Design Of Supply Chain System Research Articles

Adaptive Supply Chain System Design for Fruit Crops under Climate Change

There is an urgent need for adaptive supply chain strategies that can mitigate the effects of climate change on the agricultural system. This study introduces a new mathematical model, Capacitated Facility Location Problems with Multi-Period (CFLP-MP), to respond to this challenge. Unlike existing models, the CFLP-MP framework is designed to optimize the supply chain system design of facility locations and transportation routes by accommodating changes in production and demand for multiple time periods. The proposed model can be extended to other time-sensitive agricultural foods, but in this research, it is applied to the U.S. apple industry as a case study. Despite varying conditions, the model demonstrates resilience in maintaining its operational efficiency, thereby offering a solution to the initial challenge of creating an adaptive agricultural supply chain system. In conclusion, this research offers a versatile toolset for enhancing resilience and sustainability in fruit crop production, precisely addressing the climate-induced challenges identified above.

Design of Supply Chain System Based on Blockchain Technology

As the interaction between companies becomes more and more complex, the problems of asymmetric information, weak traceability, and low collaboration efficiency in the traditional centralized supply chain are becoming increasingly prominent. To solve these problems, this paper designs a supply chain system based on blockchain. With the help of trade chain and information chain platforms, an overall framework of the supply chain system is constructed. By formulating platform interaction rules, the system information exchange format is standardized to ensure the stability and efficiency of system interaction. Smart contracts are used to manage supply chain system transactions and information interactions to achieve efficient and convenient information sharing, ensuring the security and reliability of supply chain information. The comprehensive performance of the system is evaluated through experiments. Experimental results indicate that while the system realizes the basic functions of the supply chain, it can promote the sharing of information between participants and improve its efficiency.

Research on the Optimization Design of Supply Chain System of Jilin Chemical Industry

The chemical industry plays an important role in the national economy and social development of Jilin Province, especially the competition among enterprises turns to the competition among the supply chains of enterprises at this stage. The optimization of the supply chain system plays an important role in accelerating the development of enterprises and improving the economic benefits of enterprises. Therefore, based on the characteristics of chemical enterprises, this paper discusses the supply chain optimization path from six aspects: technical resources, procurement resources, marketing resources, logistics services, production resources, and information resources. Enhance the overall competitive advantage of Jilin province's chemical industry, so that it can play a better role in the social and economic development.

Intelligent Supply Chain Information System Based on Internet of Things Technology under Asymmetric Information

The hardware and software designed in the traditional supply chain system lack cooperation in the transmission process, have low efficiency, and lead to a large amount of information distortion.In response to this problem, this paper proposes an intelligent supply chain information system based on the Internet of Things technology. The research focuses on the hardware and software of the system. The hardware part consists of the embedded processor CS89712, Flash7861 memory, Ethernet, touch screen, and LCD (Liquid Crystal Display). The software system is based on asymmetric information theory design and is divided into signal acquisition, input signal detection, interference signal processing, and power signal output. The experimental results show that it is compared with the traditional supply chain information system. The designed system seamlessly integrates the hardware and software components to achieve maximum information supply in the shortest amount of time. The power supply capacity is four times that of the traditional system, and the node coverage is high. When the number of data nodes is 120, the traditional supply chain system is basically unable to supply, but the supply accuracy of the intelligent supply chain is still as high as 48%. The research in this paper has certain guiding significance for intelligent technology development, supply chain system design, and enterprise information exchange.

Sustainable Supply Chain System Design and Optimization

Due to increasing concerns about the environment, potential economic benefits and legislation pressure; supply chain management has changed to focus on the environmental impacts of production and Earth resource preservation. Therefore, many managers are working hard on improving the sustainability of their supply chain systems. In this paper, we present the themes addressed, and the approaches used in this special issue to investigate the design and optimization of sustainable supply chain systems. Firstly, we introduce the topics under investigation, and then we present the published articles to discuss the benefits of sustainable supply chain systems in raising profits and improving ecology. This issue increases our knowledge of the sustainable supply chain systems design and sustainable strategies.

