Supply Chain Design Research Articles

Spatio-temporal feedstock availability and techno-economic constraints in the design and optimization of supply chains: The case of domestic woody biomass for biorefining

A future bio-based economy envisions the transformation of the petrochemical industry into using biomass such as wood (waste) as a major resource. The early-stage evaluation of a biorefinery project requires the optimization of the lay-out of the supply chain considering the spatio-temporal variability of the availability of feedstock and the techno-economical characteristics of the biorefinery process. Therefore, the presented methodology was developed combining three models: (1) a forest management and planning tool providing a detailed prediction on the wood resource availability as well as the harvested feedstock quantity and cost with respect to location and time, (2) a techno-economic assessment model of the biorefinery process (e.g., species-specific conditions, capacity, CAPEX, OPEX), and (3) a strategic supply chain optimization model combining the insights of (1) and (2) into a spatio-temporal explicit supply chain analysis.The developed methodology has been evaluated through a case-study on the emerging reductive catalytic fractionation (RCF) biorefining in the Flanders region (EU) and shows that the most economically interesting configuration is one large biorefinery with a yearly wood chip intake of 150 kton. The biorefinery location reflects the available feedstock distribution in Flanders and is suggested to be situated best in the most forested region. The proposed methodology proved to be dynamic and robust: (1) input data and technical calculations can easily be adapted or updated; (2) the methodology can be applied to a broad range of applications beyond the scope of the biorefinery, to different feedstock choices; (3) the impact of the biorefinery location on e.g. energy balance, CO2 emissions, and financial balance can be assessed.

Supply chain disruptions during COVID-19 pandemic: Key lessons from the pharmaceutical industry

Purpose: This study extends previous research by exploring the key lessons learned by the pharmaceutical industry in South Africa from the COVID-19 pandemic supply chain disruptions.Design/methodology/approach: Having embraced the interpretivist paradigm, 25 supply chain professionals were purposively selected on the basis of their experience and deep knowledge of the industry and interviewed using the semi-structured approach of interviews. A qualitative data analysis programme, ATLAS.ti (version 9.1), was used to analyse the transcripts.Findings/results: Following thematic analysis, the following themes emerged from the primary data: supply networks, demand planning and management, supply chain coordination, inventory management, logistics management and local production.Practical implications: It is crucial to build resilience in the design of pharmaceutical supply chains. A comprehensive demand management strategy and use of data analytics need to be adopted by pharmaceutical companies to improve demand visibility, responsiveness and supply chain resilience. The study also revealed the need for local production, as local skills and enterprises are being developed.Originality/value: This study has extended the body of knowledge on the supply chain disruptions, particularly in the pharmaceutical industry by building on the studies that were conducted during COVID-19, many of which were not based on empirical data. It also points supply chain professionals in a direction which enables them to develop a disruption strategy while providing justification for policymakers to support investment in the development of the requite skills for the pharmaceutical industry and the development of local production facilities.

IoT-BIM and blockchain integration for enhanced data traceability in offsite manufacturing

The transformation of dynamic supply chains within the realm of offsite manufacturing presents a unique and compelling opportunity to effectively respond to shifts in market demand. However, this paradigm shift also entails novel challenges and prospects for streamlining processes, augmenting efficiency, and ultimately driving success across production workflows and logistical operations. Dynamic supply chains necessitate unimpeded access to high-quality, dependable data to facilitate real-time, data-driven decision-making. Furthermore, owing to their inherently intricate nature, these supply chains are subject to a heightened vulnerability to disruptions and delays, surpassing those encountered in traditional supply chains. Against this backdrop, this paper proposes a framework that synthesises the convergence of the Internet of Things (IoT), Building Information Modelling (BIM), and blockchain technology (BCT) into a cohesive and integrated system, thereby optimising the efficiency and transparency of supply chain management operations. The proposed framework takes cognisance of the challenges inherent in ensuring information traceability, mitigating fragmented information, enhancing interoperability, and fortifying reliability throughout the design, production, and implementation phases of assets within dynamic supply chains operating in the offsite manufacturing domain. To illustrate the efficacy of our proposition, we present a framework that exemplifies the seamless integration of a permissioned, open-source distributed ledger, which forms the bedrock of our support infrastructure for IoT and BIM integration.Through rigorous analysis, we showcase the effectiveness of the developed framework in the form of a designed Supply Chain Management Model (SCMM-PDO), which harmonises the physical, digital, and operational layers within a robust system architecture (BCT.IoT-BIM). The integration of these technologies provides a decentralised solution, reinforcing supply chains with improved security, reliability, and quality control mechanisms, thus enhancing the efficiency of the supply chain network. It is anticipated that this transformative integration will yield substantial improvements in key performance indicators (KPIs) such as operational efficiency, cost reduction, and the cultivation of trust and accountability across supply chain activities.The research proposes an IoT and BIM conceptual framework that simulates the dynamic supply chain operations, facilitating real-time analysis and prediction of supply chain participants' behaviours from resources, processes, and assets. Furthermore, the integration of IoT-BIM (digital twinning) with a blockchain-based system, such as Hyperledger Fabric, engenders a secure and transparent framework for the diligent tracking of assets and information throughout the supply chain. The findings of this study offer an all-encompassing conceptual framework for the secure and transparent tracking of asset information by integrating Blockchain-based technologies with IoT and BIM. This research endeavour thus expands the existing body of knowledge, establishing a foundation for future investigations within this proliferating field.

