Embedding risk in closed-loop supply chain network design

Robust optimization model for sustainable supply chain for production and distribution of polyethylene pipe

Purpose

In this study, the authors consider the key decisions in the design of the green closed-loop supply chain (CSLC) network. These decisions include considering the optimal location of suppliers, production facilities, distribution, customers, recycling centers and disposal of non-recyclable goods. In the proposed model, the level of technology used in recycling and production centers is taken into account. Moreover, in this paper is the environmental impacts of production and distribution of products based on the eco-indicator 99 are considered.

Design/methodology/approach

In this study, the author consider the key decisions in the design of the green CLSC network. These decisions include considering the optimal location of suppliers, production facilities, distribution, customers, recycling centers and disposal of non-recyclable goods. In the proposed model, the level of technology used in recycling and production centers is taken into account. Moreover, the environmental impacts of production and distribution of products based on the eco-indicator 99 are considered.

Findings

The results indicate that the results obtained from the colonial competition algorithm have higher quality than the genetic algorithm. This quality of results includes relative percentage deviation and computational time of the algorithm and it is shown that the computational time of the colonial competition algorithm is significantly lower than the computational time of the genetic algorithm. Furthermore, the limit test and sensitivity analysis results show that the proposed model has sufficient accuracy.

Originality/value

Solid modeling of the green supply chain of the closed loop using the solid optimized method by Bertsimas and Sim. Development of models that considered environmental impacts to the closed loop supply chain. Considering the impact of the technology type in the manufacture of products and the recycling of waste that will reduce emissions of environmental pollutants. Another innovation of the model is the multi-cycle modeling of the closed loop of supply chain by considering the uncertainty and the fixed and variable cost of transport.

Introducing Risk Considerations into the Supply Chain Network Design

Supply chains (SC) aim to provide products to the final customer at a certain service level. However, unforeseen events occur that impede supply chain objectives. SC Risk has been studied in the literature, providing frameworks and methodologies to manage SC failures. Nevertheless, more efforts are needed to prevent hazardous and disruptive risks and their consequences. These risks must be considered during the process of designing a supply chain. Some methodological contributions concerning risk in the supply chain network design (SCND) are conceptual frameworks for mitigating SC disruptions, which suggest strategies and measures for designing robust and resilient SCs. Although such contributions are valuable, they do not indicate how to cope with risk when designing a SC. The main objective of this research is to describe a methodology aimed at including risk considerations into the SCND. Our proposal aims to be, on the one hand, a comprehensive approach that includes a risk identification and assessment procedure in each of the stages of the SCND process and, on the other hand, a tool for decision-making in SC design or redesign processes when SC risks need to be considered. The methodology proposed is an extension of a SCND methodology including risk considerations in order to improve the performance of the supply chains. A case study illustrates how the proposed methodological works, achieving the identification of SC risks already observed in previous works.

The design and planning of an integrated supply chain for perishable products under uncertainties

Purpose

This paper aims to design an optimal supply chain network and to develop a suitable distribution planning under uncertainty for perishable product's supply chain. The ultimate goal is to help in making decisions under uncertain environments.

Design/methodology/approach

In this paper, stochastic programming is used under conditions of demand, supply and process uncertainties, and a non-linear mathematical model is developed for perishable product’s supply chain. Authors’ study considers disruptions in transportation routes and also within the facilities and investigates optimal facility location and shipment decisions while minimising the total supply chain cost. A scenario-based approach is used to model these disruptions. The retailer level uncertainty due to demand-supply mismatch is handled by incorporating the newsvendor model into the last echelon of supply chain network. In this paper, two policies are proposed for making decisions under uncertain environments. In the first one, the expected cost of the supply chain is minimised. To also consider the risk behaviour of the decision maker, authors propose the second policy through a conditional value-at-risk approach.

Findings

Authors discuss the model output through various examples that are provided via a case study from the milk industry. The supply chain design and planning of the disruption-free model are different from those of the resilient model.

Practical implications

Authors’ research benefits the perishable products industries which encounter the disruption problems in their transportation routes as well as in the facilities. Authors have demonstrated the research through a real-life case in a milk industry.

Originality/value

The major contribution of authors’ work is the design of the supply chain network under disruption risks by incorporating aspects of product perishability. This work provides insight into areas such as the simultaneous consideration of demand, supply and process uncertainties. The amalgamation of newsvendor model and the approximation of the non-linearity of retailer level cost function especially in the context of supply chain under uncertainty is the first of its kind. We provide a comprehensive statistical study of uncertainties that are present in the supply chain in a unique manner.

Analysis of supply chain risk in the ceramic industry using the TOPSIS method under a fuzzy environment

Purpose

Risk management has emerged as a critical issue in operating a supply chain effectively in the presence of uncertainties that result from unexpected variations. Assessing and managing supply chain risks are receiving significant attention from practitioners and academics. At present, the ceramic industry in Bangladesh is growing. Thus, managers in the industry need to properly assess supply chain risks for mitigation purposes. This study aims to identify and analyze various supply chain risks occurring in a ceramic factory in Bangladesh.

Design/methodology/approach

A model is proposed based on a fuzzy technique for order preference using similarity to an ideal solution (fuzzy-TOPSIS) for evaluating supply chain risks. For this, 20 supply chain risk factors were identified through an extensive literature review and while consulting with experts from the ceramic factories. Fuzzy-TOPSIS contributed to the analysis and assessment of those risks.

Findings

The results of this research indicate that among the identified 20 supply chain risks, lack of operational quality, lack of material quality and damage to inventory were the major risks for the ceramic sector in Bangladesh.

Research limitations/implications

The impact of supply chain risks was not shown in this study and the risks were considered independent. Therefore, research can be continued to address these two factors.

Practical implications

The outcome of this research is expected to assist industrial managers and practitioners in the ceramic sector in taking proactive action to minimize supply chain risks. A sensitivity analysis was performed to determine the relative stability of the risks.

Originality/value

This study uses survey data to analyze and evaluate the major supply chain risks related to the ceramic sector. An original methodology is provided for identifying and evaluating the major supply chain risks in the ceramic sector of Bangladesh.

Performance measurement for supply chain management and quality management integration

Purpose

The purpose of this paper is to present a conceptual framework for performance measurement (PM) for the integration of supply chain management (SCM) and quality management (QM).

Design/methodology/approach

A systematic literature review on SCM and QM was conducted to develop key performance measures related to six areas of integration between QM and SCM: leadership; continuous improvement and innovation; sustainability performance; stakeholders; information system; and management and strategic planning.

Findings

Supported by the literature concerning to supply chain quality management (SCQM) integration, a set of nine propositions about performance measures, that contribute to the integration of SCQM, were developed.

Originality/value

This study contributes to QM practices within a supply chain environment from an integrated perspective. Additionally, the propositions have significant implications from both managerial and theoretical perspectives. This study also extends the concept of supply chain quality integration by focusing on key aspects of PM that may help to improve the overall performance of the supply chain.