A Stochastic Linear Programming Method for the Reliable Oil Products Supply Chain System With Hub Disruption

This paper focuses on a reliable design of oil products supply chain system, which is conductive to promote the sales of oil products. A multi-scenario MILP (Mixed Integer Linear Programming) model coupled with Monte Carlo sampling is employed for optimizing the supply chain system with considering the transportation process of oil products, the stochastic hub disruption and the demand uncertainty. A real-world case is presented to illustrate the accuracy, applicability and efficiency of the proposed model. High-quality solutions are obtained successfully under deterministic conditions as well as uncertain conditions. Then, the effect of uncertainties on the supply chain system design is also analyzed. Finally, the results demonstrate that the stability and flexibility of the designed supply chain system could be substantially improved with less extra costs.

Robust Optimization Method to Green Biomass-to-Bioenergy Systems under Deep Uncertainty

This paper presents a robust optimization method to deal with the deep uncertainty of a green biomass-to-bioenergy supply chain system design. The proposed model is triggered to minimize the total costs including establishing facilities costs, material flow costs, and inventory holding costs and to maximize carbon trade. In the proposed model, carbon dioxide emissions (CO2-equivalent) of all involved processes are calculated through Eco-indicator 99 method employing SimaPro software. Due to a lack of historical information about the parameters of the proposed model, set-induced robust optimization method is utilized to model the deep uncertainty of parameters. The proposed model is implemented in a real case in Iran. The results justify the efficiency of the proposed model in designing a green biodiesel supply chain network.

Cost efficient robust global supply chain system design under uncertainty

Brutal competitions in today’s global supply chain have forced business enterprises to focus attention on their supply chains. These issues have guided this research to introduce a supply chain service level measure and develop a novel robust design optimization (RDO) approach to assure service level rate requirements and minimize total service level costs. A supply chain system design must maintain its efficiency over time while coping with the uncertainty in production and transportation. Unexpected delay in the product flow can render the supply chain system inefficient with respect to service level costs. Analytical models for the determination of the risk involved in a supply chain system design are difficult to derive when uncertainty is involved in the supply chain. In this paper, the service level rate measure approach is detailed first. Then, the methodology for the robust design optimization-based approach is provided. Two case studies are performed to demonstrate the effectiveness of the proposed service level measure and developed robust design optimization model. Results from the two case studies have shown that by implementing the developed robust design optimization approach, a system is able to achieve a 90 % service level rate while minimizing performance cost and uncertainty impact.

Evaluating the value proposition for improving vaccine thermostability to increase vaccine impact in low and middle-income countries

The need to keep vaccines cold in the face of high ambient temperatures and unreliable access to electricity is a challenge that limits vaccine coverage in low and middle-income countries (LMICs). Greater vaccine thermostability is generally touted as the obvious solution. Despite conventional wisdom, comprehensive analysis of the value proposition for increasing vaccine thermostability has been lacking. Further, while significant investments have been made in increasing vaccine thermostability in recent years, no vaccine products have been commercialized as a result. We analyzed the value proposition for increasing vaccine thermostability, grounding the analysis in specific vaccine use cases (e.g., use in routine immunization [RI] programs, or in campaigns) and in the broader context of cold chain technology and country level supply chain system design. The results were often surprising. For example, cold chain costs actually represent a relatively small fraction of total vaccine delivery system costs. Further, there are critical, vaccine use case-specific temporal thresholds that need to be overcome for significant benefits to be reaped from increasing vaccine thermostability. We present a number of recommendations deriving from this analysis that suggest a rational path toward unlocking the value (maximizing coverage, minimizing total system costs) of increased vaccine thermostability, including: (1) the full range of thermostability of existing vaccines should be defined and included in their labels; (2) for new vaccines, thermostability goals should be addressed up-front at the level of the target product profile; (3) improving cold chain infrastructure and supply chain system design is likely to have the largest impact on total system costs and coverage in the short term—and will influence the degree of thermostability required in the future; (4) in the long term, there remains value in monitoring the emergence of disruptive technologies that could remove the entire RI portfolio out of the cold chain.