A Fisher-Based Framework for the Circular Integration of Product Development and Supply Chain Design

This research aims to highlight the opportunities for integrating product development (PD) processes and supply chain (SC) design decisions in the transition towards a circular economy (CE). For this purpose, the pivotal role of implementing the R-imperatives (recovering, recycling, and remanufacturing to reducing, rethinking, and refusing) in developing Fisher’s model as a managerial tool for designing the SC for a specific product in a CE context, is investigated. This model has been designed using evidence from the literature, industrial workshops, and site visits conducted within Norwegian industries. According to the outcomes, there are three distinct scenarios for implementing R-imperatives in PD and SC design, each scenario highlights the evolving collaboration between PD and SC managers. The proposed model provides a tool allowing SC managers to start the transition towards CE by developing effective CE strategic plans that align with Fisher’s model, thus designing a more optimal SC for their products.

Design of battery supply chains under consideration of environmental and socio-economic criteria

The demand for electric vehicles is increasing worldwide, leading to a high demand for lithium-ion batteries, whose supply chains are associated with high environmental and socio-economic impacts. Therefore, legal regulations, such as the EU Battery Regulation, force battery manufacturers to use secondary materials, comply with CO2-limits and ensure social conditions along their supply chains. These circumstances make it necessary to assess battery supply chains in terms of their environmental, economic, and social impacts. For this purpose, the life cycle sustainability assessment approach can be used. However, the results of this approach often lead to conflicting goals between and within sustainability dimensions, making it challenging to derive recommendations for more sustainable battery supply chain designs. One approach to solving this problem is to use optimization models that take the three sustainability dimensions into account.To this end, this study aims to combine the results of a Life Cycle Sustainability Assessment of battery supply chains with a decision support model to derive recommendations for action for the design of more sustainable battery supply chains. For this purpose, different spatial-differentiated activities are assessed and included in a decision support model that aims at minimizing the costs of a German battery pack manufacturer, considering environmental, social, and legal restrictions. The decision support model is implemented in Python and solved using Gurobi. The results of the decision support model are compared with the current state of battery supply chains as a benchmark. The result of the study shows that in many of the scenarios studied, the cost, as well as the environmental and social impacts, can be significantly reduced compared to the benchmark. However, if the environmental and social impacts were to be reduced strictly, this would lead to higher costs compared to the benchmark. Furthermore, the results show that a European-centric supply chain would emerge for more environmentally friendly supply chains, while for a more socially friendly supply chain, the focus would be on Japan.

Network science indicators and their relationship with performance during disruptions: a case study

Interest in supply chain (SC) resilience has increased in the wake of the pandemic and other crises, including those related to political and environmental instability. The literature offers some contributions to proactive indicators to assess the resilience of a system before a disruption occurs. Other studies provide metrics to assess resilience from the reactive perspective after the onset or end of a disruption. This paper examines the application of some proactive indicators from network science to some post-disruption measure of resilience, especially how these measure evolves as a function of time. We examine this by testing different supply chain designs against disrupted scenarios and using data from a real-life industry. The focus is on service level as a performance metric. The tested indicators correlate well with performance loss but show a limited ability to correlate with metrics representing SC dynamics. The practical contribution of this paper is an approach to measure SC resilience as an inherent property of the system, which can aid in designing future SCs, rather than measuring resilience as a response to a disruptive event. The paper also provides theoretical contributions, including the further validation of certain indicators from the literature and the identification of research areas in need of new metrics.

