REFERENCE OVERVIEW ON DESIGN AND SIMULATION OF GREEN SUPPLY CHAIN MANAGEMENT

The issue of decreasing air quality index due to supply chain transportation is one of the problems that must be addressed by the manufacturing sector. Green supply chain management (GSCM) can be a solution to address environmental issues in the supply chain. The GSCM is an integrated view that incorporates environmental considerations into the conventional supply chain, ranging from supplier selection, product design, material selection, manufacturing processes, packaging, and distribution. The correct implementation of GSCM can address both environmental and performance issues, e.g. decreasing both energy consumption and air pollution. The GSCM consists of green design, green manufacturing, green logistics, disassembly, and remanufacturing. To address the GSCM issues, the simulation is also discussed in this work. Meanwhile, this work suggests more policies for recycling, remanufacturing, and reuse of obsolete manufacturing products to support GSCM in developing nations.


INTRODUCTION
The supply chain is a network consisting of suppliers, manufacturers, warehouses, distributors, retailers, and consumers. Through the supply chain, companies develop plans and carry out activities to create or develop products by converting raw materials into finished products. Due to heavy market competition, companies compete in the supply chain of their industry by cooperating with many external parties. This circumstance leads to a less than optimal supply chain network since it increases cooperation among companies but requires less effort to optimize it. In addition, many companies apply conventional supply chains, which always prioritize profits at the lowest possible cost, regardless of environmental aspects [1]. As a result, environmental problems have increased in recent years Tsai and Lin [2] reported a decrease in the air quality index in Taiwan from 18.1% in 2017 to 10.1% in 2020. Of many sources, vehicles used in supply chain activity contribute to this increasing air pollution. Thus, vehicle operation in supply chain activity should consider environmental aspects in order to minimize air pollution. In this case, the environmental aspect is highly considered since social pressure forces companies to implement environmentally friendly activities. As a result, in addition to company policies on employee and production, external policies concerning the environment should be considered [3]. Some of these issues are critical since they can guarantee the success or failure of the entire supply chain network. Of several existing solutions, the design of a green supply chain network is offered in this review paper.
Green supply chain management (GSCM) is an integrated approach that takes into account the environmental aspects of traditional supply chains, including supplier selection, product design, material selection, manufacturing processes, packaging, and distribution. The GSCM also aims to minimize energy consumption and its negative impact on the environment since it considers environmental issues in evaluating production performance. In addition, correct implementation of GSCM can also provide benefits in terms of efficiency, lower production costs, and improved company working conditions, e.g. fresh air or more oxygen for employees. To achieve these aspects, GSCM must be optimally designed using the right method.
This article also reviews the existing literature regarding the use of optimization and simulation methods in green supply chain design, including the hybrid approach, which combines metaheuristics and simulation algorithms to investigate supply chain sequences and dynamic conditions. The widely applied hybrid method is a combination of an optimization model and a simulation system. The simulation part is normally applied when dealing with uncertain problems. However, the simulation makes it difficult to obtain optimal or close-to-optimal solutions. The optimization-model side is therefore required to address this issue [4]. This paper discusses the gray wolf optimizer (GWO) automation model and dynamic simulation, two of many hybrid methods. The GWO is an algorithmic model for determining decision variables [5]. Meanwhile, dynamic simulation can describe a complex system based on a certain pattern [6].

GREEN SUPPLY CHAIN MANAGEMENT
The GSCM concept is very useful in improving environmental performance in the industrial sector. The GSCM is a new concept in supply chain management that considers environmental issues in the industry [7]. Several studies have been conducted on the GSCM concept since its inception in the early 2000s. Soda et al. [8] applied several methods to solve GSCM problems. Jing et al. [9] enriched the GSCM implementation by considering profitability and operational factors to increase competitiveness. Zhao et al. [10] offered to minimize waste and pollution to achieve optimal GSCM. In addition, several studies discussed strategies to increase competitiveness by optimizing both environmental performance and economic factors. Chin et al. [11] explained that all parties, ranging from producers, suppliers, and distributors to consumers, should consider the GSCM issues. For this reason, this work also discusses some important aspects of GSCM, i.e. green design, green manufacturing, green logistics, disassembly, and remanufacturing [12].