A Supply Chain of Things: The EAGLET Ontology for Highly Visible Supply Chains

Recently, technological developments, such as radio frequency identification (RFID), have facilitated the identification of individual things and information sharing regarding their behavior throughout the supply chain. Such developments have generated the capabilities of a highly visible supply chain (HVSC): a supply chain where the location of arbitrary individual things can be determined at any point in time by all appropriate supply chain partners, made possible by an “Internet of Things” for the supply chain, referred to as a “Supply Chain of Things.” A critical component of a Supply Chain of Things is an ontology to facilitate the visibility and interoperability of things along the supply chain. As a result, the objective of this paper is to define an ontology that leverages the availability of an individual thing’s (object) identification information within the context of a standard set of economic phenomena that support multiple views in a range of data architectures. Our design science approach begins with a set of ontological primitives and gradually defines structuring principles that provide guidance for the design of supply chain systems that are characterized by increased visibility and interoperability and which facilitate management of and collaborative decision making about supply chain activities. The EAGLET ontology is named after its five primitives: Event, AGent, Location, Equipment, and Thing. The following are some of its unique characteristics: location and equipment are recognized as ontological primitives, and creating and destroying of containment structures is explicitly modeled; the economic phenomena underlying the supply chain are defined from an independent view, as opposed to a trading-partner view; the supply chain is defined from three different perspectives: the physical flow, the chain of custody, and the chain of ownership; event sequences that resemble the economic scripts underlying the supply chain are defined.

A supply chain of things: The EAGLET ontology for highly visible supply chains

Recently, technological developments, such as radio frequency identification (RFID), have facilitated the identification of individual things and information sharing regarding their behavior throughout the supply chain. Such developments have generated the capabilities of a highly visible supply chain (HVSC): a supply chain where the location of arbitrary individual things can be determined at any point in time by all appropriate supply chain partners, made possible by an “Internet of Things” for the supply chain, referred to as a “Supply Chain of Things.” A critical component of a Supply Chain of Things is an ontology to facilitate the visibility and interoperability of things along the supply chain. As a result, the objective of this paper is to define an ontology that leverages the availability of an individual thing's (object) identification information within the context of a standard set of economic phenomena that support multiple views in a range of data architectures.Our design science approach begins with a set of ontological primitives and gradually defines structuring principles that provide guidance for the design of supply chain systems that are characterized by increased visibility and interoperability and which facilitate management of and collaborative decision making about supply chain activities. The EAGLET ontology is named after its five primitives: Event, AGent, Location, Equipment, and Thing. The following are some of its unique characteristics: location and equipment are recognized as ontological primitives, and creating and destroying of containment structures is explicitly modeled; the economic phenomena underlying the supply chain are defined from an independent view, as opposed to a trading-partner view; the supply chain is defined from three different perspectives: the physical flow, the chain of custody, and the chain of ownership; event sequences that resemble the economic scripts underlying the supply chain are defined.

Supply chain system design integrated with risk pooling

This paper considers the location, production–distribution and inventory system design model for supply chain for determining facility locations and their capacity. Risk pooling effect, for both safety stock and running inventory (RI), have been incorporated in the system to minimize the supply chain cost along with determining facility location and capacity. In order to study the benefit of risk pooling for safety stock and RI two cases have been considered, first when retailers act independently and second when DCs-retailers work jointly. The model is formulated as mixed integer nonlinear problem and divided into two stages. The first stage determines the optimal locations for plants and flow relation between plants-DCs and DCs-retailers. At this stage the problem has been linearized using piece-wise linear function. Second stage enumerates the required capacity of opened plants and DCs. The first stage problem is further divided in two sub-problems using Lagrangean relaxation. First sub-problem determines the flow relation between plants and DCs whereas; second sub-problem determines the DCs- retailers flow. Solution of the sub-problems provides the lower bound for the main problem. Computational results reveal that main problem is within the 8.25% of the lower bound and significant amount of cost reduction can be achieved for safety stock and RI costs when DC-Retailer acts jointly.