Development of supply chain risk mitigation framework in the digital era

In the context of digital transformation, supply chains contend with various challenges, and reconfiguration of supply chain design has obtained significant consideration in today’s digital era. This paper aims to reveal the adaptability of Industry 4.0 technologies to risk mitigation in supply chain design and develop a conceptual Framework. Analytic Hierarchy Process (AHP) method was used to create a conceptual risk mitigation framework and validated it through a comprehensive questionnaire collected by industrial and academic experts and academics and carried out the pairwise comparison between the main criteria and sub-criteria The contribution of this study lies in the taxonomy study, and findings revealed that digitalisation of supply chain design for risk mitigation shed light on future research. Additionally, it focuses on the potential to enhance supply networks’ efficiency and responsiveness.

Sustainability implications of establishing a circular European supply chain of battery materials

The increasing number of electric vehicles worldwide leads to strategic challenges in designing battery supply chains. More sites for raw material extraction, battery production, and recycling will be needed to fulfill the future battery demand and the legislative goals regarding recycling rates, recycled content, CO2-limits, and social standards from the European Union for sustainable batteries. Battery manufacturers must also design their supply chains cost-efficiently to compete with non-European battery manufacturers. The environmental and socio-economic impacts of supply chains depend significantly on the supply chain design, which is expected to change in the upcoming years. Therefore, this study aims to investigate battery supply chains in the status quo and 2035 regarding all three sustainability dimensions using the life cycle sustainability assessment (LCSA). The status quo is modelled based on current market shares and without circular supply chains. For 2035, circularity is added with secondary materials in the production and more European-centered supply chains by moving the cell production and the recycling fully to Europe. The results provide insights into the design of sustainable battery supply chains. They highlight that moving a big part of the supply chains to Europe has a more significant influence on the environmental, social, and economic impacts than the circularity of materials. However, the results depend on the current supply chain design and future developments of products and processes as well as the electricity mix.

A risk-averse sustainable perishable food supply chain considering production and delivery times with real-world application.

In recent years, a relatively novel paradigm known as sustainable development has been introduced in response to concerns regarding the adverse impact of industrial activities on the environment and society. Managers in the food sector have been attempting to incorporate the principle of sustainable development in their supply chains owing to the paramount importance of social and environmental considerations in creating a competitive advantage for food products. To this end, we propose a multi-objective linear mathematical model considering the three dimensions of sustainability, i.e. economic, environmental, and social, to design a sustainable food supply chain. Given today's volatile business environment, we employ a robust optimization model by incorporating Conditional Value-at-Risk into the configuration of two-stage stochastic programming to tackle uncertainty and take up a risk-averse strategy in supply chain design. The model aims to identify the optimal production and delivery times of the products, investigate the effects of their perishability characteristic on inventory decisions, and assess the financial and environmental advantages of transportation decisions to improve the sustainability of logistics operations. A novel version of fuzzy goal programming approach is applied to solve the proposed model. Next, the applicability of the proposed model and its solution method is verified based on computational experiments on a real-world case study of a processed food company. Lastly, conflicts between the sustainability aspects are examined, and several sensitivity analyses on risk-aversion parameters are performed to provide managerial insights for industry executives seeking to optimize their network concerning sustainability issues and well-performance under worst-case scenarios.

Supply Chain Management Analysis and Design for a Variety of Economic Scenarios, Including Data and System Administration

Supply Chain Management Analysis and Design for a Variety of Economic Scenarios, Including Data and System Administration

Leveraging graph theory approach for managing design principles for sustainable manufacturing of industry 4.0: A case study of electrical equipment manufacturing industry