Green Design
Green design is product design that considers environmental factors. It aims to minimize the unwanted environmental impact of the product. More precisely, the product is designed to use less energy and emit less pollution during the manufacturing process and produce fewer emissions during use. Prendeville et al. [13] applied the branding of a product as a "green design" product to attract more markets and customers. Kumar et al. [12] conducted a survey to determine which green designs customers were interested in. Pigosso et al. [14] applied a green design philosophy to design products that will have an impact on the company's economic performance. Tischner [15] provided tools to design green products at a low cost. Andrae's et al. [16] provided innovation to green design by involving users in the design process to acquire environmentally friendly products. Ko [17] implemented computer-aided design (CAD) to achieve a lower design cost. Andriankaja et al. [18] applied the eco-opti-CAD method, supported by environmental experts and researchers, to create a green design product. Trentin et al. [19] described green products and sustainable green manufacturing as green design boundaries that should be considered in industrial activity. Hafezi and Zolfagharinia [20] elaborated product development combined with green design and environmental standards to describe an interaction model between consumers, government and industry.
Many works on then-green design included elements. Poux et al. [21] broadened the scope of green design to create a sustainable process and product. Mcaloone and Pigosso [22] considered suppliers and other parties involved in the manufacturing process in the green design process. Tischner and Hora [23] developed a green design by considering lower energy consumption. Sonego et al. [24] created a green design product by using recycled materials to optimize green design from a material point of view. Agrawal and Singh [25] outlined a green design product with reverse logistics. Taghdisian et al. [26] applied green design to decrease CO2 emissions in methane-containing products. However, the implementation of green design has its own challenges, both internal and external. An internal challenge is due to the fact that green products have less flexibility and performance than usual products. Meanwhile, an external challenge is due to market competition. In many cases, a green design product is more costly. Shapira et al. [27] argued that an inefficient combination of design and environment will affect the implementation of green design.

Green Manufacturing
The manufacturing process creates or develops products from raw materials to finished products. The process, however, produces unwanted output as waste, emissions, and residue. Green manufacturing offers a solution to minimize waste from a conventional manufacturing process. To address these challenges, several studies regarding green manufacturing have been worked out. Mittal et al. [28] applied a green manufacturing philosophy to support green processes. They also developed frameworks, e.g. for planning and evaluating green scores, created improvement plans, and then implemented them. Sangwan and Choudhary [29] measured green manufacturing parameters to support performance indicators. Jonrinaldi and Zhang [30] applied a mathematical model to manage suppliers and companies to select green raw materials and components.
Green manufacturing is closely related to cost. Green manufacturing, when worked out correctly, can decrease manufacturing costs. Orji and Wei [31] carried out a method of selecting green technology through costly activities, e.g. modification of processes and materials to decrease waste materials and pollution decreased by decreasing consumption of electrical energy and fossil fuels. Leong et al. [32] researched combination between lean and green manufacturing to reduce manufacturing process cost. Wenzel et al. [33] developed a model production line in green manufacturing to decrease energy consumption during production.
In the implementation of green manufacturing, many challenges exist, e.g. the existence of environmentally friendly technology and methods, increasing costs, employee and customer awareness, etc. Li et al. [34] investigated the influence of consumers and producers, e.g. due to increasing product costs, which can disrupt green manufacturing. Govindan et al. [35] argued that another challenge for green manufacturing implementation is government regulation. Green manufacturing can therefore be more widely applicable in a large company than in a small one due to government regulation. In supply chain activity, a large company can compete better compared to a small company, e.g. the large company can purchase more raw materials at a better price than the small company.

Green Logistics
Logistics comprises the flow of goods from the supplier to the factory and from the factory to consumers. The logistic activity is normally recorded in the database. Green logistics aims to reduce environmental pollution from the logistics process in a variety of ways, such as optimizing the logistic route, such as by using a train or environmentally friendly vehicles, minimizing the transportation of an empty container to reduce fuel loss, which can then reduce air pollution. As a result, several works were devoted to the study of green logistics. De Souza et al. [36] measured the performance of green logistics with a measurement index. Jazairy and Von Haartman [37] ranked the level of green for logistical services. Sureeyatanapas et al. [38] stated that green logistics has a lot of room for improvement. Yu et al. [39] applied a fuzzy mathematical model to model green logistics, which aims to improve the performance of green logistics and minimize logistic costs. Hajipour et al. [40] suggested optimizing the location of logistics warehouses to decrease air pollution while reducing transportation costs. Thus, economic efficiency can increase. Subramanian et al. [41] implemented cloud computing in green logistics at Chinese logistics companies to improve both financial and environmental performance.