Network analysis of supply chain systems: A systematic review and future research

AbstractSupply chains are continuously evolving and adapting systems driven by complex sociotechnical interfirm interactions. Traditional engineering and operations management modeling approaches have primarily focused on technical issues and are not well suited to effectively capture the many complex structural and behavioral aspects of supply chain systems (SCSs). There is growing recognition by the supply chain community of the significant benefits a network analytic lens can provide to understand, design, and manage SCSs. We systematically review and analyze the relevant literature and, drawing on a multidisciplinary theoretical foundation, develop an integrative framework. Our framework identifies three distinct, but interdependent themes that characterize the study of SCSs: SCS network structure (i.e., system architecture), SCS network dynamics (i.e., system behavior), and SCS network strategy (i.e., system policy and control). We elaborate on these themes, review key findings, identify the current limitations and knowledge gaps, and discuss the fundamental benefits derived from adopting an integrated SCSs perspective. We conclude with future research directions for network analysis in SCS design and management, in particular, and complex enterprise systems, in general. ©2012 Wiley Periodicals, Inc. Syst Eng 16:

An integrated model of dynamic cellular manufacturing and supply chain system design

In a global dynamic environment, there is a need to develop organizations and facilities significantly more flexible and responsive. This work proposes an integrated model of dynamic cellular manufacturing and supply chain design with consideration of various issues such as multi-plant locations, multiple markets, multi-time periods, reconfiguration, etc. The model objective was to minimize the sum of various costs such as facility/plant to market transportation cost, part holding cost at a facility/plant, part outsourcing cost, machine procurement cost, machine maintenance overhead cost, machine repair cost, production loss cost due to machine breakdown, machine operation cost, setup cost, tool consumption cost, inter-cell travel cost, intra-cell travel cost, and system reconfiguration cost for the entire planning time horizon. To study the model, three procedures—LINGO, artificial immune system, and hybrid artificial immune system—are used to perform computational experiment on some problems from existing literature. The best result generally is found by the hybrid artificial immune system algorithm.

Supply Chain Systems—Recent Trend in Research and Applications

Supply chains consist of a number of autonomous companies that make decision independently. In this paper applications of various system approaches from theoretical to implementation issues of supply chain systems are discussed. This special section is a collection of original re search that addresses various aspects of supply chain systems design, implementation, and applications.

Transferring academic decision models to practitioners: a structured process

The decision support model presented in this paper is the result of a research project initiated by a large organisation operating in an emerging economy. The exotic business context of this company generated many reservations and questions about the applicability of traditional supply chain management models in terms of the decisions that should be made to design a supply chain. As supply chain management decisions are complex, decision makers often rely on approximate, ineffective decision making processes. Through a process rooted in decision analysis, this paper shows how apparently conflicting academic models of supply chain system design were successfully transferred, absorbed, customised and used by the company.

An enterprise engineering approach for supply chain systems design and implementation

This paper reports research into the specification and implementation of an Information Technology (IT) Route Map for supply chain systems development and deployment. The purpose of the Map is to enable rapid design and implementation of IT solutions, capable of semi-automating business processes within manufacturing supply chains. The Map helps structure transition processes involved in 'identification of key business strategies and design of business processes' and 'choice of supply chain systems and supporting implementation techniques'. Common limitations of current Enterprise Resource Planning (ERP) systems are observed and incorporated as IT Route Map implications and constraints. Scope of investigation is targeted at Small-to Medium-sized Enterprises (SMEs) that employ Engineer-To-Order (ETO) and Make-To-Order (MTO) business processes. In the course of the research a 'Business Strategy Driven IT (BSDIT) System Concept' was conceived and examined. Part-evaluation of the applicability and capabilities of the IT Route Map has been carried out by conducting industrial survey and case study work.

Queueing networks and the topological design of supply chain systems

Manufacturing firms are linking their internal processes to external suppliers and customers. The resulting supply chain is often a very large network of activities and resources. Modeling and optimization of such complex systems is a new area of research for which exact analytical results are obviously very difficult if not impossible. We develop a methodology based on analytical queueing networks coupled with nonlinear optimization to design supply chain topologies and evaluate various performance measures. The results obtained from small network configurations as well as from the case study discussed in the paper demonstrate that our approach is a very useful tool to analyze congestion problems and to evaluate the performance of the network topologies.

Guidelines for Collaborative Supply Chain System Design and Operation

Over the past decade, firms have adopted supply chain management as a critical element of their corporate strategies. Despite these efforts, it is our observation that many firms do not realize the...