Optimal manufacturing-remanufacturing policies in a lean production environment

This study analyses a production-management model that considers the possibility of implementing a reverse-logistics system for remanufacturing end-of-life products in a lean production environment (as opposed to models than use EOQ approaches). Decisions variables are identified (including manufacturing and remanufacturing capacities and return rates and use rates for end-of-life products) and optimal policies are determined. Moreover, the structure of these optimal policies is analysed. The conclusion draw is that, in may realistic scenarios, mixed policies (that is, with return rates and use rates strictly between 0 and 1) can be optimal. This conclusion is contrary to results published in earlier studies, which are based on more restrictive assumption

Production planning and control of closed-loop supply chains

More and more supply chains emerge that include a return flow of materials. Many original equipment manufacturers are nowadays engaged in the remanufacturing business. In many process industries, production defectives and by-products are reworked. These closed-loop supply chains deserve special attention. Production planning and control in such hybrid systems is a real challenge, especially due to increased uncertainties. Even companies that are engaged in remanufacturing operations only, face more complicated planning situations than traditional manufacturing companies.We point out the main complicating characteristics in closed-loop systems with both remanufacturing and rework, and indicated the need for new or modified/extended production planning and control approaches. An overview of the existing scientific contributions is given. It appears that we only stand at the beginning of this line of research, and that many more contributions are needed and expected in the future.closed-loop supply chains;Production planning and control

Optimal production planning for a multi-product closed loop system with uncertain demand and return

We study the production planning problem for a multi-product closed loop system, in which the manufacturer has two channels for supplying products: producing brand-new products and remanufacturing returns into as-new ones. In the remanufacturing process, used products are bought back and remanufactured into as-new products which are sold together with the brand-new ones. The demands for all the products are uncertain, and their returns are uncertain and price-sensitive. The problem is to maximize the manufacturer\u27s expected profit by jointly determining the production quantities of brand-new products, the quantities of remanufactured products and the acquisition prices of the used products, subject to a capacity constraint. A mathematical model is presented to formulate the problem and a Lagrangian relaxation based approach is developed to solve the problem. Numerical examples are presented to illustrate the model and test the solution approach. Computational results show that the proposed approach is highly promising for solving the problems. The sensitivity analysis is also conducted to generate managerial insights

Production planning and control of closed-loop supply chains

More and more supply chains emerge that include a return flow of materials. Many original equipment manufacturers are nowadays engaged in the remanufacturing business. In many process industries, production defectives and by-products are reworked. These closed-loop supply chains deserve special attention. Production planning and control in such hybrid systems is a real challenge, especially due to increased uncertainties. Even companies that are engaged in remanufacturing operations only, face more complicated planning situations than traditional manufacturing companies. We point out the main complicating characteristics in closed-loop systems with both remanufacturing and rework, and indicated the need for new or modified/extended production planning and control approaches. An overview of the existing scientific contributions is given. It appears that we only stand at the beginning of this line of research, and that many more contributions are needed and expected in the future

Sustainable supply chain management trends in world regions: A data-driven analysis

This study proposes a data-driven analysis that describes the overall situation and reveals the factors hindering improvement in the sustainable supply chain management field. The literature has presented a summary of the evolution of sustainable supply chain management across attributes. Prior studies have evaluated different parts of the supply chain as independent entities. An integrated systematic assessment is absent in the extant literature and makes it necessary to identify potential opportunities for research direction. A hybrid of data-driven analysis, the fuzzy Delphi method, the entropy weight method and fuzzy decision-making trial and evaluation laboratory is adopted to address uncertainty and complexity. This study contributes to locating the boundary of fundamental knowledge to advance future research and support practical execution. Valuable direction is provided by reviewing the existing literature to identify the critical indicators that need further examination. The results show that big data, closed-loop supply chains, industry 4.0, policy, remanufacturing, and supply chain network design are the most important indicators of future trends and disputes. The challenges and gaps among different geographical regions is offered that provides both a local viewpoint and a state-of-the-art advanced sustainable supply chain management assessment

Developing green supply chain management strategies: a taxonomic approach

Purpose: The objective of this research is to explore the empirical green supply chain activities found in literature, and to develop a taxonomic framework that can be used for formulating appropriate strategies for green supply chains, based on characteristic dimensions for the green supply chain. Design/methodology/approach: The taxonomic framework is developed through (i) analysis of green supply chain activities found in existing empirical work or case studies recorded in literature, (ii) identification of key dimensions that influence green supply chain management strategies, and (iii) development of a taxonomic scheme for selecting or developing green strategies. Findings: The paper finds that this study yielded: a set of three characteristic dimensions that influence strategic green supply chain management, and a guided structured approach selecting appropriate green strategies, providing managerial insights. Research limitations/implications: This paper shows that future work includes development of specific performance management indices according to the taxonomy of green strategies developed in this study. Practical implications: This research provided a practical guided approach that enhances appropriate formulation of green strategies for green supply chain management, while providing sound managerial insights for the supply chain decision maker. The choice of supply chain strategy directly impacts the overall environmental, economic and operations performance of the supply chain. Originality/value: This study presents to supply chain decision makers a new taxonomic framework that simplifies and enhances the formulation of green strategies, and to researchers a comparative understanding of various strategies applicable to green supply chains.Peer Reviewe

Coordinating production and recycling decisions with stochastic demand and return

In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints — the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time

OPTIMAL INBOUND/OUTBOUND PRICING MODEL FOR REMANUFACTURING IN A CLOSED-LOOP SUPPLY CHAIN

The paper presents a model for optimizing inbound and outbound pricing for closed-loop supply chains that remanufacture reusable products. Remanufacturers create reusable products from returned used products and sell the products “as new” to manufacturers or consumers. By implementing a return subsidy, remanufacturers can encourage the consumer to return used products. Demand for the as-new components often depends on the selling price and inventory. The available inventory increases as the subsidy increases and as the price decreases. Our model can determine the optimal subsidy and selling price for used and remanufactured products, respectively. Our model uses the Karush–Kuhn–Tucker conditions to solve its nonlinear problem. Sensitivity analysis reveals how different parameters affect profit under model-optimized conditions

End-of-life vehicle (ELV) recycling management: improving performance using an ISM approach

With booming of the automobile industry, China has become the country with increasing car ownership all over the world. However, the end-of-life vehicle (ELV) recycling industry is at infancy, and there is little systematic review on ELV recycling management, as well as low adoption amongst domestic automobile industry. This study presents a literature review and an interpretive structural modeling (ISM) approach is employed to identify the drivers towards Chinese ELV recycling business from government, recycling organizations and consumer’s perspectives, so as to improve the sustainability of automobile supply chain by providing some strategic insights. The results derived from the ISM analysis manifest that regulations on auto-factory, disassembly technique, and value mining of recycling business are the essential ingredients. It is most effective and efficient to promote ELV recycling business by improving these attributes, also the driving and dependence power analysis are deemed to provide guidance on performance improvement of ELV recycling in the Chinese market