations research and business analytics, and reconsideration of food SCs. This paper contributes to the body of knowledge by providing insightful research agenda to scholars and practitioners concerned in exploring more of the influences of the current pandemic on SCs.
... SC network design describes how the many functions and activities, implemented by a variety of organizations, are integrated to achieve SC goals. Erenay (2016) indicated that SC managers should realize the issue of design considering aspects such as locations of prospective consumers, available suppliers, labor rates, transportation expenses, etc. Besides, SC designers take into consideration the boundaries of the numbers, locations and capacities of the facilities including plants/producers, warehouses, and distribution centers. Design decisions are also made on shipping aspects of goods considering quantities and delivery modes. ...
... Klibi et al., (2010) indicated some strategic issues that should be considered in SC networking design such as the targeted markets, pricing, manufacturers' location and distribution centers, technology embracing, product design, capacity planning, supplier choice, etc. The tactical decisions are made for short-duration commitment for activities on a weekly or monthly basis and made by the middle manager considering distribution management, inventory management, production planning, forecasting, etc. (Wisner, 2016;Stevenson, 2018;Erenay, 2016). Lastly, operational decisions level is considered for day-to-day operations and made by operational managers including activities such as scheduling, sequencing, production management, vehicle routing decisions, etc. (Wisner, 2016;Stevenson, 2018). ...
... These industries that are mostly labour-intensive industries requiring high operator involvement. Similar data structure was used by (Suer and Maddisety, 2005;Erenay, 2016). According to Erenay (2016), in the supply chain of fashion jewellery industry, the manufacturer produces most of products through three phases: pre-plating operations such as finding, deburring, casting, degating, tumbling and buffing, plating operations such as chain plating, barrel and manual plating and post-plating operations such as dying (frosting), welding (soldering), linking, stone setting, enamelling, finishing, oven, inspection and carding and packing. ...
... Similar data structure was used by (Suer and Maddisety, 2005;Erenay, 2016). According to Erenay (2016), in the supply chain of fashion jewellery industry, the manufacturer produces most of products through three phases: pre-plating operations such as finding, deburring, casting, degating, tumbling and buffing, plating operations such as chain plating, barrel and manual plating and post-plating operations such as dying (frosting), welding (soldering), linking, stone setting, enamelling, finishing, oven, inspection and carding and packing. It is considered that carding and packaging operation is required for each product. ...
... In this study, the prices of the machines used are based on the research of (Erenay, 2016). The useful life of a machine is assumed to be five years. ...
In supply chains, businesses compete to meet customer requirements by leveraging their competitive operational capabilities. In this paper, the manufacturer in its supply chain, faces uncertain market demand environment. Based on the products, operations and demand information, the manufacturer makes decisions to design its manufacturing system that saves time and effort in the production process. The methodology followed in this paper includes four phases. In Phase 1, the manufacturer benefits from the grouping of the similar products into families to save time and effort in the production and eventually the related machines are formed accordingly. In Phase 2, the decision of manufacturing system layout or design, considering a stochastic customer demand, is made including cellular manufacturing system design. In Phase 3, the expected profits generated by the system designed to meet the demand of product families are determined and optimal design is selected accordingly. In Phase 4, the problem of determining the optimal profits and quantities of the individual products in families, considering multi-demand coverage levels, is tackled using a proposed mathematical model, then results are analyzed. The results showed that similar products are grouped into four product families using p-median mathematical model and machine cells are formed accordingly. Consequently, the cellular manufacturing systems is designed for each family and the decision on the optimal number of cells is made based on the maximum expected profits generated by the system designed. Further, the problem of finding the optimal profits by individual products in families is studied considering three demand coverage probability scenarios: non-demand coverage restriction, only lower bound-demand coverage restriction and both lower and upper bounds-demand coverage restriction. Maximum profits are generated when the decision does not include any restriction on the demand; however, the product that has the lowest processing time is produced and sold where other products are not. This may leave the decision maker with either keep-the-winner perspective or not depending on the policy implemented in the competition process. Better decisions are made when more information is shared about the customer requirements.
... The fashion jewelry company uses mostly plated metals and synthetic precious stones to make jewelry. The precious jewelry company depends on precious metals such as gold, and platinum to build its products, like (rings, bracelets, necklaces, etc) [13]. The products of fashion jewelry industry are not very expensive and therefore sales volumes are higher and many competitors operate in the market. ...
