Abstract
Recent research underlines the crucial role of supply chain optimization, in terms of maximize profit and minimize cost. Today the stakeholders are also empowered and the organizations are becoming stakeholder-centered, relates to the main objectives of a supply chain are availability and inventory control so the particular aim for availability must relate to stakeholder satisfaction. The implementation of supply chain optimization in tire industry nowadays not only focuses on profit, but also on the environmental and societal effect that is considered as ways to achieve the sustainable supply chain and stakeholder satisfaction. Currently a wealth of literature on supply chain optimization with maximize profit and minimize cost, to the best of our knowledge there is limited state-of-the art review on supply chain optimization considering with economy, environment and stakeholder satisfaction. This manuscript analyze research stream on supply chain optimization with economy objectives such maximize profit and minimize cost, environmental effect and stakeholder satisfaction with the aim to relate the existing optimization methods to empirical research and reveal the conceptual framework. The paper classifies existing research streams and application in tire industry areas with different optimization subject. The results of this study gives outlook which optimization methods are available for supply chain managers and give a conceptual framework in tire industry considering sustainable supply chain factors from economic, environmental and societal effect.
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1 Introduction
Today, millions of tires are used each year and with the growing concern about environmental issues in recent years, the problem of used tires disposal has attracted many practitioners and researchers [1]. World demand for tires increase 4.1% per year and reach to 3.0 billion units in 2019, according to the U.S. Environmental Protection Agency (EPA) report [4]. Hence tire industry is become an important issues for both academics and practitioners. Supply chain optimization is the application of processes and tools to ensure the optimal operation of a manufacturing and distribution supply chain [5]. It can be observed in the existing study that used of problem statements are generally considered:
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Supply chain optimization considerations with sustainable factors
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Supply chain optimization considerations without sustainable factors.
The goal of this study is to classify existing research streams and application in tire industry areas with different optimization subject. The results of this study gives outlook which optimization methods are available for supply chain managers and give a conceptual framework in tire industry considering sustainable supply chain factors from economic, environmental and societal effect.
2 State-of-the-Art Review
2.1 Literature Selection
Supply chain in the tire industry is getting more complex today. Variabilities of market demand and supply add to the complexity [7]. Supply chain optimization is the application of processes and tools to ensure the optimal operation of a manufacturing and distribution supply chain [5]. In order to restrict our research, so we focused the typical supply chain optimization that used in tire industry. Reverse logistic and closed-loop supply chain have an incremental trend in recent years [10]. The single period mixed integer linear programming (MILP) model considering the uncertainty parameters for closed-loop supply chain proposed [11] in their model also the Multi-echelon reverse logistic network adopted by [13] case study at India use mixed integer non-linear programming (MINLP) models to maximize profit.
2.2 Mixed Integer Linear Programming (MILP)
Mixed Integer Linear Programming (MILP) involves problems in which only some of the variables, xi are constrained to be integers, while other variables are allowed to be non-integers. This is why it is called Mixed [14]. A mixed integer linear programming model is designed for the closed-loop supply chain to maximize total profit. The proposed model usually determines the optimum number of distribution, collection, recycling centers and retreading. of products to meet the quality for remanufacturing. In fact, uncertainty is embedded in the optimization model [11].
2.3 Mixed Integer Non-linear Programming (MINLP)
Mixed integer nonlinear programming (MINLP) refers to optimization problems with continuous and discrete variables and nonlinear functions in the objective function and/or the constraints [14]. MINLP arise in applications in a wide range of fields, including chemical engineering, finance, and manufacturing. Closed-loop supply chain with MINLP model use to maximize profit adopted by [16]. Meanwhile MINLP model in reverse logistic proposed by [13] to maximize profit in remanufacturing tire.
2.4 Closed-Loop Supply Chain
The closed-loop supply chain consists of the activity start from design, control, and operation for a system in terms for maximize value creation over the entire life cycle of a product with the dynamic recovery [8]. Designing an economically and ecologically optimized closed-loop supply chain network is a prerequisite for tire producers to facilitate increased environmental responsibility and sustainable development [3].