Disassembly
Green design, manufacturing, logistics, and disassembly processes are part of GSCM. The disassembly process aims to reduce waste in the environment. Disassembly can be worked out for both usable and unusable products, e.g. products with obsolete technology or damaged products. Then, it is reused, recycled, or reproduced. The disassembled components can be either large components or small ones. After that, these components are categorized based on their level of recycling, reuse, reproduction, recycling, or disposal. By separating these components, the amount of waste product disposed of can be decreased. Kalaychi et al. [42] noted that product disassembly can recover the product's functionality. In green design, product disassembly followed by product reuse should be included in every manufacturing step to decrease waste. Slam et al. [43] outlined the economic factor as a disassembly process by developing a mathematical model for an efficient disassembly process. Wuster et al. [44] modeled the disassembly process by considering human factors and the disassembly path. Peeters et al. [45] proposed a new disassembly process by applying magnetic force and heating. This new process can result in a more efficient and economically sustainable disassembly process.
Achieving a higher efficiency level can also be a reason for product disassembly. Mandolini et al. [46] developed a mathematical model of product disassembly, commencing with the use of connectors in product disassembly and product assembly and improving product performance with connectors. Wang et al. [47] optimized the disassembly sequence by prototyping to be more economical and sustainable. Bentaha et al. [48] created a design to optimize the disassembly process by detailing all disassembly processes, searching for a plausible solution for the disassembly process and defining the most optimal disassembly method. However, several factors can prevent companies from disassembling, e.g. the petite size of the components, the lower economic value of the disassembled components, and the high difficulty level for component recycling or disassembly [49]. Thus, the economic factor in the disassembly process should also be considered [50].

Remanufacturing
Remanufacturing utilizes the disassembled components, which comprises the following steps: selection of products that can be remanufactured, then categorization by product type, disassembly, sterilization, repair, and the last step, reassembling. Remanufacturing delivers many advantages, such as reducing soil and water contamination due to the accumulation of unused and obsolete components. The component accumulation in the soil and water can be harmful to the ecosystem near the dumping yard. Liu et al. [51] revealed that market competition should be considered for the remanufactured products since the remanufactured products have lower quality and quantity compared to new products, i.e., not remanufactured ones. A lower product price is usually used as a selling point for remanufactured products. On the other hand, Li et al. [52] explained that remanufacturing can provide a high-quality product if the remanufactured product, made from recycled components, is designed with higher quality and functionality. Torres-Carrillo et al. [53] applied laser tools in quality control to result in fewer defects in the remanufacturing process. In addition, Dialo et al. [54] described that the business of remanufacturing products is more profitable than regular products if the remanufacturing process is well designed.
However, many challenges remain for remanufacturing, such as the quality of the initial components, scheduling, the quantity of the final product, the product's competitiveness, and the product price. Many studies, therefore, addressed these challenges. Govindan et al. [55] developed the remanufacturing decision framework for remanufacturing planning from design to inventory. Bentaha et al. [48] outlined the idea of lot sizing in remanufacturing by considering the amount of material and disassembly, which will be beneficial in reducing costs. Cunha et al. [56] minimized the cost of remanufacturing by calculating the batch period of products. Oh and Behdad [57] developed a remanufacturing schedule by considering the delivery lead time. Li et al. [58] studied the inventory of remanufacturing by controlling stock, production, and product decomposition. It can be concluded that costs and inventory can be optimized through product remanufacturing [59]. Tao et al. [60] modeled the remanufacturing process by using price, technical, and material parameters. Dong et al. [61] analyzed the economic factors of products returned by consumers at distribution agents. Partners [62] proposed a model that relates sales value and logistics costs to remanufacturing. Fofou et al. [63] argued that the current remanufacturing procedures are influenced by product life cycle factor and the market need for remanufactured products. Kumar et al. [64] applied radio frequency identification (RFID) to oversee the component location in real-time. Zhang et al. [65] developed a multi-criteria model for the technology applied in remanufacturing. The parameters of GSCM studied by many researchers, ranging from design to cost to materials, are outlined in Table 1.