Analyzing design principles and supply chain sustainability are critical for organizational success in today's competitive marketplace. The process of evaluating an organization's supply chain design principles and manufacturing sustainability entails incorporating various sources of information, which are typically uncertain, incomplete, and subjective in nature. Particularly when various organizations are confronted with significant principles such as a lack of interoperability, decentralization, virtualization, real-time and capabilities, service orientation, and so on. Using graph theory and a matrix approach (GTMA), this article attempts to analyze the interaction between design principles-related factors with a focus on operational excellence, growth and sustainability in supply chains by considering the business of Industry 4.0. We have considered electrical equipment manufacturing Industry 4.0 as test ground. Based on a literature review and expert opinions, we identified several key principles, and then explored the most significant one using graph theory and a matrix approach. The findings indicate that autonomy has been evaluated as the most significant challenge to manage design principles most effectively for sustainable manufacturing in the Industry 4.0 context. Therefore, organizations must enhance autonomous systems capable of operating and making decisions alone, without relying on external instructions or support, in order to achieve sustainability. This and the other identified principles to achieving corporate supply chain sustainability are ranked in this paper. These findings will be useful for managers and policymakers managing the interaction between people and processes, as well as corporate sustainability management in Industry 4.0-based supply chain organizations. The unique contributions of this paper can aid in the improvement of design principles and the sustainability of emerging economies' Industry 4.0 perspectives.

Supply Network Risk Mitigation-Industry 4.0 Approach

With the evolution of Industry 4.0, the most advanced technologies have been invented and due to rapid globalisation, supply chains (SC) have become vulnerable to various risks. Risk management performs a key role in operating SC effectively in variety of uncertain circumstances. This paper aims to reveal the adaptability of digital technologies in supply chain networks, identify and analyse the various emerging supply chain risks in the industry 4.0 environment, and develop a framework to mitigate the risk level. A systematic literature review was conducted to identify and analyse the emerging supply chain risks, and Analytical Hierarchy Process (AHP) method was used to develop a conceptual risk mitigation framework. The contribution of this study lies in the taxonomy study, and findings revealed that digitalisation of supply chain design for risk mitigation shed light on future research. Additionally, it focuses on the potential to enhance supply networks' efficiency and responsiveness.

Presenting a two-echelon multi-objective supply chain model considering the expiration date of products and solving it by applying MODM

The supply chain (SC) as the most significant factor influencing competitive advantage has a great impact on the organization's life and progress. Considering the expiration date of products in supply chain modeling is essential for ensuring operational efficiency, reducing waste, maintaining product quality, and ultimately driving business success. Therefore, this paper provides a two-level supply chain including manufacturer and distributor then chain modeling with considered conditions and applying the concept of Markowitz's theory. Finally, drawing the optimal cost curve of producer and distributor as an efficient frontier. For this purpose, the main contribution of the paper is determining the optimal cost of each level of the chain if the cost of another level is known and increasing the power of analysis. The proposed model applied in Darupakhsh Manufacturing Company and Mahya Daroo Distribution Company, a two-echelon supply chain design, including a manufacturer and a distributor is developed. At first, this chain is modeled, and then, implementing the concept of Markowitz theory, the optimal cost curve of producer and distributor is drawn as an efficient frontier. Findings show it is found that the optimal cost of the two echelons of the chain is inversely correlated and decreases with the increase of another one. Furthermore, it is found that the producer warehouse limit is redundant and has no effect on the final response. Also, with the increase in the cost of the manufacturer, the number of deliveries decreases, and instead, the number of products in each delivery increases, which results in a reduction in the costs of the distributor.

Blockchain-enabled Safeguard Mechanism in SCP-based Relief Supply Chain Designs in Response to Long-term Disasters

Blockchain-enabled Safeguard Mechanism in SCP-based Relief Supply Chain Designs in Response to Long-term Disasters

Design and optimization of a pharmaceutical supply chain network under COVID-19 pandemic disruption

Efficient management of pharmaceutical supply chains during the COVID-19 pandemic is critical to mitigate material and human losses. This paper addresses the design of a pharmaceutical supply chain network under pandemic disruption, introducing a novel bi-objective mathematical model. Traditional supply chain management strategies often fall short in the face of sudden disruptions, necessitating the development of resilient systems. Our model seeks to minimise economic costs and shortages as primary objectives, addressing the specific challenge of sudden surges in demand for pharmaceuticals. To enhance resilience, we propose solutions including the establishment of temporary distribution points and the creation of backup inventory. We employ a scenario-based, discrete, and linear modelling approach, solving the model using goal-planning methods and validating its efficacy through numerical examples. Additionally, we conduct a case study in the metropolitan area of Mashhad, further demonstrating the applicability and effectiveness of our approach. This research contributes to the advancement of resilient supply chain design in the pharmaceutical sector, offering insights that can inform improved management practices and bolster resilience in pharmaceutical supply chains.