In a manufacturing facility, the decision maker considers customer satisfaction as an essential priority in which customer due dates should be met. The cell loading, scheduling and the total manpower are considered among the main decisions in a manufacturing system. Three performance measures are studied in this paper and they are the number of tardy jobs, total manpower, and average flow time. Two approaches are proposed to handle such performance measures. In the first approach, lexicographical analysis is proposed to achieve the objectives, when the performance measures are not equally important. A three-phase methodology is introduced. In the first phase, a mathematical model has been used to maximize the output rate by allocating manpower to operations for several manpower levels. In the second phase, another mathematical model is developed based on the results of the first phase to minimize total manpower such that no job is tardy (i.e., the number of tardy jobs (NT = 0)). In the third phase, a mathematical model is also proposed to minimize the average flow time based on the results obtained in the first and the second phases. The second approach allows varying weights for minimizing average flow time and total manpower subject to zero tardy jobs due to considerations for customer satisfaction. Thus, a two-phase methodology is followed, and a bi-objective fuzzy mathematical model is developed. Two-phase methodology produced similar results to three-phase methodology for certain values of weights assigned to performance measures. Three-phase methodology was efficient for lexicographical analysis. Furthermore, the number of cells in the system is affected by the nature of due dates. The number of cells and total manpower increase when the due dates are tight and decrease when the due dates are relaxed.
... A cellular manufacturing system (CMS) is more flexible and responsive to increasing variety and decreasing product life cycles than process and product layouts (Jia and Kong, 2014) and CMSs could provide a more efficient movement of material and information flow within the complex supply chain networks and more lean processes (Yahia et al., 2017;Maharaja et al., 2017). Reduced material handling cost, intercellular travel, setup time, flow-time, manufacturing lead time, work-in-process inventory, lot size, number of workers, number of machines are some of the reported advantages of CMS (Burbidge and Wei, 1992;Erenay, 2016;Esen et al., 2017;Gothwal and Raj, 2017). The objectives are to design efficient manufacturing cells and product families which maximise productivity of the manufacturing system (Egilmez et al., 2016). ...
This study investigates hybrid cellular manufacturing system design where products with highly similar process routes are formed as manufacturing cells, and products with dissimilar routes are produced in a process layout. A cell similarity threshold, cellularisation ratio (C-ratio), is proposed for product assignment to cells and process layout, and integrated into a mathematical modelling-based cell formation approach. The cell formation phase is carried out with the proposed mathematical model. Several case problems are tested, and selected cases are also studied with a newly developed simulation model where manufacturing system performance is also evaluated along with the proposed hybrid cellular manufacturing design alternatives. Results indicated that considering a C-ratio during cell formation can provide higher cell similarity thus better cell formation. The increase in the coverage levels resulted in higher number of cells formed. The proposed approach can be significantly beneficial for manufacturing design decisions where product mix and process complexity are high, and for a hybrid layout that consists of cellular plus process layouts could be implemented.
... When the production volume is high, but production variety is low, product layout; when production volume is low, but product variety is high, then process layout fits better to the manufacturing system (Erenay, Süer, Huang, & Maddisetty, 2015). In labor intensive manufacturing systems, determining the number of workers in a cell, and assigning the this manpower to cells and operations is a major factor that determines the performance of the entire manufacturing system (Erenay, 2016). ...
In labor-intensive cells, the number of operators assigned to a cell and to the operations determines the performance of the cell. In order to increase the efficiency of the cell, it is extremely important to assign the optimal number of operators for each operation. In this study, a three-stage hierarchical methodology is proposed for the optimal operator assignment, optimal cell size determination, and manpower allocation. The objective is to find the optimal number of operators for each operation using a mathematical model at the first stage. In the second stage, a heuristic approach is developed in order to determine an optimal cell size for each cell using cell size efficiency values. In the third stage, manpower allocation is performed using two different approaches; common cell size and optimal cell size approaches.
Cellular manufacturing system is designed and evaluated according to its profitability under stochastic demand environment. In this paper, the methodology consists of five phases. First, the cellular system is studied through identifying information of processing time and demand for parts according to part-machine matrix and demand data. Then, the cellular system is configured or designed through the following steps: determining means, variance and standard deviation of capacity requirements for parts in family, determining demand coverage probabilities for part family and determining the expected cells utilization. Second, the expected revenues generated by the cellular design are determined. Third, the total expected costs of cells open for part family are determined considering different scenarios of the expected shortages of units. Fourth, the expected profits generated by cells open are determined and finally the decision is made regarding the optimal design that yields the largest profits with its associated demand coverage probability. The results show that although five manufacturing cells meet the expected demand of the part family, three manufacturing cells generate the highest profits for the system