SIMULATION ON SUPPLY CHAIN
Simulation in engineering is applied to model real phenomena, and it aims to decrease cost and accelerate the understanding of the effect of changed parameters on the entire system. Many simulations have been dedicated to supporting the GSCM. Fahimnia and Jabbarzadeh [66] implemented a hybrid method by combining fuzzy, stochastic, and goal programming to research suitability in the supply chain. Khalili et al. [67] planned supply chain production and distribution using stochastic and possibility models. Jabbarzadeh et al. [68] applied stochastic, Robusta and Monte Carlo simulation methods to design demand and risk disturbances in the supply chain. Aqlan and Lam [69] managed the supply chain risks with optimization and simulation methods. Li and Zhang [70] examined locations with limited capacity by using stochastic methods and Monte Carlo simulations. Chiadamrong and Piyathanavong [71] implemented linear programming and simulation to optimize supply chain networks, which is very powerful and effective in illustrating dynamic problems and uncertainties. Costa et al. [72] applied goal programming and simulation to create frameworks and designs that are sustainable in supply chain networks.
Many simulation works are also dedicated to examining logistics, environmental cycles, life cycle assessments (LCA) and community aspects of supply chain networks. De Armas et al. [73] solved optimization problems of logistics, telecommunications networks, and costs with deterministic and stochastic methods. Zhao et al. [74] implemented optimization and simulation methods to plan a supply chain design for green ammonia production in a Chinese company. Guerrero et al. [4] designed a closed-loop supply chain in the company using the grey wolf optimizer (GWO) method and simulation.
De Keizer et al. [75] simulated cost savings in supply chain networks with mixed-integer linear programming (MILP) algorithms and simulation methods. The MILP algorithms handle product quality issues, while simulation is applied to examine the sustainability of products designed by the MILP. González-Hernández et al. [76] designed a food distribution chain network to increase profits from the agricultural industry by using a hybrid model consisting of linear programming and simulation. Dai and Zheng [77] applied simulation and CPLEX 12.6 to design a multi-echelon network that includes suppliers, factories, warehouses, distributors, and consumers. Ye and You [78] established consistent operating costs and quality that can satisfy customers.
A dynamic simulation was widely implemented in GSCM research. The dynamic simulation uses commercial software, e.g. Arena or Stella. Gao and Ma [79] implemented dynamic simulations to model supply chains in manufacturing companies by looking at the bullwhip effect. Yusianto et al. [80] created scenarios with dynamic simulations to increase efficiency in food companies. The resulting scenario generated a fairly higher profit. Guelpa et al. [81] applied dynamic simulation to optimize the system using orthogonal decomposition with high accuracy. Jia et al. [82] increased the efficiency of waste management system by simulating the waste flow.

FUTURE CHALLENGE AND OPPORTUNITY
Due to strong market competition, research on the GSCM issue focuses more on an economic viewpoint than on an environmental one. The GSCM is a complex system originating from design, economy, company performance factors, etc. [83]. In many developing nations, there are less adequate systems and policies for waste sorting, product recycling, and remanufacturing. Strong market competition, as well as a lack of awareness among society and policymakers, contributed to this circumstance. To address this issue, several important regulations regarding waste sorting, product recycling, and remanufacturing should be created in the near future. Companies need these regulations to stay competitive in the market. More studies to create a competitive remanufacturing product should be interesting.

CONCLUTION
Due to strong market competition, research on the GSCM issue focuses more on an economic viewpoint than on an environmental one. The GSCM is a complex system originating from design, economy, company performance factors, etc. In many developing nations, there are fewer adequate systems and policies for waste sorting, product recycling, and remanufacturing. Strong market competition as well as a lack of awareness among society and policymakers contributed to this circumstance. To address this issue, several important regulations regarding waste sorting, product recycling, and remanufacturing should be created in the near future. Companies need these regulations to stay competitive in the market. More studies to create a competitive remanufactured product should be interesting.