Sustainable supply chain design: A case of collaborative wholesale distribution

We assess the cooperative network design's efficiency outcomes in Morocco's food wholesale distribution. Before joining the collaborative coalition, we provide decision-makers with an initial preference instrument to assess the environmental and financial effects of cooperative freight distribution. We assess the practicality of incorporating decisions from the Facility Location Problem (FLP) and Vehicle Routing Problem (VRP) into partnerships for sustainable freight transportation. The coalition utilizes a 3PL provider's fleet of cars, therefore the Vehicles are exempt from having to go back to the consolidation depot; as a result, the fundamental issue becomes an open location routing problem (OLRP). Although there have been several studies on open location-routing problems, their application to horizontal shipper collaboration is new. For diverse collaboration scenarios, our computational approach is founded on two-echelon OLRP under a multiple objective and periods’ framework. Every shipper involved in the partnership needs to receive gains. Therefore, evaluating the benefits to each individual shipper is essential for an effective and durable collaboration. This study addresses the issue of profit allocation to determine the collective and individual shipper's savings. By considering not just economic variables but also environmental factors, the Open LRP may help firms plan and optimize their collaborative supply chains in a more sustainable manner.

A novel multi-objective stochastic model and a novel hybrid metaheuristic for designing supply chain network under disruption risks to enhance supply chain resilience

Supply chains are vulnerable to various disruption risks that can adversely affect their overall performance and objectives. This study addresses the challenge of designing a resilient and environmentally sustainable mixed open and closed-loop supply chain network that can withstand both operational and disruption risks. The research employs a bi-objective stochastic mathematical model to examine the balance between environmental sustainability and profitability within the SC. To mitigate the impact of disruptions, several resilience strategies are incorporated into the model, significantly reducing their adverse effects. Due to the inherent complexity of the problem, the study introduces a novel hybrid metaheuristic algorithm that combines ant colony optimization with teaching and learning-based optimization, named ACO-TLBO. Additionally, two other enhanced hybrid metaheuristics are proposed. The performance of these solution methods is assessed through various test problems, using specific performance metrics for comparison. Results reveal that the ACO-TLBO algorithm excels in generating high-quality, non-dominated solutions. The model's practical applicability is demonstrated through a case study in the tire industry, validating its effectiveness. The findings indicate that the proposed resilience strategies are crucial for minimizing the negative impacts of disruptions on SC objectives. Furthermore, the results underscore the importance of resilience in maintaining both sustainability and profitability within supply chains.

SUPPLY CHAIN DESIGN: A CASE STUDY IN A PULP AND PAPER COMPANY

This paper comprehensively analyzes a company’s supply chain design process in the pulp and paper industry. It focuses on the company’s supply chain strategy, structure, operations, and performance and highlights the challenges and opportunities specific to the industry. The purpose of this case study is to show how effective supply chain design can improve a company’s competitiveness and success. This paper also offers recommendations for improving supply chain design in the pulp and paper industry and other similar industries.

Impact-oriented risk management: guiding practitioners towards a resilient supply chain design

ABSTRACT In times of crisis, resilience has become a popular buzzword in supply chain management as a counterpart to efficiency and lean management. But how can supply chain resilience be addressed by companies and how can a process for assessing it be designed and established? The aim of this paper is to highlight the issue from both a practical and a scientific perspective, and to point the way forward for practical research. We present the strategic concept of an impact-oriented approach that, in contrast to standard risk management, proposes to first analyze the material flows of a supply chain to uncover its vulnerable elements before identifying specific risk events. The approach is flanked by three Practitioner Principles for resource-efficient application: i) use existing data in a reduced and structured manner, ii) examine Key Resilience Areas to assess vulnerabilities, and iii) consider the resilience appetite of supply chain managers.

Retracted: Research on Optimal Design of Short-Life Cycle Product Logistics Supply Chain Based on Multicriteria Decision Model

Retracted: Research on Optimal Design of Short-Life Cycle Product Logistics Supply Chain Based on Multicriteria Decision Model