Some literature reviews papers have been published about closed-loop supply chain in tire industry such as [3] with minimize environment impact and maximize profit [2]. And [17] with the first stage model on maximize profit but in second stage the model focus on sustainable factors such minimize environment and social effect, maximize profit.
2.5 Reverse Logistic
Reverse logistics (RL) has been defined as a term that refer to the role of logistics in product returns, the source reduction, a recycling, the materials substitution, a reuse of materials, a waste disposal, and the refurbishing [9]. Reverse logistics systems use of mathematical tools to design for the recovery of products that have ended their life cycle [18]. Beside the MILP or MINLP model for example, in reverse logistics proposed by [9] to minimize the total cost with genetic algorithm also [19] use fuzzy multi-objective mixed integer program model to maximize total profit and coverage area.
3 Analysis and Observations
3.1 Literature Analysis
Based on literature analysis on supply chain optimization in tire industry, our next objective is to derive some classifications regarding the following issues:
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What types of supply chain optimization should be considered by supply chain managers.
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Which methods are mostly suitable for supply chain in tire industry.
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How to identify challenges in implementations the supply chain optimization in tire industry.
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What the conceptual framework represents the supply chain implementations in tire industry.
For the first step, identify the implementation of supply chain optimization in tire industry as following Table 1 which describes the methodology, evaluated factor and also research method.
3.2 Critical Analysis
Publications specifically for tire industry the research of supply chain optimization are boomed in 2015 until present. In early 2010 there are no significant publications as described in Fig. 1 summary of supply chain optimization implementation research in tire industry in last decade, also the objective function is analyzed. Mostly the recent publication have evaluate factor in economic sector. Sustainable supply chain factor implementation is still limited.
3.3 Managerial Implications
In many practical settings, companies need analysis tools to estimate both the supply chain robustness and sustainable. For sustainable supply chain the objective function need to consider from economic, environment and social impact. Thus the Tables 2 and 3 as the results of classified literature review by objective function categories can contribute to give support decisions reference for supply chain manager in tire industry to implement based on desired objective that match with their company objective.
4 Towards a Conceptual Framework
The developed conceptual framework is expected to provide general guidance [22] on supply chain optimization in tire industry. Figure 2 illustrates the conceptual framework that is constructed based on the analysis of the findings in the literature. The framework comprises four elements, which represent the essential features for successful supply chain optimization implementation in the tire industry:
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(1)
Reliable data support;
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(2)
Sustainable model;
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(3)
Reliable solvers; and
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(4)
Simultaneously implementation.
The contribution from conceptual framework in this manuscript is describing the sustainable supply chain factor that had robust result in the implementation based on literature analysis. Combination of three factors from economic, environment and social impact such provided by [17], [1] and [24] give the robust and sustainable impact in tire industry. Simultaneously factor need to be highlight for supply chain managers in their practical problems to achieve robustness result.
5 Conclusions
Supply chain optimization is crucial part to ensure tire business remains profitable and still have a good relation with stakeholder. The managerial implications and conceptual framework for sustainable supply chain optimization such economic, environment, social factor revealed in this study. Thus it is contribute to supply chain manager in decision support of their practical problem which the best fit method to achieve the company objective.
Although there is a growing research in supply chain optimization, but still it is limited publications to rise focus on stakeholder satisfaction as the objective of the research. In future, social methodology like customer relationship management need to studied further either in the tire business or in other practical industries.
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Alfina, K.N., Ratnayake, R.M.C. (2019). Supply Chain Optimization in the Tire Industry: State-of-the-Art. In: Ameri, F., Stecke, K., von Cieminski, G., Kiritsis, D. (eds) Advances in Production Management Systems. Towards Smart Production Management Systems. APMS 2019. IFIP Advances in Information and Communication Technology, vol 567. Springer, Cham. https://doi.org/10.1007/978-3-030-29996-5_7
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